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

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

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

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

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

Venue: Bharti501 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" of novel failure modes and the sheer scale of telemetry. In this talk, I argue that the path forward requires a paradigm shift from… Read More »Abstractions for expressive, extensible, and scalable root cause analysis by Vipul Harsh

Venue. Bharti 501 Abstract. We present TESSERA, a pixel-wise foundation model for multi-modal (Sentinel-1/2) earth observation time series that learns robust, label-efficient embeddings.  Our goal with TESSERA is to make manipulating global satellite intelligence as easy as LLMs did for natural language! Towards this we release global, annual, 10m, pixel-wise embeddings together with open weights and… Read More »TESSERA: Programming Petabytes of Earth Observations using Foundation Models by Prof. Anil Madhavapeddy