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TZID:Asia/Kolkata
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DTSTART:20250101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20260306T120000
DTEND;TZID=Asia/Kolkata:20260306T130000
DTSTAMP:20260921T152941
CREATED:20260303T103646Z
LAST-MODIFIED:20260303T103646Z
UID:2432-1772798400-1772802000@homecse.iitd.ac.in
SUMMARY:Neural Circuit Discovery via Representation and Dynamics by Savik Kinger
DESCRIPTION:Abstract: Neuroscience and AI share a bottleneck: while one can build (artificial) or record (biological) complex networks\, we struggle to explain their functional circuitry; i.e.\, how they compute. In this talk I use whole-brain recordings from C. elegans\, a canonical neurobiological system\, as a concrete testbed for “circuit interpretability.” I then introduce two complementary inference approaches for turning high-dimensional activity data into mechanistic structure. Approach 1 treats circuit discovery as a representation problem: learn time-varying functional structure and uncover recurring\, stimulus-dependent modules rather than a single static connectivity map. Approach 2 treats circuit discovery as a dynamics problem: go beyond correlation to estimate directed\, time-lagged influence—i.e.\, which units appear to drive others and over what delays—using modern score-based generative modeling ideas. I will show how these ML methods produce testable hypotheses for biologists and\, potentially\, offer new avenues for understanding complex networks in AI. \nBio: Savik Kinger is a PhD candidate in Computer Science at Yale University\, advised by Steven Zucker. His research focuses on developing methods to analyze biological and artificial neural networks\, integrating ideas from machine learning\, dynamical systems\, and causal inference. He received Bachelor’s degrees in Math and Computer Science from Columbia University. He is supported by a Nathan Hale fellowship.
URL:https://homecse.iitd.ac.in/event/neural-circuit-discovery-via-representation-and-dynamics-by-savik-kinger/
LOCATION:SIT 113\, Amar Nath and Shashi Khosla School of Information Technology\, Indian Institute of Technology\, Delhi\, Hauz Khas\, New Delhi\, Delhi\, 110016\, India
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20260202T120000
DTEND;TZID=Asia/Kolkata:20260202T130000
DTSTAMP:20260921T152941
CREATED:20260115T072749Z
LAST-MODIFIED:20260115T072749Z
UID:2365-1770033600-1770037200@homecse.iitd.ac.in
SUMMARY:Deep generative models for single-cell and spatial genomics by Ajita Shree
DESCRIPTION:Speaker: Ms. Ajita Shree is a PhD student in the Department of Computer Science and Engineering at IIT Kanpur and will be joining EMBL-EBI\, UK\, as a postdoctoral researcher. \nAbstract: Recent advances in large-scale genomic assays\, including single-cell and spatial transcriptomics (ST)\, have provided unprecedented insights into the biological mechanisms underlying development\, disease\, and therapeutic response. However\, these datasets pose significant computational challenges. \nOne of the major challenges is the integration of heterogeneous single-cell datasets across donors\, time points\, and experimental conditions to create a unified resource for downstream analysis. In this talk\, I will present scDREAMER\, a novel deep generative model that can perform integration of multi-batch single-cell datasets in unsupervised\, semi-supervised and supervised settings. Using real benchmarking datasets\, we demonstrate that scDREAMER can overcome critical challenges including skewed cell type distribution among batches\, nested batch-effects\, large number of batches and enables integration of millions of cells across species. \nFurther\, I will discuss the emerging field of spatial genomics\, which enables the study of gene expression at a spatial level\, but its spot-level resolution poses challenges in resolving cell-type contributions in situ. This has spurred extensive development of deconvolution methods\, yet evaluation remains lacking. In this work\, we present a novel graph attention auto-encoder for simulating spatial cell type distributions from three major tissue types including brain\, cancer and organs\, and performed a comprehensive benchmarking. \nBio: Ajita Shree is a PhD student in the Department of Computer Science and Engineering at IIT Kanpur and will be joining EMBL-EBI\, UK\, as a postdoctoral researcher. Previously\, she worked for three years as a Data Scientist at GE Aerospace and GE Global Research\, and was a graduate of GE’s Global Leadership Program. She earned her M.Tech. in Computer Science and Engineering from IIT Delhi in 2017 and holds a B.Tech. in Computer Science and Engineering.
URL:https://homecse.iitd.ac.in/event/deep-generative-models-for-single-cell-and-spatial-genomics-by-ajita-shree/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20260122T120000
DTEND;TZID=Asia/Kolkata:20260122T130000
DTSTAMP:20260921T152941
CREATED:20260116T114035Z
LAST-MODIFIED:20260116T144924Z
UID:2385-1769083200-1769086800@homecse.iitd.ac.in
SUMMARY:Logical Relations for Formally Verified Authenticated Data Structures by Chaitanya Agarwal
DESCRIPTION:Venue: Bharti501 \nAbstract: Authenticated data structures (ADSs) allow untrusted third parties to carry out operations which produce proofs that can be used to verify an operation’s output. Such data structures are challenging to develop and implement correctly. In this talk\, I will talk about a library\, Authentikit\, that is implemented in OCaml\, that generates authenticated versions of data structures automatically. I will also talk about recent work by us (https://dl.acm.org/doi/abs/10.1145/3719027.3744801) that gives a formal proof of security and correctness of Authentikit. The proof is based on a new relational separation logic for reasoning about programs that use collision-resistant cryptographic hash functions. This logic provides a basis for constructing two semantic models of a type system\, which are used to justify how Authentikit makes use of type abstraction to enforce security and correctness. Using these models we also prove the correctness of several optimizations to Authentikit and then show how optimized\, hand-written implementations of authenticated data structures can be soundly linked with automatically generated code. All of the results have been mechanized in the Rocq prover using the Iris framework. \nSpeaker Bio: Chaitanya Agarwal (https://culechetoo.github.io <https://culechetoo.github.io/>) is a 3rd year computer science PhD student at the New York University\, advised by Joseph Tassarotti. He is broadly interested in programming languages and formal verification with a particular focus on verification of security applications. In the past\, he has also worked with Thomas Wies on abstract-interpretation analysis for recursive\, higher-order programs\, and with Shibashis Guha\, on developing statistical-model-checking techniques for Markov Decision Processes (MDPs). Chaitanya obtained his B.Tech. from IIIT Delhi.
URL:https://homecse.iitd.ac.in/event/logical-relations-for-formally-verified-authenticated-data-structures-by-chaitanya-agarwal/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20251215T120000
DTEND;TZID=Asia/Kolkata:20251215T130000
DTSTAMP:20260921T152941
CREATED:20251209T045950Z
LAST-MODIFIED:20251209T045950Z
UID:2235-1765800000-1765803600@homecse.iitd.ac.in
SUMMARY:Matroids are Equitable by Hannaneh Akrami
DESCRIPTION:Abstract: We show that if the ground set of a matroid can be partitioned into k≥2 bases\, then for any given subset S of the ground set\, there is a partition into k bases such that the sizes of the intersections of the bases with S may differ by at most one. This settles the matroid equitability conjecture by Fekete and Szabó (Electron.~J.~Comb.~2011) in the affirmative. We also investigate equitable splittings of two disjoint sets S1 and S2\, and show that there is a partition into k bases such that the sizes of the intersections with S1 may differ by at most one and the sizes of the intersections with S2 may differ by at most two; this is the best possible one can hope for arbitrary matroids. \nWe also derive applications of this result into matroid constrained fair division problems. We show that there exists a matroid-constrained fair division that is envy-free up to 1 item if the valuations are identical and tri-valued additive. We also show that for bi-valued additive valuations\, there exists a matroid-constrained allocation that provides everyone their maximin share. \nThis is based on joint work with Siyue Liu\, Roshan Raj\, and László A. Végh. \nSpeaker Bio: Hannaneh Akrami is a postdoctoral fellow at the University of Bonn and a Minerva Fast-track fellow at MPI-Informatik. She obtained her PhD from the University of Saarlandes and MPI-Informatik in 2024 and completed a BSc from Sharif University of Technology in 2019. Her interests are in fair division\, Algorithmic Game theory\, Combinatorics\, Graph theory and Approximation algorithms. \n 
URL:https://homecse.iitd.ac.in/event/matroids-are-equitable-by-hannaneh-akrami/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20251211T110000
DTEND;TZID=Asia/Kolkata:20251211T170000
DTSTAMP:20260921T152941
CREATED:20251209T113155Z
LAST-MODIFIED:20251209T113155Z
UID:2239-1765450800-1765472400@homecse.iitd.ac.in
SUMMARY:Multiparty Session Types: Separation and Encodability Results by Prof. Nobuko Yoshida
DESCRIPTION:Venue: Bharti501 / Teams link will also be shared \nAbstract: Multiparty session types (MPST) are a type discipline for enforcing the structured\, deadlock-free communication of concurrent and message-passing programs. Traditional MPST have a limited form of choice in which alternative communication possibilities are offered by a single participant and selected by another. Mixed choice multiparty session types (MCMP) extend the choice construct to include both selections and offers in the same choice. This talk presents a mixed-choice synchronous multiparty session calculus and its typing system\, which guarantees communication safety and deadlock-freedom. We then talk of expressiveness of nine subcalculi of the MCMP-calculus by examining their encodability (there exists a good encoding from one to another) and separation (there exists no good encoding from one calculus to another). The highlight is that the binary (2-party) mixed sessions by Casal et al. (2022) are strictly less expressive than the MCMP-calculus. \n\nJoint work with Kirstin Peters appeared in LICS’24 (https://arxiv.org/abs/2405.08104) \nAbout the speaker. Nobuko Yoshida is Christopher Strachey Chair of Computer Science in University of Oxford. She is an EPSRC Established Career Fellow and an Honorary Fellow at Glasgow University. Last 10 years\, her main research interests are theories and applications of protocol specification and verification. She introduced multiparty session types [ POPL’08\, JACM ] which received the Most Influential POPL Paper Award in 2018 (judged by its influence over the last decade). This work enlarged the community and widened the scope of applications of session types\, e.g. runtime monitoring based on Scribble (co-developed with Red Hat) has been deployed to other projects such as cyberinfrastructure in the US Ocean Observatories Initiative (OOI); and widened the scope of her research areas. She received the Test-of-time-award from PPDP’24 and the best paper awards from CC’20\, COORDINATION’23 and DisCoTech’23. She received the third Suffrage Science Award for Mathematics and Computing from MRC for her STEM activity. She is an editor of ACM Transactions on Programming Languages and Systems\, Theoretical Computer Science\,  ACM Formal Aspects of Computing\, Mathematical Structures in Computer Science\, Journal of Logical Algebraic Methods in Programming\, and the chief editor of The Computer-aided Verification and Concurrency Column for EATCS Bulletin.
