Venue: Bharti501 Abstract: Memory bandwidth scaling has emerged as a critical bottleneck as compute capabilities continue to grow faster than DRAM performance. This talk examines why higher memory frequencies do… Read More »Challenges in scaling memory bandwidth in modern SoCs by Nithya Bashyam
Venue: Bharti501 Abstract: Secure Multi-Party Computation (MPC) is a central problem in cryptography, often regarded as its holy grail. It enables a group of mutually distrusting data owners to jointly… Read More »The Landscape of Exact Round Complexity in Secure Multi-Party Computation by Prof. Arpita Patra
Venue: Bharti501 Abstract: This talk will provide a perspective on where we are at IBM Quantum in building useful quantum computers. There are two main pillars: developing a quantum computing… Read More »Quantum Computing: Towards Advantage by Dhinakaran Vinayagamurthy
Venue: SIT001 Online joining: https://teams.microsoft.com/meet/48853006918605?p=788lqF84K1ykLq1rtg Abstract: Standard supervised learning on neuroimaging data optimizes for diagnostic prediction while yielding feature-level importance scores that lack network-level, assessment-specific interpretability required for biomarker discovery; while… Read More »Learning assessment-aware brain representations from multimodal neuroimaging data by Dr. Ishaan Batta
Online joining: https://teams.microsoft.com/meet/44299089959938?p=5wwN132pf54i4sVnyN Abstract: Successful engagement with the physical world involves perceiving the underlying structure, predicting how things unfold, and planning actions accordingly. This rich understanding and reasoning about our physical… Read More »Physical reasoning in Minds, Brains, and Machines by Dr. Pramod RT
Venue: SIT001 Abstract: Solving long-horizon tasks remains a central challenge in robotics because agents must explore efficiently, assign credit over long time scales, and act under sparse supervision. To address… Read More »Learning Hierarchical Control via Feasible Subgoal Prediction by Utsav Singh
Venue: Bharti-501/ MS Teams Abstract: In-Context Learning (ICL) is a remarkable phenomenon whereby transformer-based LLMs can use data contained within their prompts to adapt their responses, without changing their weights. This suggests… Read More »Algorithmic Behaviours in In-Context Learning by Dr. Aditya Gangrade
Abstract: This talk explores a novel approach to speeding up complex database queries by combining two powerful ideas: factorization and vectorized execution. Instead of processing large intermediate results (which can… Read More »Faster Queries, Smarter Execution: Factorization Meets Vectorization in Modern Data Systems
Abstract: In many settings, a finite supply of some public resource is allocated among people over time, without using money: a computing cluster among researchers, food among food-banks, medical supplies between… Read More »The Mathematics (and Ethics) of Fair Resource Allocation by Dr. Siddhartha Banerjee (Cornell University)
Abstract: The Pigeonhole Equal Subset Sum problem (PESS), introduced by Papadimitriou (1994), asks: given n positive integers bounded by M with total sum less than 2^n − 1, find two… Read More »Finding Equal Subset Sums in the Pigeonhole Regime by Dr. Pranjal Dutta
