Papers by Vandana Mukherjee
CODMAS: A Dialectic Multi-Agent Collaborative Framework for Structured RTL Optimization (2026.eacl-industry)
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Che-Ming Chang, Prashanth Vijayaraghavan, Ashutosh Jadhav, Charles Mackin, Hsinyu Tsai, Vandana Mukherjee, Ehsan Degan
| Challenge: | generating and optimizing Hardware Description Languages (HDLs) remains challenging. |
| Approach: | They propose a framework that combines dialectic reasoning with domain-aware code generation and deterministic evaluation to automate RTL optimization. |
| Outcome: | The proposed framework reduces critical path delay and power loss by 25% compared to baselines. |
SYMDIREC: A Neuro-Symbolic Divide-Retrieve-Conquer Framework for Enhanced RTL Synthesis and Summarization (2026.eacl-industry)
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Prashanth Vijayaraghavan, Apoorva Nitsure, Luyao Shi, Charles Mackin, Ashutosh Jadhav, David Beymer, Ehsan Degan, Vandana Mukherjee
| Challenge: | Existing prompting and retrieval-augmented generation methods lack symbolic planning . rigid HDL syntax, limited supervision, and weak alignment with natural language hinder RTL synthesis and summarization. |
| Approach: | SYMDIREC decomposes RTL tasks into symbolic subgoals and assembles verified outputs . a neuro-symbolic framework supports both Verilog and VHDL without LLM fine-tuning . |
| Outcome: | SYMDIREC achieves higher Pass@1 rates for synthesis and 15–20% ROUGE-L improvements for summarization over prompting and RAG . synthesis, summarizing require preserving strict HDL syntax, modular structure, and precise functional semantics, authors show . |