Ian Davidson

Professor Ian Davidson is a faculty member in the Department of Computer Science at the University of California Davis, College of Engineering. His research focuses on machine learning, data mining, and constraint programming, with applications in neuroscience, healthcare, and social networks. He emphasizes rigorous algorithm design and human-in-the-loop learning paradigms.

• Editorial Board Member: ACM TKDD, IEEE TKDE, Springer DMKD
• Conference Leadership: PC Chair (SDM 2012), Vice/Area Chair (IEEE ICDM, ACM KDD, SIAM DM, ECML/PKDD 2013-2015)

Research Interests:

• Human-in-the-loop learning (active, transfer, and transductive frameworks)
• Constraint programming and spectral methods for clustering and classification
• Applications in neuroimaging analysis, intelligent tutoring systems, and social impact domains
• Fairness in machine learning and clustering algorithms
• Tensor decomposition and matrix factorization techniques
• Interdisciplinary collaborations in neuroscience and healthcare

Recent publications highlight his work on fairness-aware clustering with constraint programming, advanced spectral methods for brain connectivity analysis, and explainable AI frameworks. His research often combines theoretical rigor with practical applications in clinical domains.

Scientific Awards:

• Best Paper Award, SIAM Data Mining Conference 2005
• Best Paper Award, ECML/PKDD 2006
• Best Paper Award, ICDM 2006

Students & Collaborators:

• Former students: Xiang Wang (IBM Watson), Buyue Qian (Xi'an Jiaotong University), Tom Kuo (Google), Sean Gilpin (Google)
• Current advisees: Aubrey Guess, Zilong Bai, Erin McGinnis, Zheng Fang, Hongjing Zhang