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Coping with choices – List Decoding in Coding Theory by Dr. Shashank Srivastava

Bharti 501 IIT Campus, Hauz Khas, New Delhi

Venue: Bharti-501/MS Teams Abstract: The goal of error correcting codes is to encode data in a way that allows for this data to be recovered even if the encoded copy is corrupted by an adversary. The usual algorithmic challenge associated with codes, called decoding, is to output the uncorrupted copy of data by looking only at… Read More »Coping with choices – List Decoding in Coding Theory by Dr. Shashank Srivastava

Agentic Information Seeking for Knowledge Acquisition by Revanth Reddy

SIT 001 Amar Nath and Shashi Khosla School of Information Technology, IIT Delhi, Hauz Khas, New Delhi 110016, India, Delhi, Delhi, India

Venue: SIT001 Abstract:  The vast expansion of online information has shifted the challenge from simply locating data to efficiently filtering and aggregating relevant content from diverse sources. This talk introduces innovative methodologies aimed at enhancing automated information seeking capabilities within intelligent systems. I will present a modular, agent-based framework that decomposes the information-seeking process into navigation,… Read More »Agentic Information Seeking for Knowledge Acquisition by Revanth Reddy

WhiteLie: A Robust System for Spoofing User Data in Android Platforms by Harish Yadav

SIT 113 Amar Nath and Shashi Khosla School of Information Technology, Indian Institute of Technology, Delhi, Hauz Khas, New Delhi, Delhi, India

Venue: SIT113 Abstract: The Android operating system uses a permission framework that allows users to control access to their private data, such as location and contacts, when using apps. However, many apps become non-functional or crash if denied these permissions, effectively pressuring users to grant access and compromising their privacy. In this paper, we introduce WhiteLie,… Read More »WhiteLie: A Robust System for Spoofing User Data in Android Platforms by Harish Yadav

Logical Relations for Formally Verified Authenticated Data Structures by Chaitanya Agarwal

Bharti 501 IIT Campus, Hauz Khas, New Delhi

Venue: Bharti501 Abstract: 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… Read More »Logical Relations for Formally Verified Authenticated Data Structures by Chaitanya Agarwal

Lumos: A DSL for Language Model System Certification by Isha Chaudhary

Bharti 501 IIT Campus, Hauz Khas, New Delhi

Venue: Bharti 501 Abstract: As Language Model Systems (LMS) are deployed across an expanding range of applications, aligning them with human ethics has become crucial. Although recent works propose methods to formally certify LMS properties such as fairness, correct question answering, and safety, these approaches are generally ad hoc and hard to generalize. We introduce a principled… Read More »Lumos: A DSL for Language Model System Certification by Isha Chaudhary

Image decomposition with Fluorescence Microscopy Data by Ashesh

Bharti 501 IIT Campus, Hauz Khas, New Delhi

Venue: Bharti501 Abstract: Fluorescence microscopy is limited by optics, fuorophore chemistry, and photon exposure, forcing trade-ofs in speed, resolution, and depth. In this talk, I will discuss my PhD research that addresses these challenges. Specifcally, my PhD research enables imaging of multiple cellular structures within a single fuorescent channel, allowing faster imaging with less photon… Read More »Image decomposition with Fluorescence Microscopy Data by Ashesh

Deep generative models for single-cell and spatial genomics by Ajita Shree

Bharti 501 IIT Campus, Hauz Khas, New Delhi

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. Abstract: 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.… Read More »Deep generative models for single-cell and spatial genomics by Ajita Shree

A new characterization of VNP via colored determinant by Dr. Prasad Chaugule

Bharti 501 IIT Campus, Hauz Khas, New Delhi

Venue: Bharti501 Abstract: Understanding the algebraic complexity class VNP through alternative characterizations is a central theme in algebraic complexity theory, closely tied to the VP vs. VNP problem. While the permanent provides a canonical complete polynomial for VNP, identifying natural and combinatorial variants that lead to new structural insights remains an important challenge.In this talk,… Read More »A new characterization of VNP via colored determinant by Dr. Prasad Chaugule

Approximately Packing Dijoins Via Nowhere-Zero Flows by Dr. Ravi

Bharti 501 IIT Campus, Hauz Khas, New Delhi

Venue: Bharti501 Abstract: In a digraph, a dicut is a cut where all the arcs cross in one direction. A dijoin is a subset of arcs that intersects each dicut. Woodall conjectured in 1976 that in every digraph, the minimum size of a dicut equals to the maximum number of disjoint dijoins. By building connections… Read More »Approximately Packing Dijoins Via Nowhere-Zero Flows by Dr. Ravi

Molecular Machine Learning for Chemical Catalysis by Dr. Sukriti Singh

SIT 001 Amar Nath and Shashi Khosla School of Information Technology, IIT Delhi, Hauz Khas, New Delhi 110016, India, Delhi, Delhi, India

Venue: SIT001 Abstract: The development of new reaction methodology could become a tedious task demanding both time and resources. The application of machine learning (ML) approaches for reaction optimization and prediction can make a significant impact on efficient exploration of the high-dimensional chemical space. But the direct adaptation of ML as used in well-developed domains,… Read More »Molecular Machine Learning for Chemical Catalysis by Dr. Sukriti Singh