Collaboration is all you need: LLM Assisted Safe Code Translation

Sun, 01 Jun 2025 00:00:00 +0000

LLM Reasoning & Code Generation

Wed, 01 Jan 2025 00:00:00 +0000

My research on LLMs spans reasoning evaluation, automated code/test generation, and reliability. Key contributions include:

AgentTester — A multi-agent framework for automated unit test generation that significantly improves software reliability (AIWare 2025).
HPCAgentTester — Extending multi-agent test generation to high-performance computing environments.
LogBabylon — A unified framework for cross-log file integration and analysis using LLMs.
Hallucination Mitigation — Techniques for reducing AI hallucinations in diagnostic and clinical contexts.
Evaluating LLM Rationality & Randomness — Benchmarking the quality of reasoning and entropy in LLM-supported tasks.
Synthesizing Public Opinions — Using LLMs to synthesize democratic discourse (IEEE ICEDEG 2025).

This line of research explores how multi-agent systems can produce more reliable, verifiable AI outputs, with applications from software engineering to healthcare.

Harnessing the Power of LLMs: Automating Unit Test Generation for High-Performance Computing

Sat, 06 Jul 2024 00:00:00 +0000

Software Engineering | Rabimba Karanjai

Collaboration is all you need: LLM Assisted Safe Code Translation

LLM Reasoning & Code Generation

Harnessing the Power of LLMs: Automating Unit Test Generation for High-Performance Computing