URL:https://homecse.iitd.ac.in/event/multiparty-session-types-separation-and-encodability-results-by-prof-nobuko-yoshida/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20251209T140000
DTEND;TZID=Asia/Kolkata:20251209T150000
DTSTAMP:20260921T152941
CREATED:20251208T052758Z
LAST-MODIFIED:20251208T052758Z
UID:2233-1765288800-1765292400@homecse.iitd.ac.in
SUMMARY:Approximating Optimal Broadcast of Files in a Hose-Model Network
DESCRIPTION:Speaker:Sukriti Gupta (PhD student)\, CSE Dept.\, IIT Delhi\nAbstract -\nWe consider the problem of file sharing among peers who are connected to \na common core network through links of differing upload and download \ncapacities\, as is the case in networks provisioned according to the hose \nmodel. The file is assumed to be divided into equal-sized chunks\, and a \npeer can start sending a “chunk” of the file to another peer only after \nit has received the entire chunk. The objective is to share a chunk\, \ninitially residing on one of the peers\, with all other peers in the \nleast time possible. Peers can simultaneously send/receive parts of a \nchunk to/from multiple peers\, subject to the upload and download \ncapacity constraints.
URL:https://homecse.iitd.ac.in/event/approximating-optimal-broadcast-of-files-in-a-hose-model-network/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20251030T110000
DTEND;TZID=Asia/Kolkata:20251030T120000
DTSTAMP:20260921T152941
CREATED:20251028T055031Z
LAST-MODIFIED:20251028T055031Z
UID:2136-1761822000-1761825600@homecse.iitd.ac.in
SUMMARY:Towards Reliable LLM Reasoning: Coordinated Agents\, Variance-Aware Evaluation\, and Lean Inference by Prof. Akhil Arora
DESCRIPTION:Abstract: Large language models (LLMs) are increasingly deployed as reasoning engines\, yet their practical use remains constrained by three persistent challenges: achieving high-quality reasoning at low cost\, measuring performance reliably\, and ensuring efficient\, reproducible deployment. In this talk\, I will present a research agenda addressing these challenges through new methods\, benchmarks\, and systems for practical LLM reasoning. I begin with Next\, I turn to Finally\, I focus on Together\, these contributions chart a path toward LLM reasoning that is not only more powerful\, but also leaner\, more reliable\, and environmentally responsible.\n\n  \n\nBio: Akhil Arora is a Tenure-Track Assistant Professor of Computer Science at Aarhus University\, where he heads the CLAN for AI Research on Language and Networks (or “CLAN” for short). He is a fellow of the Copenhagen Center for Social Data Science (SODAS)\, an affiliate of the Pioneer Centre for AI and ELLIS\, and a formal collaborator of the Wikimedia Foundation\, the non-profit organization that manages Wikipedia and related projects. Akhil’s research lies broadly in human-centered AI with a focus on improving human knowledge-seeking\, bridging knowledge gaps\, and promoting knowledge equity on the Web. To this end\, he devises methods and tools blending techniques from NLP\, AI\, Graph ML\, and Computational social science. Recently\, his group has been devising robust\, trustworthy\, accessible\, and efficient LLM inference strategies.\nAkhil received his PhD in Computer Science from EPFL (2024) in Switzerland\, his MS from IIT Kanpur (2013)\, and his undergraduate degree from NCU Gurgaon (2010). In days of yore\, he spent close to five years in the industry working with the research labs of Xerox and American Express as a Research Scientist. His work on influence maximization has been recognized as the 8th most influential paper of SIGMOD 2017 by Paper Digest and received the 2018 ACM SIGMOD Most Reproducible Paper Award. He is a recipient of the prestigious EDIC Doctoral Fellowship\, an alumnus of the coveted Heidelberg Laureate Forum\, and a DAAD AINet fellow on human-centered AI. Akhil is a director of the P1-programs on
URL:https://homecse.iitd.ac.in/event/towards-reliable-llm-reasoning-coordinated-agents-variance-aware-evaluation-and-lean-inference-by-prof-akhil-arora/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250901T120000
DTEND;TZID=Asia/Kolkata:20250901T130000
DTSTAMP:20260921T152941
CREATED:20250806T062326Z
LAST-MODIFIED:20250809T094539Z
UID:1766-1756728000-1756731600@homecse.iitd.ac.in
SUMMARY:Giving Some Space Can Be Hard: Two New Models to Match Agents with Locations by Shivika Narang
DESCRIPTION:Abstract: There can be a multitude of reasons to match agents to specific locations in a given space. In this talk we cover two: distributing delivery orders and assigning shared hostel rooms. For both settings we shall try to find solutions that satisfy desirable properties and characterize instances for which they exist.\n \nWe first initiate the study of fair distribution of delivery tasks among a set of agents wherein delivery jobs are placed along the vertices of a graph. Our goal is to fairly distribute delivery costs (modeled as a submodular function) among a fixed set of agents while satisfying some desirable notions of economic efficiency. We characterize instances that admit fair and efficient solutions by exploiting underlying graph structures. Unfortunately\, finding these solutions proves to be NP-hard. We complement this by designing an XP algorithm (parameterized by the number of agents) that can find all fair and efficient solutions when they exist. We conclude this discussion by theoretically and experimentally analyzing the price of fairness.\n \nWe shall then introduce Leontief utilities to the problem of roommate matchings. We aim to find strategyproof mechanisms that give good bounds on agent welfare. We first find that no approximation to welfare can be achieved under strategyproof mechanisms for either Leontief or additive utilities. Even for binary additive utilities no maximum welfare mechanism can be strategyproof. In contrast\, we then –surprisingly– find that binary Leontief utilities enable us to find strategyproof mechanisms that maximize welfare.\n \nJoint work with Hadi Hosseini\, Sanjukta Roy and Tomasz Was.\n \nBio: Shivika Narang is a postdoctoral fellow at UNSW Sydney. Previously she was a postdoc at Simons Laufer Mathematical Sciences Institute\, Berkeley (SLMath) and completed her PhD from IISc Bengaluru. During her PhD\, she received the Tata Consultancy Services Research Fellowship. Her work is currently focused on finding fair and efficient solutions to societal problems. She largely works in computational social choice\, especially matching and allocation problems.
