publications

2025

1. NeurIPS Workshop

   AuditCopilot: Leveraging LLMs for Fraud Detection in Double-Entry Bookkeeping

   Md Abdul Kadir, Sidharth S. Nair, S. S. M. Vasu, and 1 more author

   2025

   Abs arXiv PDF

   AuditCopilot is a hybrid LLM-driven anomaly detection system for accounting data, combining learned anomaly scoring with rule-based audit logic and natural language explanations for model decisions.

2023

1. EUSIPCO

   Learning to Precode for Integrated Sensing and Communication Systems

   RS Prasobh Sankar, Sidharth Nair, Siddhant Doshi, and 1 more author

   2023

   Abs arXiv Code

   In this paper, we present an unsupervised learning neural model to design transmit precoders for integrated sensing and communication (ISAC) systems to maximize the worst-case target illumination power while ensuring a minimum signal-to-interference-plus-noise ratio (SINR) for all the users. The problem of learning transmit precoders from uplink pilots and echoes can be viewed as a parameterized function estimation problem and we propose to learn this function using a neural network model. To learn the neural network parameters, we develop a novel loss function based on the first-order optimality conditions to incorporate the SINR and power constraints. Through numerical simulations, we demonstrate that the proposed method outperforms traditional optimization-based methods in presence of channel estimation errors while incurring lesser computational complexity and generalizing well across different channel conditions that were not shown during training."