Research Interests
Current Research
I am currently researching different Large Language Models (LLMs), with a specific focus on LLM safety. This area of research is critical as AI systems become more prevalent and powerful, requiring robust safety mechanisms to ensure responsible deployment.
Research Focus Areas
LLM Safety & Alignment
Investigating methods to ensure LLMs behave safely and align with human values. This includes studying adversarial robustness, prompt injection defenses, and content filtering mechanisms.
Model Evaluation & Benchmarking
Developing comprehensive evaluation frameworks to assess LLM safety across different dimensions, including toxicity, bias, and reliability metrics.
Fine-tuning & Safety Training
Exploring techniques like LoRA/QLoRA for efficient fine-tuning of LLMs with safety constraints, balancing model capabilities with safety requirements.
Multi-Agent Systems
Researching how multiple LLM agents interact in production environments, focusing on safety protocols and coordination mechanisms in agentic workflows.
Related Work
My practical experience building RAG systems, multi-agent architectures, and production LLM applications informs my research approach. I'm particularly interested in bridging the gap between theoretical safety research and real-world deployment challenges.