URL:https://homecse.iitd.ac.in/event/giving-some-space-can-be-hard-two-new-models-to-match-agents-with-locations-by-dr-shivika-narang/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250822T140000
DTEND;TZID=Asia/Kolkata:20250822T150000
DTSTAMP:20260921T152941
CREATED:20250827T082004Z
LAST-MODIFIED:20250827T082004Z
UID:1825-1755871200-1755874800@homecse.iitd.ac.in
SUMMARY:Optimal Capacity Modification for Stable Matchings with Ties by Dr. Keshav Ranjan
DESCRIPTION:Abstract: In this talk\, we consider the Hospitals/Residents (HR) problem in the presence of ties in preference lists of hospitals. Among the three notions of stability\, viz. weak\, strong\, and super stability\, we focus on strong stability. Strong stability is appealing both theoretically and practically; however\, its existence is not guaranteed. Our objective is to optimally increase hospitals’ quotas so that the resulting instance admits a strongly stable matching.\nSuch an augmentation is guaranteed to exist when resident preference lists are strict. We explore two natural optimization criteria:\n\n\n\nMINSUM: minimizing the total capacity increase across all hospitals and \nMINMAX: minimizing the maximum capacity increase for any hospital\n\nWe prove that the MINSUM problem admits a polynomial-time algorithm\, whereas the MINMAX problem is NP-hard. We prove an analogue of the Rural Hospitals theorem for the MINSUM problem. When each hospital incurs a cost for a unit increase in its quota\, the MINSUM problem becomes NP-hard\, even for 0/1 costs. In fact\, we show that the problem cannot be approximated to any multiplicative factor. We also present a polynomial-time algorithm for optimal MINSUM augmentation when a specified subset of edges is required to be included in the matching.\n\nThe talk is based on a recent work accepted at IJCAI 2025 and is a joint work with Meghana Nasre (IIT-M) and Prajakta Nimbhorkar (CMI). \nBio: Keshav Ranjan recently (July 2025) completed his Ph.D. from the Department of Computer Science and Engineering\, IIT Madras\, under the supervision of Dr. Meghana Nasre. His Doctoral thesis\, titled “Two-Sided Matchings: Lower Quotas\, Ties\, and Capacity Augmentation”\, focuses on the algorithmic aspects of two-sided matching problems under various constraints. Previously\, he held an M. Tech degree in Mathematics and Computing from the Department of Mathematics\, IIT Patna. His research interests lie in the broad area of Graph Algorithms\, with a particular focus on matching problems with preferences.
URL:https://homecse.iitd.ac.in/event/optimal-capacity-modification-for-stable-matchings-with-ties-by-dr-keshav-ranjan/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250806T120000
DTEND;TZID=Asia/Kolkata:20250806T130000
DTSTAMP:20260921T152941
CREATED:20250730T061826Z
LAST-MODIFIED:20250730T165814Z
UID:1727-1754481600-1754485200@homecse.iitd.ac.in
SUMMARY:Rank Aggregation and Fairness by Diptarka Chakraborty
DESCRIPTION:Abstract: Aggregating multiple input rankings over a set of candidates to generate a consensus ranking is one of the fundamental ranking problems\, having many applications in social choice theory\, hiring\, college admission\, web search\, and databases. However\, the optimal consensus ranking might be biased against any individual candidate or candidates belonging to certain marginalized communities or groups. This has motivated studies of the rank aggregation problem from the fairness perspective. While finding a consensus ranking\, the additional objective is to ensure fair representation of each group in the top positions of the final aggregated ranking. In this talk\, we will discuss various algorithms to find such a fair ranking approximately.\n\nSpeaker: Diptarka Chakraborty is an Assistant Professor at the National University of Singapore. He did his Ph.D. at the Indian Institute of Technology\, Kanpur. Before joining NUS\, he spent two years at Charles University\, Prague\, and then almost a year at Weizmann Institute of Science\, Israel\, as a post-doctoral fellow. His research interest mostly lies in theoretical computer science\, more specifically\, algorithms on large data sets\, approximation algorithms\, sublinear algorithms\, string matching algorithms\, and graph algorithms. He is a recipient of the best paper award at FOCS 2018 and the Google South & Southeast Asia Research Award 2022.
URL:https://homecse.iitd.ac.in/event/rank-aggregation-and-fairness/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250609T120000
DTEND;TZID=Asia/Kolkata:20250609T130000
DTSTAMP:20260921T152941
CREATED:20250604T065636Z
LAST-MODIFIED:20250604T065657Z
UID:1639-1749470400-1749474000@homecse.iitd.ac.in
SUMMARY:Designing advanced cryptographic primitives in distributed settings
DESCRIPTION:Speaker: Dr. Anshu Yadav\, Postdoctoral Researcher\, Institute of Science and Technology\, Austria \nAbstract: In today’s world\, the rapid advancement of technology has led to the generation of vast amounts of sensitive data\, which must be accessed in a secure and controlled manner to facilitate research across various domains. Often this data\, associated with a single logical entity\, is generated in a distributed manner\, yet must be protected with the same level of security as if it were produced by a single source. Furthermore\, distributing authority among multiple entities is essential to avoid a single point of security failure. These are natural\, yet complex challenges in modern cryptography. My research focuses on exploring how advanced cryptographic primitives can provide effective solutions to such problems. In this talk\, I will begin with a brief overview of my research interests and profile. I will then focus on the themes discussed above. In particular\, I will briefly talk about a result on multi-input attribute based encryption which is a generalization of attribute-based encryption (ABE) – a novel encryption paradigm enabling expressive access control on encrypted data. In ABE\, a message m is encrypted under an attribute x\, and decryption keys are associated with a policy 𝑓. Decryption is possible if and only if 𝑓(x)=1\, unlike traditional public key encryption scheme where a single key can decrypt all ciphertexts. In the multi-input setting\, data is generated by k non-interacting parties\, with each party contributing an input (x_i\, m_i)\, so that x=(x_1\,…\,x_k) and m=(m_1\,…\,m_k). The function 𝑓 is now a k-ary predicate. The goal is for each party to independently encrypt their data as ct_1\,…\,ct_k\, and for a decryption algorithm with key sk_f to recover (m_1\,…\,m_k) if and only if 𝑓(x_1\,…\,x_k)=1. We formally defined the notion of multi-input ABE (k-ABE) and presented constructions for different k under different cryptographic hardness assumptions. I will describe the key challenges in designing cryptographic schemes in the multi-input setting and how our work addresses these challenges. If time permits\, I will also briefly talk about my work in threshold cryptography – a very useful and active field of cryptography with advanced practical applications in distributed environments (e.g.\, block chains\, distributed key generation\, etc.). In threshold cryptography\, a privileged operations—such as ‘signing’ in digital signature scheme or ‘decryption’ in an encryption scheme—is distributed among n parties\, ensuring that at least a threshold t of them are required to perform the operation. In this area\, my research has mostly focussed on threshold signatures\, where we improve the security of post-quantum threshold signature scheme. Finally\, I will conclude the talk with a discussion of my future research directions\, including open problems in the areas discussed above.
URL:https://homecse.iitd.ac.in/event/designing-advanced-cryptographic-primitives-in-distributed-settings/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250605T100000
DTEND;TZID=Asia/Kolkata:20250605T110000
DTSTAMP:20260921T152941
CREATED:20250602T072215Z
LAST-MODIFIED:20250602T094001Z
UID:1633-1749117600-1749121200@homecse.iitd.ac.in
SUMMARY:Multimodal Learning in 3D environments: Perception\, and Simulation
DESCRIPTION:Speaker: Dr. Arun Balajee Vasudevan is currently a Research Scientist at Amazon \nAbstract: \nAutonomous robots have several potential applications such as virtual assistants\, VR/AR\, gaming\, self-driving technologies\, city planning and others. To achieve autonomy\, a robot needs to see and hear the environment\, before it can converse or navigate favorably to perform a human-desired task. Precisely\, scene understanding begins with building 3D geometry\, decoding semantics\, understanding surround objects/humans\, and planning and actions. My research talk addresses these fundamental challenges independently under two broad themes: understanding geometry and multimodal perception & data-driven simulation and navigation. \nUnder geometry and perception\, I introduce the usage of several multimodalities such as the user’s gaze\, visual sensors such as cameras or range sensors (e.g. Kinect)\, and speech/language instructions from human referrals for robot perception tasks. Further\, I delve deep into the investigation of the audio sensing modality for the task using binaural sound microphones. Secondly\, regarding the geometry\, my talk addresses one of my ongoing works about the construction of digital twins of the real world with 4D reconstruction of dynamic scenes from ground visuals of a robot. \nUnder the theme of Data-driven simulation and robot navigation. Following perception\, robots must navigate and take meaningful actions in the world. This involves broadly two aspects: wayfinding and motion planning. Earlier works address wayfinding based on directional instructions\, overlooking human aspects. I briefly talk about a new paradigm that integrates principles from cognitive science with learning-based methods to tackle the challenge of language-based wayfinding for robots in real-world outdoor environments. The second aspect is motion planning for which I propose the learning of driver behavior models for MPC-based planners to build data-driven simulators. \nLong term\, I envision to bridge the above two themes to build multimodal digital twins simulators of the real-world. This potentially helps in training and testing of planners\, VR/AR setups\, gaming\, and others. Lastly\, I also cover my future research plan in the talk. \nShort Bio: \nArun Balajee Vasudevan is currently a Research Scientist at Amazon. Previously\, he was a postdoctoral researcher at Carnegie Mellon University under Prof. Deva Ramanan till March 2025. His core research interest is in Computer Vision and Multimodal Learning. He has works in multimodal (vision\, language and sounds) perception and navigation\, 3D/4D reconstruction\, Motion Planning and improving Foundational models. He published papers predominantly in vision and machine learning conferences/journals such as CVPR\, ECCV\, ICML\, IJCV\, TPAMI\, and others. He defended his PhD under Prof. Luc Van Gool at ETH Zurich. He received his MSc in Computer Science from EPFL in 2016 and an undergraduate degree in Electrical Engineering from the Indian Institute of Technology Jodhpur in the year 2014.
