Jian Kang

Jian Kang is an Assistant Professor of Computer Science at the University of Rochester's Hajim School of Engineering & Applied Sciences. He joined in August 2023 after earning his Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign. His research focuses on trustworthy artificial intelligence, data mining, computational social science, and algorithmic fairness, with a strong emphasis on ensuring ethical and reliable AI systems.

Education:

• Ph.D. in Computer Science, University of Illinois at Urbana-Champaign

Research Interests:

• Data Mining and Machine Learning
• Trustworthy AI and Uncertainty Quantification
• Algorithmic Fairness and Bias Mitigation
• Computational Social Science

His work explores fair and reliable modeling of interconnected systems, leveraging graph learning, fairness-aware algorithms, and uncertainty analysis.

Publications Trends: Recent work emphasizes fairness in graph neural networks, bias analysis in language models, and robust graph learning methods. Key themes include cross-lingual bias benchmarking, class-imbalanced learning, and theoretical foundations for fairness and uncertainty.

Awards and Recognition:

• Rising Stars in Data Science (2022)
• Mavis Future Faculty Fellow (2022)
• Top Reviewer for LOG 2022, NeurIPS 2022, CIKM 2021, ICLR 2021, and ICML 2020

Advising and Grants: While no specific grants are listed, his research has led to impactful contributions in fairness and graph learning, with publications in top venues like ICLR, KDD, and TKDE. He advises on cutting-edge topics in trustworthy AI.

Labs and Teams: His work is part of a broader effort at Rochester to advance ethical AI and computational methods, though no specific lab name is mentioned in the text.