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
Abstract: A common denominator of conventional financial systems, trusted execution environments (like SGX), blockchain technology, and ZK-rollups is the promise of computational integrity -- doing the right computation on potentially secret… Read More »Cryptographic proofs for privacy and integrity by Prof. Chaya Ganesh (IISc)
Abstract: The convergence of artificial intelligence (AI), the Internet of Things (IoT), cloud-edge computing, and autonomous cyber-physical systems is transforming critical infrastructures across healthcare, manufacturing, transportation, and smart cities. As… Read More »Building Trustworthy Intelligent Systems for Critical Infrastructures by Dr. Geetanjali
Abstract: Modern Internet-scale services must identify and mitigate customer-impacting incidents quickly. Despite the development of many Root Cause Analysis (RCA) algorithms—including recent LLM-assisted solutions—existing approaches struggle with the "long tail"… Read More »Abstractions for expressive, extensible, and scalable root cause analysis by Dr. Vipul Harsh
Abstract: We will discuss two new frontiers in science. 1) Autonomous AI Scientists: Research conducted by autonomous AI scientist systems is rapidly increasing in prevalence. These systems execute the entire research… Read More »Two New Frontiers in Science: Autonomous AI Scientists and Lotteries for Acceptance Decisions by Prof Nihar Shah
In this talk I will start by describing a protocol called magic state distillation, which was first introduced by Bravyi and Kitaev in 2005. This protocol uses quantum error-correcting codes… Read More »Weight Enumerators and Magic State Distillation by Dr. Amolak Kalra
Abstract: What can be learned from data? Traditional answers to this question assume an idealized data-generating process where test and training distributions are symmetric, which is rarely the case in… Read More »Foundations of Learning from Positive Samples by Dr. Anay Mehrotra
Abstract: The volume of data generated worldwide is growing at an unprecedented rate, and GPUs have emerged as the primary compute engine for processing this data. While GPUs offer massive… Read More »Scaling Up GPU Memory Management by Dr. Pratheek B