URL:https://homecse.iitd.ac.in/event/multimodal-learning-in-3d-environments-perception-and-simulation/
LOCATION:Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250529T120000
DTEND;TZID=Asia/Kolkata:20250529T130000
DTSTAMP:20260921T152941
CREATED:20250526T171008Z
LAST-MODIFIED:20250526T171008Z
UID:1628-1748520000-1748523600@homecse.iitd.ac.in
SUMMARY:Giving Some Space Can Be Hard: Two New Models to Match Agents with Locations by Shivika Narang
DESCRIPTION:Title: Giving Some Space Can Be Hard: Two New Models to Match Agents with Locations \nSpeaker: Shivika Narang (UNSW Sydney)\n\nAbstract: There can be a multitude of reasons to match agents to specific locations in a given space. In this talk\, we cover two: distributing delivery orders and assigning office spaces. For both settings\, we shall try to find solutions that satisfy desirable properties and characterize instances for which they exist.\n\nWe first initiate the study of fair distribution of delivery tasks among a set of agents\, wherein delivery jobs are placed along the vertices of a graph. Our goal is to fairly distribute delivery costs (modeled as a submodular function) among a fixed set of agents while satisfying some desirable notions of economic efficiency. We characterize instances that admit fair and efficient solutions by exploiting underlying graph structures. Unfortunately\, finding these solutions proves to be NP-hard. We complement this by designing an XP algorithm (parameterized by the number of agents) that can find all fair and efficient solutions when they exist. We conclude this discussion by theoretically and experimentally analyzing the price of fairness.\n\nWe shall then introduce and analyze distance preservation games (DPGs). In DPGs\, agents express ideal distances to other agents and need to choose locations in the unit interval while preserving their ideal distances as closely as possible. We analyze the existence and computation of location profiles that are jump stable (i.e.\, no agent can benefit by moving to another location) or welfare optimal for DPGs\, respectively.\n\nJoint Work with Hadi Hosseini and Tomasz Wąs (Fair Delivery) and Haris Aziz\, Hau Chan\, Patrick Lederer\, and Toby Walsh (DPGs).\n\nSpeaker Bio: Shivika Narang is a postdoctoral fellow at UNSW Sydney. Previously\, she was a postdoc at Simons Laufer Mathematical Sciences Institute\, Berkeley (SLMath)\, and completed her PhD from IISc Bengaluru. Her work is currently focused on fairness and efficiency in computational social choice\, especially matching and allocation problems.
URL:https://homecse.iitd.ac.in/event/giving-some-space-can-be-hard-two-new-models-to-match-agents-with-locations-by-shivika-narang/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250528T120000
DTEND;TZID=Asia/Kolkata:20250528T130000
DTSTAMP:20260921T152941
CREATED:20250518T062803Z
LAST-MODIFIED:20250526T171039Z
UID:1592-1748433600-1748437200@homecse.iitd.ac.in
SUMMARY:Enhancing Safety and Ethical Alignment in Large Language Models by Rima Hazra
DESCRIPTION:Speaker:  Dr. Rima Hazra \n\n\nAbstract: In this talk\, we explore cutting-edge strategies for enhancing the safety and ethical alignment of large language models (LLMs). The research spans various approaches\, including red teaming and jailbreaking techniques\, which assess and improve model robustness and ethical integrity. We delve into how instruction-centric responses\, when generated by LLMs\, can increase the likelihood of unethical output\, thereby highlighting the vulnerabilities of these AI systems. Through the introduction of frameworks like ‘Safety Arithmetic’ and ‘SafeInfer\,’ we demonstrate methods to mitigate risks by manipulating model parameters and decoding-time behaviors to foster safer interactions. The discussions also emphasize the importance of safety alignment strategies and the challenges posed by integrating new knowledge through model edits\, which can paradoxically destabilize ethical guidelines. This comprehensive examination not only sheds light on the current vulnerabilities of LLMs but also presents a pathway toward more reliable and ethically aligned AI implementations. \n\nBio: Dr. Rima Hazra is a senior postdoc at Eindhoven University of Technology (TU\e)\, Netherlands. Earlier she was a Postdoctoral Researcher at the Singapore University of Technology and Design\, working in the area of AI safety alignment\, natural language processing\, and LLM reasoning. She earned her Ph.D. from the Indian Institute of Technology\, Kharagpur\, where she explored the area of Information retrieval\, NLP and graph learning. With experience in information retrieval\, NLP and graph learning\, Dr. Hazra has published several papers in prestigious CORE A* and A conferences such as AAAI\, ACL\, EMNLP\, NAACL\, ECIR\, ECMLP PKDD and JCDL. She has also received the prestigious Microsoft Academic Partnership Grant (MAPG) and the PaliGemma Academic Program award from Google for her work in AI safety alignment.
URL:https://homecse.iitd.ac.in/event/enhancing-safety-and-ethical-alignment-in-large-language-models-by-dr-rima-hazra/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250523T120000
DTEND;TZID=Asia/Kolkata:20250523T130000
DTSTAMP:20260921T152941
CREATED:20250519T054519Z
LAST-MODIFIED:20250520T083950Z
UID:1599-1748001600-1748005200@homecse.iitd.ac.in
SUMMARY:Next-Generation AI-Enhanced Stream Processing
DESCRIPTION:Speaker: Dr. Manisha Luthra Agnihotri is the Deputy Head of the German Research Center for Artificial Intelligence (DFKI) in Darmstadt. \nIt is an online talk. Please write to the CSE office to get the Teams link. \nAbstract: In this talk\, I will outline my vision for next-generation\, AI-enhanced data management systems through the lens of learned stream processing. Today’s stream processing platforms demand extensive manual tuning to optimize critical decisions such as query plan selection\, operator placement\, and parallelism. My vision eliminates these labor-intensive processes by leveraging zero-shot learning to automatically derive optimal configurations\, thereby radically enhancing performance and generalisability. A key contribution of my work is a novel learned operator placement optimization provided by a novel cost model that forecasts the execution costs of streaming queries on heterogeneous hardware. Particularly in IoT environments—where diverse hardware and network conditions are the norm—our approach employs graph neural networks to predict query costs accurately\, even for unseen placements and query patterns. This approach not only overcomes the generalizability limitations of existing methods but also paves the way for more robust and adaptive cost-based optimizations for stream processing systems. I will also discuss my future research directions\, focusing on extending these AI-driven techniques to multi-modal stream processing. This work aims to redefine data management by creating systems that adapt to evolving computational needs for multiple modalities\, ultimately setting new standards for understanding data inputs and autonomy in stream processing. \nBio: Manisha Luthra Agnihotri is the Deputy Head of the German Research Center for Artificial Intelligence (DFKI) in Darmstadt and a Research Group Leader at TU Darmstadt. She co-leads the Systems AI for Decision Support group with focus of research on learned system optimizations and multimodal data management. Her work sits at the dynamic intersection of machine learning\, data systems\, and hardware\, with major contributions in learned cost-based optimization and the acceleration of query workloads via GPU and RDMA technologies. \nThroughout her academic journey\, Manisha has received several prestigious awards\, including the German national Best Ph.D. Thesis award from the GI/ITG special interest group on Communication and Distributed Systems (KuVS)\, the Athena Young Investigator Award\, the Anita Borg Faculty Scholarship\, the Zeiss Top Dissertation Scholarship\, and mentoring and networking accolades from the German Research Foundation (DFG). Her expertise has led her to speak at top-tier institutions such as the University of Toronto\, and she has presented her innovative research at premier conferences like SIGMOD\, VLDB\, ICDE\, and EDBT. Manisha also actively contributes to the academic community as a program committee member for major data management conferences\, including VLDB\, SIGMOD\, and EuroSys.
