Venue: SIT001 Abstract: This talk overviews recent results in the theoretical foundations of adversarially robust machine learning. Modern ML classifiers can fail spectacularly when subject to specially crafted input-perturbations, called… Read More »Machine Learning under Adversaries: How Structure in Data Helps by Ambar Pal

Venue: Bharti-501/ MS Teams Abstract: Building artificial intelligence with meaningful real-world impact requires models that can understand and interact in both the virtual and physical world. This talk outlines four key… Read More »Advancing Safe Multimodal Intelligence by Dr. Pritam Sarkar

Venue: Bharti501 Abstract: Over the last decade, confidential computing has emerged as an advanced security and privacy primitive that can fundamentally change the nature of trust that we place in… Read More »State of Confidential Computing by Dr. Kapil Vaswani

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