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X-ORIGINAL-URL:https://homecse.iitd.ac.in
X-WR-CALDESC:Events for Computer Science and Engineering
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TZID:Asia/Kolkata
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TZOFFSETFROM:+0530
TZOFFSETTO:+0530
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DTSTART:20250101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250403T110000
DTEND;TZID=Asia/Kolkata:20250403T170000
DTSTAMP:20260924T034150
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
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250408T160000
DTEND;TZID=Asia/Kolkata:20250408T170000
DTSTAMP:20260924T034150
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/
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250422T110000
DTEND;TZID=Asia/Kolkata:20250422T120000
DTSTAMP:20260924T034150
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:20250422T120000
DTEND;TZID=Asia/Kolkata:20250422T130000
DTSTAMP:20260924T034150
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:20250424T120000
DTEND;TZID=Asia/Kolkata:20250424T170000
DTSTAMP:20260924T034150
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:20250425T120000
DTEND;TZID=Asia/Kolkata:20250425T170000
DTSTAMP:20260924T034150
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:20250428T120000
DTEND;TZID=Asia/Kolkata:20250428T130000
DTSTAMP:20260924T034150
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:20250429T150000
DTEND;TZID=Asia/Kolkata:20250429T160000
DTSTAMP:20260924T034150
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
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