URL:https://homecse.iitd.ac.in/event/next-generation-ai-enhanced-stream-processing/
LOCATION:Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250514T100000
DTEND;TZID=Asia/Kolkata:20250514T110000
DTSTAMP:20260921T152941
CREATED:20250512T144512Z
LAST-MODIFIED:20250512T144600Z
UID:1589-1747216800-1747220400@homecse.iitd.ac.in
SUMMARY:Synthesis and Arithmetic of Quantum Circuits
DESCRIPTION:Speaker: Amolak Kalra (https://sites.google.com/view/amolakratankalra/home) \nAbstract: Efficient decomposition of a unitary operator U using words from a universal gate set G is a fundamental problem in quantum computing. The process by which this is achieved is called circuit synthesis. This problem arises naturally in the context of quantum circuit\ncompilation. In this talk\, I will introduce this problem and explain how one can use tools from number theory to solve it. I will then explain some recent results that build on this connection.
URL:https://homecse.iitd.ac.in/event/synthesis-and-arithmetic-of-quantum-circuits/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250508T140000
DTEND;TZID=Asia/Kolkata:20250508T150000
DTSTAMP:20260921T152941
CREATED:20250507T062717Z
LAST-MODIFIED:20250507T063432Z
UID:1581-1746712800-1746716400@homecse.iitd.ac.in
SUMMARY:Trading Prophets: How to trade multiple stocks optimally
DESCRIPTION:Speaker: Surbhi Rajput\, MSR Student\, CSE Dept.\, IIT Delhi \nAbstract:\n\nIn the (single stock) \emph{trading prophet} problem formulated by Correa et\nal.\ [2023]\, an online algorithm observes a sequence of prices of a stock.\nAt each step\, the algorithm can either buy the stock by paying the current\nprice if it doesn't already hold the stock\, or it can sell the currently\nheld stock and collect the current price as a reward. The goal of the\nalgorithm is to maximize its overall profit. Correa et al.\ showed that the\noptimal competitive ratio for this problem is $\nicefrac{1}{2}$ when the\nstock prices are identically and independently distributed.\nIn this talk\, I will discuss the simplifications and generalizations of\nCorrea et al.'s analysis\, which led us to generalize the model by allowing\nthe algorithm to trade multiple stocks. First\, we generalize the model to\n$(k\,\ell\, \ell')$-\textsc{Trading Prophet Problem}\, wherein there are $k$\nstocks in the market\, and the online algorithm can hold up to $\ell$ stocks\nat any time\, where $\ell \leq k$. The online algorithm competes against an\noffline algorithm that can hold at most $\ell' \leq \ell$ stocks at any\ntime. Under the assumption that prices of different stocks are independent\,\nwe show that\, for any $\ell$\, $\ell'$\, and $k$\, the optimal competitive\nratio of $(k\,\ell\, \ell')$-\textsc{Trading Prophet Problem} is\n$\min\left\{\frac{1}{2}\,\frac{\ell}{k}\right\}$.\nWe further generalize it to $\mathcal{M}$-\textsc{Trading Prophet Problem}\nover a matroid $\mathcal{M}$ on the set of $k$ stocks\, wherein the stock\nprices at any given time are possibly correlated (but are independent across\ntime). The algorithm is allowed to hold only a feasible subset of stocks at\nany time. We prove a tight bound of $\frac{1}{1+d}$ on the competitive ratio\nof the $\mathcal{M}$-\textsc{Trading Prophet Problem}\, where $d$ is the\n\textit{density} of the matroid.\nWe then consider the non-i.i.d.\ random order setting over a matroid\,\nwherein stock prices drawn independently from $n$ potentially different\ndistributions are presented in a uniformly random order. In this setting\, we\nachieve a competitive ratio of at least $\frac{1}{1+d} - \mathcal{O}\n\left(\frac{1}{n} \right)$\, where $d$ is the density of the matroid\,\nmatching the hardness result for i.i.d.\ instances as $n$ approaches\n$\infty$.\nOur analysis of the above problems is based on the following key insights.\nFirst\, any algorithm can be simulated by one that\, on each time step\, sells\n\emph{all} its currently held stocks before buying a suitable subset of\nstocks. Second\, we prove that the general problem reduces to a restriction\nwhere the expected price of every stock is zero.\nThird\, we reduce the problem in the random order non-i.i.d.\ setting to the\ni.i.d. setting by leveraging the fact that the outcome of sampling two\nobjects without replacement from a large set is almost identically\ndistributed as the outcome of sampling with replacement.
URL:https://homecse.iitd.ac.in/event/trading-prophets-how-to-trade-multiple-stocks-optimally/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250506T120000
DTEND;TZID=Asia/Kolkata:20250506T130000
DTSTAMP:20260921T152941
CREATED:20250503T125437Z
LAST-MODIFIED:20250503T125437Z
UID:1572-1746532800-1746536400@homecse.iitd.ac.in
SUMMARY:Power and limitations of quantum computation and quantum cryptography by Dr. Srijita Kundu
DESCRIPTION:Title: Power and limitations of quantum computation and quantum cryptography \nSpeaker: Dr. Srijita Kundu \nAbstract: Quantum computers are approaching practical viability\, and quantum cryptography is already being deployed for secure communication. Understanding the capabilities and limitations of these technologies is crucial for their effective use. \nMy research lies at the intersection of quantum complexity theory and cryptography. I focus on proving what quantum computation can and cannot do in concrete models such as query and communication complexity. In this talk\, I will share results in both directions:\n1. I will talk about direct product theorems for quantum communication complexity\, which are a useful lower bound technique for quantum communication protocols.\n2. I will talk about quantum proofs being more powerful than classical proofs in query complexity.\nAdditionally\, I will talk about quantum protocols for novel cryptographic tasks such as certified deletion and uncloneable encryption\, whose security can be proved using the communication direct product theorems. \nShort Bio: Srijita Kundu completed her PhD at the Centre for Quantum Technologies in the National University of Singapore in 2021\, under the supervision of Prof. Rahul Jain. Since 2022\, she has been a postdoctoral researcher at the Institute for Quantum Computing in the University of Waterloo. She is interested in quantum complexity theory and cryptography.
URL:https://homecse.iitd.ac.in/event/power-and-limitations-of-quantum-computation-and-quantum-cryptography-by-dr-srijita-kundu/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250501T110000
DTEND;TZID=Asia/Kolkata:20250501T120000
DTSTAMP:20260921T152941
CREATED:20250425T023119Z
LAST-MODIFIED:20250427T060150Z
UID:1521-1746097200-1746100800@homecse.iitd.ac.in
SUMMARY:Certifying Large Language Models with LLMCert
DESCRIPTION:Speaker: Isha Chaudhary \nAbstract: Large Language Models (LLMs) are increasingly deployed in critical systems\, e.g.\, healthcare and finance and can produce incorrect and biased responses. These can cause huge social and economic losses to the deploying agencies and their clients. Conventional studies are\, however\, insufficient to thoroughly evaluate LLMs\, as they cannot scale to a large number of possible inputs and provide no formal guarantees. Therefore\, we develop and present the first family of LLM certification frameworks\, LLMCert\, consisting of certifiers providing formal probabilistic guarantees for desirable properties such as correct LLM reasoning and fairness on prohibitively large distributions of prompts. Our certificates are quantitative — they consist of provably high-confidence\, tight bounds on the probability of desirable LLM responses for random prompts sampled from a distribution. We design and certify novel specifications for bias and knowledge comprehension in individual certifiers – LLMCert-B (https://certifyllm.com/) and LLMCert-C (https://arxiv.org/abs/2402.15929)\, respectively. We illustrate bias certification for distributions of prompts created by applying varying prefixes drawn from a prefix distribution to a given set of prompts. We consider prefix distributions for random token sequences\, mixtures of manual jailbreaks\, and jailbreaks in the LLM’s embedding space to certify bias. We obtain non-trivial certified bounds on the probability of unbiased responses of SOTA LLMs\, exposing their vulnerabilities over distributions of prompts generated from computationally inexpensive prefix distributions. \nFor knowledge comprehension certification\, we design and use novel distributions of knowledge comprehension prompts with natural noise\, using knowledge graphs. We certify SOTA LLMs over specifications arising in precision medicine and general question-answering. We show previously undiscovered vulnerabilities of SOTA LLMs owing to natural noise in prompts. We also establish the first performance hierarchies with formal guarantees among SOTA LLMs\, pertaining to question-answering in precision medicine. \n  \nBio: Isha Chaudhary is a third-year Ph.D. candidate at the Siebel School of Computing and Data Science\, University of Illinois Urbana-Champaign\, advised by Prof. Gagandeep Singh. Her research interest is broadly in trustworthy foundation models and neural networks for computer systems. She graduated from a B.Tech. in Electrical Engineering from IIT Delhi in 2022. For details about her work\, please check out: https://ishachaudhary.web.illinois.edu/.
