Shwai He

Shwai He is a PhD student and Affiliate Assistant Professor at the University of Maryland, advised by Ang Li. Their research focuses on advancing AI systems through innovative approaches in large language models (LLMs), fairness in machine learning, and efficient neural network architectures. Key areas include multi-agent systems, causal modeling for bias mitigation, and optimization techniques for mixture-of-experts models.

Research interests span artificial intelligence, machine learning, and natural language processing with emphasis on practical applications like healthcare diagnostics and social pairing systems. Notable work includes developing GNWT-based multi-agent digital twins for social platforms and improving LLM transparency through token analysis.

Publications highlight contributions to counterfactual fairness, dynamic-depth transformers, and parameter-efficient methods. Current efforts explore computational efficiency in vision-language models and bio-inspired antibody prediction systems. No scientific awards have been mentioned.

Advising and grants: Currently a PhD student under Ang Li's supervision. Research involves collaborations across computer science and bioinformatics domains.