Application of Federated Learning in Medical Imaging. - Ehsan Degan; Shafiq Abedin; David Beymer; Angshuman Deb; Nathaniel Braman; Benedikt Graf; Vandana V. Mukherjee (Federated Learning, 2022)

PROMINET: Prototype-based Multi-View Network for Interpretable Email Response Prediction. - Yuqing Wang; Prashanth Vijayaraghavan; Ehsan Degan (EMNLP (Industry Track), 2023)

Data-free Model Fusion with Generator Assistants. - Luyao Shi; Prashanth Vijayaraghavan; Ehsan Degan (CVPR Workshops, 2024)

Chain-of-Descriptions: Improving Code LLMs for VHDL Code Generation and Summarization. - Prashanth Vijayaraghavan; Apoorva Nitsure; Charles Mackin; Luyao Shi; Stefano Ambrogio; Arvind Haran; Viresh Paruthi; Ali El-Zein; Dan Coops; David Beymer; Tyler Baldwin; Ehsan Degan (MLCAD, 2024)

Self-Regulated Data-Free Knowledge Amalgamation for Text Classification. - Prashanth Vijayaraghavan; Hongzhi Wang 002; Luyao Shi; Tyler Baldwin; David Beymer; Ehsan Degan (NAACL (Industry Track), 2024)

VHDL-Eval: A Framework for Evaluating Large Language Models in VHDL Code Generation. - Prashanth Vijayaraghavan; Luyao Shi; Stefano Ambrogio; Charles Mackin; Apoorva Nitsure; David Beymer; Ehsan Degan (CoRR, 2024)

CIRCUITSYNTH: Leveraging Large Language Models for Circuit Topology Synthesis. - Prashanth Vijayaraghavan; Luyao Shi; Ehsan Degan; Xin Zhang (CoRR, 2024)

DECASTE: Unveiling Caste Stereotypes in Large Language Models through Multi-Dimensional Bias Analysis. - Prashanth Vijayaraghavan; Soroush Vosoughi; Lamogha Chizor; Raya Horesh; Rogério Abreu de Paula; Ehsan Degan; Vandana V. Mukherjee (CoRR, 2025)

AUTOCIRCUIT-RL: Reinforcement Learning-Driven LLM for Automated Circuit Topology Generation. - Prashanth Vijayaraghavan; Luyao Shi; Ehsan Degan; Vandana V. Mukherjee; Xin Zhang (CoRR, 2025)