URL:https://homecse.iitd.ac.in/event/certifying-large-language-models-with-llmcert/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250429T150000
DTEND;TZID=Asia/Kolkata:20250429T160000
DTSTAMP:20260921T152941
CREATED:20250425T023346Z
LAST-MODIFIED:20250427T060123Z
UID:1523-1745938800-1745942400@homecse.iitd.ac.in
SUMMARY:Computation-In-Memory based Edge-AI for Healthcare: A Cross-Layer Approach
DESCRIPTION:Speaker: Sumit Diware \nAbstract: Recent advancements in artificial intelligence (AI) have driven the emergence of real-world cognitive products and services\, which rely on neural networks to perform complex tasks. Edge computing for AI (edge-AI) combines data sources with local hardware that executes neural network computations\, to improve the response latency\, data privacy/security\, and service reliability. Computation-in-memory (CIM) offers an energy-efficient and compact alternative to conventional neural network hardware for edge-AI\, by enabling in-situ data processing with emerging memory technologies called memristors. Healthcare stands out as a key domain for CIM\, due to its critical impact on society and the need for energy-efficient\, compact hardware in healthcare edge applications. However\, developing AI models for healthcare that are effective\, accurate\, and can fully reap CIM benefits remains a significant challenge. Moreover\, memristors exhibit non-idealities that lead to errors during hardware execution. In this talk\, I will describe our cross-layer research approach and contributions towards addressing these challenges. We first create effective\, accurate\, and CIM-oriented AI models for two healthcare applications: electrocardiogram (ECG) classification and diabetic retinopathy screening. We then devise mitigation strategies against memristor non-idealities and develop a system-on-chip tapeout as a holistic solution that covers the entire abstraction layer stack from application to fabrication. \nShort Bio: Sumit Diware obtained Ph.D. from the Computer Engineering Group at Delft University of Technology (TU Delft)\, Netherlands\, and M.Tech. in VLSI Design Tools and Technology (VDTT) from IIT Delhi. His research focuses on artificial intelligence (AI) processing architectures\, with expertise in computation-in-memory\, neuromorphic computing\, emerging memory technologies\, hardware-algorithm co-design\, and system-on-chip (SoC) design/tapeout. He has authored/co-authored several publications in leading conferences such as DATE\, DAC\, and ICCAD\, as well as IEEE journals including TBioCAS and TETCI. For his doctoral work\, he recently received the European Design & Automation Association (EDAA) Outstanding Dissertation Award at DATE 2025 conference. Before his Ph.D.\, Sumit was a research assistant at the Karlsruhe Institute of Technology (KIT)\, Germany\, where he worked on multicore SoC architectures. Prior to that\, he worked at Qualcomm India as a part of IIT Delhi’s VDTT program\, focusing on SoC power management architecture.
URL:https://homecse.iitd.ac.in/event/computation-in-memory-based-edge-ai-for-healthcare-a-cross-layer-approach/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250428T120000
DTEND;TZID=Asia/Kolkata:20250428T130000
DTSTAMP:20260921T152941
CREATED:20250425T023615Z
LAST-MODIFIED:20250427T060100Z
UID:1526-1745841600-1745845200@homecse.iitd.ac.in
SUMMARY:Algebra and co-  ..in the theory of programming
DESCRIPTION:Speaker: Prof. Sanjiva Prasad \nThe talk explores a few elementary concepts from abstract algebra that (should) inform our data-centric development of common programs and data types\, but are often elided in most textbook treatments.  Included are sets\, monoids\, boolean algebras\, semirings and Kleene algebras\, structure-preserving maps and homomorphisms\, and notions of co-induction.  The talk is intended to be accessible to a general audience. \nThe talk will begin at 12:00 PM\, with refreshments served at 11:50 AM
URL:https://homecse.iitd.ac.in/event/algebra-and-co-in-the-theory-of-programming/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250425T120000
DTEND;TZID=Asia/Kolkata:20250425T170000
DTSTAMP:20260921T152941
CREATED:20250421T081314Z
LAST-MODIFIED:20250425T112605Z
UID:1492-1745582400-1745600400@homecse.iitd.ac.in
SUMMARY:How many matches does it take to find a champion?
DESCRIPTION:Speaker: Neeldhara Misra\n\nAbstract: Suppose there are n horses and we have a track with k lanes. If we pick k horses to run a race\, a linear ordering is established among the chosen horses\, based only on the finishing order (race time is not considered). How many races do we need to organize to determine the best two horses? How many races are necessary to reveal the full ranking?\n \nTo address this question\, we might assume that there is an overall linear ordering among all horses and that the outcomes of the races are always consistent with this global linear order. However\, this may not be true in real-world tournaments: actual outcomes may deviate from our estimate of the global order. In this talk\, we will discuss some developments around questions of determining the “top k” elements in the general setting of tournaments and the special situation when we are promised that comparisons are consistent with an underlying linear order.\n \nThe results presented are drawn from the following papers:\n \nVariations on the Tournament Problem\nFabrizio Luccio\, Linda Pagli\, Nicola Santoro\nFUN 2024\n \nQuery Complexity of Tournament Solutions\nArnab Maiti\, Palash Dey\nTCS 2024\n \nShort bio: Neeldhara Misra is a Smt. Amba and Sri. V S Sastry Chair Associate Professor of Computer Science and Engineering at the Indian Institute of Technology\, Gandhinagar. She completed her PhD from the Institute for Mathematical Sciences in 2012 in Theoretical Computer Science. Her research interests include the design and analysis of algorithms and computational social choice. She is also interested in visualizations and other methods to communicate computational thinking at an elementary level. She also enjoys learning about new card tricks\, especially self-working ones — even though she can’t remember any!\nhttps://www.neeldhara.com/
URL:https://homecse.iitd.ac.in/event/how-many-matches-does-it-take-to-find-a-champion/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250424T120000
DTEND;TZID=Asia/Kolkata:20250424T170000
DTSTAMP:20260921T152941
CREATED:20250421T130049Z
LAST-MODIFIED:20250421T130049Z
UID:1494-1745496000-1745514000@homecse.iitd.ac.in
SUMMARY:Computing Lindahl Equilibrium for Public Goods with and without Funding Caps
DESCRIPTION:Speaker: Dominik Peters \n\nAbstract: Lindahl equilibrium is a solution concept for allocating a fixed budget across several divisible public goods. It always lies in the core\, meaning that the equilibrium allocation satisfies desirable stability and proportional fairness properties. We consider a model where agents have separable linear utility functions over the public goods\, and the output assigns to each good an amount of spending\, summing to at most the available budget.\n\nIn the uncapped setting\, each of the public goods can absorb any amount of funding. In this case\, it is known that Lindahl equilibrium is equivalent to maximizing Nash social welfare. We introduce a new convex programming formulation for computing this solution and show that it is related to Nash welfare maximization through duality and reformulation. We then show that running mirror descent on our new formulation gives rise to a proportional response dynamics\, which converges rapidly to an equilibrium. Our new formulation has similarities to Shmyrev’s convex program for Fisher market equilibrium.\n \nIn the capped setting\, each public good has an upper bound on the amount of funding it can receive. In this setting\, existence of Lindahl equilibrium was only known via fixed-point arguments. The existence of an efficient algorithm computing one has been a long-standing open question. We prove that our new convex program continues to work when the cap constraints are added\, and its optimal solutions are Lindahl equilibria. Thus\, we establish that Lindahl equilibrium can be efficiently computed in the capped setting.\n \nShort bio: Dominik Peters is a CNRS researcher at Université Paris Dauphine – PSL\, working on computational social choice. After postdocs with Ariel Procaccia (Harvard) and Nisarg Shah (Toronto)\, he is studying topics in voting theory with a focus on proportional representation and participatory budgeting\, as well as fair division problems. With his collaborators\, he has proposed the Method of Equal Shares\, a voting method that is now used by several cities across Europe to allow their citizens to influence how the city government spends its budget.\nhttps://dominik-peters.de/
URL:https://homecse.iitd.ac.in/event/computing-lindahl-equilibrium-for-public-goods-with-and-without-funding-caps/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250422T120000
DTEND;TZID=Asia/Kolkata:20250422T130000
DTSTAMP:20260921T152941
CREATED:20250416T065439Z
LAST-MODIFIED:20250422T032206Z
UID:1490-1745323200-1745326800@homecse.iitd.ac.in
SUMMARY:Mathematics and Programming: The Past\, Present and Future A Personal Perspective
