Haohan Wang

Haohan Wang serves as Assistant Professor at the School of Information Sciences, University of Illinois Urbana-Champaign, with additional appointments as Affiliate at the Carl R. Woese Institute for Genomic Biology and Assistant Professor at the National Center for Supercomputing Applications (NCSA). His interdisciplinary work bridges machine learning, genomics, and AI security, focusing on trustworthy systems for biomedical applications and foundational AI research.

Wang's research centers on robust and secure artificial intelligence, with emphasis on large language model vulnerabilities (jailbreaking, safety evaluation), federated learning personalization, and genomic data analysis. He develops techniques for privacy-preserving dataset distillation, confounding factor correction in genome-wide studies, and multi-agent frameworks for scientific discovery. His fingerprint highlights expertise in Machine Learning (94%), Linear Mixed Models (87%), and Confounding Factor Correction (41%), reflecting his focus on methodological rigor in complex data environments.

Analysis of his 2025 publications reveals dominant trends in AI security (jailbreak evaluation frameworks like GuardVal, adversarial attacks such as InfoFlood), biomedical AI (transcriptomic analysis, wearable data privacy), and foundational methods (federated learning optimization, synthetic data generation). These works consistently address real-world challenges in model trustworthiness while advancing computational techniques for genomics and healthcare.

Through NCSA's high-performance computing resources and the Institute for Genomic Biology's collaborative ecosystem, Wang integrates supercomputing capabilities with biological research to tackle data-intensive problems in disease modeling and AI safety testing, as evidenced by media coverage of his team's AI security testing methods.