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… Read More »WhiteLie: A Robust System for Spoofing User Data in Android Platforms by Harish Yadav

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… 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… 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… 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.… 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… 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… 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… Read More »TESSERA: Programming Petabytes of Earth Observations using Foundation Models by Prof. Anil Madhavapeddy