DESCRIPTION:Speaker: Dr. Pritam Choudhury \nAbstract: In his article „Constructive Mathematics and Computer Programming‟\, the renowned logician and type-theorist\, Per Martin-Löf notes\, “If programming is understood not as the writing of instructions for this or that computing machine but as the design of methods of computation that it is the computer‟s duty to execute (a difference that Dijkstra has referred to as the difference between computer science and computing science)\, then it no longer seems possible to distinguish the discipline of programming from constructive mathematics.”\nIndeed\, mathematics (constructive) and programming can be viewed as two sides of the same coin via the celebrated Curry-Howard or Propositions-as-Types Correspondence. This correspondence has been of great value to both mathematics and programming. On one side\, it enabled mechanization of mathematics and consequently\, production of machine-certified proofs of mathematical theorems. On the other side\, it provided a solid mathematical foundation for programming languages and guided their development.\nIn this talk\, I shall first introduce the Curry-Howard Correspondence through examples and then present some of its technical details. We shall start with a key result\, which states that the Simply-Typed λ-calculus\, a foundational functional programming language\, is nothing but intuitionistic/constructive propositional logic. Thereafter\, I shall touch upon multiple other similar correspondences\, all manifestations of the overarching Curry-Howard Correspondence\, and discuss how these correspondences guided the development of programming languages. Then\, I shall present some of my research work on extending the Curry-Howard Correspondence in the area of dependency analysis over the Simply-Typed λ- calculus (https://dl.acm.org/doi/10.1145/3563335). Note that dependency analysis is vital to several applications\, such as\, language-based security\, multi-stage compilation\, code optimization\, etc. Finally\, I shall wind up the talk discussing some of my ongoing and future research projects that leverage the close connection between mathematics and programming for their mutual benefit. \nBio: Pritam Choudhury is a researcher in type systems and programming language design. His research focuses on graded type systems and their applications. In his doctoral dissertation\, he used graded type systems to analyze linearity and dependency in programming languages. Linearity and dependency analyses are particularly useful in memory management\, language-based security\, multi-stage compilation and code optimization. Pritam completed his PhD at University of Pennsylvania in August 2023. After graduating from UPenn\, he taught as a Visiting Assistant Professor of Computer Science at Haverford College for a year. Before joining UPenn\, he worked on formal verification at University of Cambridge. Pritam received his M.Phil. in Advanced Computer Science from University of Cambridge in 2015 and his B.Tech. in Electrical Engineering from IIT Roorkee in 2014.
URL:https://homecse.iitd.ac.in/event/mathematics-and-programming-the-past-present-and-future-a-personal-perspective/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250422T110000
DTEND;TZID=Asia/Kolkata:20250422T120000
DTSTAMP:20260921T152941
CREATED:20250416T031907Z
LAST-MODIFIED:20250416T031907Z
UID:1487-1745319600-1745323200@homecse.iitd.ac.in
SUMMARY:Impact Assessment of Natural Resource Management (NRM) Interventions in India
DESCRIPTION:Speaker: Ramneek Kaur\, post-doctoral fellow\, CSE\, IIT Delhi \nAbstract: With over 70% of India’s rural population dependent on agriculture\, and 82% of farmers being small and marginal\, the availability of water for irrigation is critical to ensuring sustainable rural livelihoods. Government welfare schemes such as the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) play a pivotal role in this context by funding the creation of Natural Resource Management (NRM) assets in rural areas for the conservation and sustainable use of water. In this talk\, I will present methods and insights from our ongoing research on evaluating the impact of NRM structures built under MGNREGA – one of the world’s largest demand-driven employment and asset creation programs. The scheme supports the creation of assets under different NRM categories such as bunds\, check dams and trenches for groundwater recharge\, and farm ponds and wells for protective irrigation. We assess the effectiveness of these interventions at both the site-level and the broader landscape-level\, using satellite imagery and other secondary data sources. In our work on impact assessment of farm ponds\, we evaluate the impact of farm ponds in their surrounding cropping areas\, on the seasonal agricultural productivity and drought resilience across the Agro-ecological Zones (AEZs) of India\, by employing the Difference-in-Differences (DiD) method and the Double ML method. Our findings show that the average impact of farm ponds is shaped by contextual AEZ-level factors such as agricultural suitability\, private borewell investments\, and canal infrastructure. Building on this\, we are currently evaluating the impact of check dams using similar techniques. At the landscape scale\, we are developing a system dynamics based framework to capture the cumulative effects of multiple MGNREGA interventions and water bodies. This approach helps model causal pathways and interdependencies between various subsystems using data-driven models\, allowing for a deeper understanding of how NRM activities influence water security and agricultural sustainability. Our methods hold potential for broader applications\, including assessing the impact of NRM efforts on forest conservation\, carbon and water credits\, and other ecosystem services. \n  \nSpeaker bio: Dr. Ramneek Kaur is a postdoctoral fellow with the ACT4D research group at IIT Delhi\, where she has been working for the past two years on using technology to strengthen resilient rural livelihoods. Her research focuses on the impact evaluation of Natural Resource Management (NRM) interventions\, particularly the construction and maintenance of water structures in rural areas. Her work leverages satellite imagery and computational methods to evaluate the effectiveness of these interventions in enhancing agricultural productivity and drought resilience\, for the broader aim of informing strategies for sustainable agricultural practices. Prior to this\, she completed her Ph.D. from IIIT-Delhi in 2022\, where her research focused on developing navigation and task allocation algorithms to promote sustainability in urban transportation systems. Her broader research interests lie in the use of ICT for social development\, with a focus on leveraging computational methods to drive sustainability and equity in both rural and urban contexts.
URL:https://homecse.iitd.ac.in/event/impact-assessment-of-natural-resource-management-nrm-interventions-in-india/
LOCATION:SIT 113\, Amar Nath and Shashi Khosla School of Information Technology\, Indian Institute of Technology\, Delhi\, Hauz Khas\, New Delhi\, Delhi\, 110016\, India
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250408T160000
DTEND;TZID=Asia/Kolkata:20250408T170000
DTSTAMP:20260921T152941
CREATED:20250402T225401Z
LAST-MODIFIED:20250402T225401Z
UID:1483-1744128000-1744131600@homecse.iitd.ac.in
SUMMARY:How Do We Build Responsible AI? Towards Fair and Participatory AI Designs
DESCRIPTION:Speaker: Vijay Keswani (Duke University)\nhttps://vijaykeswani.github.io/ \nDetails: Apr 8th (Tue) | 4 PM | Online [Teams Link] \nAbstract: As the capabilities of AI have expanded\, reports of societal and personal harms related to its use have surged. Examples range from systemic biases in AI tools used in healthcare and social media to stereotype propagation in AI-based search and summarization models. In this talk\, I will discuss some of my work on methods to audit and mitigate these biases in AI systems. Building unbiased AI tools presents technical challenges (e.g.\, constrained sampling and optimization) and practical challenges (e.g.\, limited group information in real-world settings). Through the use case of search and summarization\, I will highlight the challenges of addressing representational biases in search results and our socio-technical approaches to mitigate them. In addition to fairness\, this talk will emphasize building participatory mechanisms. I will demonstrate how user and stakeholder participation can serve as an effective mechanism to discover and address social harms due to AI and demonstrate its effectiveness in auditing and mitigating biases in image search results. \nBio: Vijay Keswani is a Postdoctoral Associate at Duke University. His research interests center around community-focused AI development and the ethics of data and technology. His work leverages tools from various disciplines to build robust AI models\, combining computational and statistical learning mechanisms with methods from law\, philosophy\, psychology\, and economics. He received his PhD from Yale University in 2023. While at Yale\, he was also a Resident Fellow at the Information Society Project during 2022-2023 and a 2022 Policy Fellow at the Yale Institute for Social and Policy Studies
URL:https://homecse.iitd.ac.in/event/how-do-we-build-responsible-ai-towards-fair-and-participatory-ai-designs/
LOCATION:Delhi
CATEGORIES:Seminars
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250403T110000
DTEND;TZID=Asia/Kolkata:20250403T170000
DTSTAMP:20260921T152941
CREATED:20250320T051935Z
LAST-MODIFIED:20250320T051935Z
UID:1465-1743678000-1743699600@homecse.iitd.ac.in
SUMMARY:Regulations\, International Standardizations and Technologies to Realize "Trusted AI"
DESCRIPTION:Abstract: With the recent rise of AI businesses in all industries around the world\, AI can also be used to make important decisions for society. However\, it is also true that using AI incorrectly or without understanding the characteristics of AI can have a negative impact on society due to concerns about its impact on human rights and social values. There is a need for wisdom and knowledge to properly utilize these new technologies\, and many countries have now developed principles and guidelines for the use of AI.\n\nThis presentation summarizes the current activities of regulations\, ISO International\nStandardization and technologies related to the realization of trusted AI. It will focus on trends and outlines of International Standards related to AI regulations and introduce some technologies for realizing trusted AI. In addition\, this presentation also provides an overview of the activities in international standards organization – ISO/IEC JTC1/SC42\, as well as introducing other important topics of AI standardization activities.\n\nBio: Yuchang Cheng is a senior research manager of AI laboratory at Fujitsu Limited. His Fujitsu responsibilities are leading the standardization activities of AI\, as well as leading the research of AI governance. In addition\, he is a delegate of Japan national body in ISO/IEC JTC 1/SC 42\, as well as the expert of SC 42’s working groups. He is leading the development of the following international standard projects as the project editor:\n\n\nISO/IEC TR 24030 (Artificial Intelligence (AI) – Use cases);\nISO/IEC 5338 (AI system life cycle processes;\nISO/IEC 25589 (Framework for human-machine teaming)
URL:https://homecse.iitd.ac.in/event/regulations-international-standardizations-and-technologies-to-realize-trusted-ai/
LOCATION:SIT 001\, Amar Nath and Shashi Khosla School of Information Technology\, IIT Delhi\, Hauz Khas\, New Delhi 110016\, India\, Delhi\, Delhi\, 110016\, India
CATEGORIES:Seminars
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250328T120000
DTEND;TZID=Asia/Kolkata:20250328T170000
DTSTAMP:20260921T152941
CREATED:20250327T132705Z
LAST-MODIFIED:20250327T132705Z
UID:1468-1743163200-1743181200@homecse.iitd.ac.in
SUMMARY:An amazing structure for representing all Steiner mincuts of a graph
DESCRIPTION:Speaker: Surender Baswana\, IIT Kanpur \n  \nAbstract: \nMincuts are one of the most well-researched topics in algorithms. In recent years\, there has been phenomenal research on algorithms for computing (s\, t)-mincuts and global mincuts. On the other hand\, the data structural and graph theoretical aspects of mincuts have also been well-researched in the last 50 years\, though they are not as widely known despite being very fundamental and seminal. \n\nWe shall begin with a light discussion of the following 2 classical results. (1) There is a directed acyclic graph that stores all (s\,t)-mincuts of a graph. (2) There is a tree-like graph that stores all global mincuts of a graph.  We shall then discuss a structure that stores Steiner mincuts – generalization of (s\,t)-mincuts and global mincuts. This structure\, designed by Dinitz and Vainshtein is amazingly elegant and beautiful. We shall discuss this structure along with new and much simpler proofs of its properties. \n\nNote: Anyone with basic knowledge of algorithms and elementary graph theory should be able to follow most of the talk. \n\nBiography of the Speaker: \nSurender Baswana is the Tapas Misra Memorial Chair Professor at the Department of Computer Science and Engineering at IIT Kanpur. He did BTech\, MTech\, and PhD from IIT Delhi\, and was a postdoctoral researcher at the Max Planck Institute for Computer Science. He has been a faculty member at IIT Kanpur since 2006. His research area is the design and analysis of algorithms.
URL:https://homecse.iitd.ac.in/event/an-amazing-structure-for-representing-all-steiner-mincuts-of-a-graph/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250326T120000
DTEND;TZID=Asia/Kolkata:20250326T130000
DTSTAMP:20260921T152941
CREATED:20250312T025840Z
LAST-MODIFIED:20250312T025840Z
UID:1454-1742990400-1742994000@homecse.iitd.ac.in
SUMMARY:Visual Discovery for Science
DESCRIPTION:Abstract: From social media all the way to satellite images\, we are capturing visual data at an unprecedented scale. These images tell a story about our planet. With advances in automatic recognition\, we can build a collective understanding of world-scale events as recorded through visual media. In this talk\, we will first explore the idea of automatic discovery from visual data in a relatively simpler domain of fashion data from social media images\, where powerful recognition models already exist. I will then discuss my work on an annotation-efficient method for building a multimodal vision-language model in the scientific domain of remote sensing where language annotations are sparse. Finally\, I will present my recent research on building interpretable models for scientific discovery using such black-box vision language models. \n\nBio: Utkarsh Mall is a postdoctoral research scientist in Computer Science at Columbia University. His research also focuses on building interpretable\, reliable\, and data-efficient methods to make novel scientific discoveries from visual data. He has also applied this research in various areas such as agriculture\, anthropology\, archaeology\, urban planning\, public health\, climate science\, etc. Before joining Columbia\, he earned his PhD from Cornell University\, where he worked on building label-efficient foundation models for scientific domains and leveraging them for unsupervised discoveries. He also co-organizes the CVPR workshop: Computer Vision for Science (CV4Science). His doctoral research was selected for the WACV 2022 and CVPR 2023 Doctoral Consortium. \n  \nonline: https://teams.microsoft.com/l/meetup-join/19%3a178c8aaec5e040879a9a053743b825cd%40thread.tacv2/1741628666733?context=%7b%22Tid%22%3a%22624d5c4b-45c5-4122-8cd0-44f0f84e945d%22%2c%22Oid%22%3a%222ac13d43-5ced-4b3c-a68a-5b66063407a9%22%7d
URL:https://homecse.iitd.ac.in/event/visual-discovery-for-science/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250325T120000
DTEND;TZID=Asia/Kolkata:20250325T170000
DTSTAMP:20260921T152941
CREATED:20250317T044524Z
LAST-MODIFIED:20250317T044524Z
UID:1461-1742904000-1742922000@homecse.iitd.ac.in
SUMMARY:The Case for Decentralised Scheduling in Modern Data Centres
DESCRIPTION:Abstract: Modern data centres serve as a backbone for executing diverse workloads. The growing demand for resources has led to high traffic volumes\, requiring clusters to operate at high utilisation. In this talk\, I will examine how current data centre schedulers\, responsible for mapping workload tasks to resources\, perform under such challenging conditions. I will discuss how centralised schedulers struggle to scale under high load\, as they generate significant network traffic by continuously transferring up-to-date node data. Conversely\, distributed schedulers scale well but lack a global cluster view\, leading to suboptimal task allocations. As a result\, existing schedulers impose up to three times longer wait times on tail tasks\, that is\, tasks that finish last among tasks of a job\, leading to increased task and job completion times. \nI will then introduce our work on decentralised scheduling\, focusing on performance\, scalability\, and load balancing. These schedulers have been under-explored due to their design complexity. However\, we demonstrate that Murmuration\, our job-aware decentralised scheduler\, achieves high performance despite its simple approach using approximate load information. It does so by reducing scheduler-node communication overhead while still achieving balanced load distribution across nodes. Prototype evaluations show that Murmuration reduces task wait times under both normal and high cluster loads\, improving median job completion times by 25% as compared to default Kubernetes’ centralised scheduler. Simulations further show that it outperforms various distributed and hybrid schedulers by two orders of magnitude. By the end of this talk\, I hope to convince you that decentralised schedulers strike the right balance between performance and scalability\, and are indeed a practical solution for today’s high utilisation data centres. \nBio: Smita Vijayakumar recently completed her PhD from the Department of Computer Science and Technology at the University of Cambridge\, under the supervision of Evangelia Kalyvianaki. As a part of her thesis\, she developed a novel decentralised scheduling framework to reduce tail task latencies in highly utilised data centres. She has over twelve years of industry experience at companies like Cisco and Juniper\, working on networking\, cloud computing\, and distributed systems. She also has an MS from The Ohio State University\, where her work investigated cloud resource allocation to bottleneck stages for processing streaming applications. Her research has been published in top-tier conferences\, and also as a book. She has also been actively involved in mentoring\, teaching\, and community leadership\, including founding Women Who Go\, India. Smita’s expertise spans resource management\, scheduling\, and scalable distributed systems.
URL:https://homecse.iitd.ac.in/event/the-case-for-decentralised-scheduling-in-modern-data-centres/
LOCATION:SIT 001\, Amar Nath and Shashi Khosla School of Information Technology\, IIT Delhi\, Hauz Khas\, New Delhi 110016\, India\, Delhi\, Delhi\, 110016\, India
CATEGORIES:Seminars
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END:VCALENDAR