Andrew McCallum

Professor McCallum has recommended books in the following areas:

References: [1], [2]


Andrew McCallum is a Distinguished Professor and Director of the Center for Data Science in the College of Information and Computer Sciences at the University of Massachusetts Amherst. He has published over 300 papers in many areas of artificial intelligence, including natural language processing, machine learning, data mining and reinforcement learning; his work has received over 70,000 citations. He received his PhD from University of Rochester in 1995 with Dana Ballard and a postdoctoral fellowship from Carnegie Mellon University with Tom Mitchell and Sebastian Thrun. Afterward he worked in an industrial research lab, where he spearheaded the creation of CORA, an early research paper search engine that used machine learning for spidering, extraction, classification and citation analysis. In the early 2000’s he was Vice President of Research and Development at at WhizBang Labs, a 170-person start-up company that used machine learning for information extraction from the Web. He was named a AAAI Fellow in 2009, and an ACM Fellow in 2017. He is the recipient of two NSF ITR awards, the UMass Chancellor’s Award for Outstanding Accomplishments in Research and Creative Activity, the UMass Lilly Teaching Fellowship, and research awards from IBM, Microsoft, Facebook, and Google. He was the Program Co-chair for the International Conference on Machine Learning (ICML) 2008, its General Chair in 2012, and from 2013 to 2017 was the President of the International Machine Learning Society. He is also a member of the editorial board of the Journal of Machine Learning Research. He has given tutorials or invited talks at NIPS, KDD, EMNLP, ISWC, and elsewhere. He organized the first workshop on Automated Knowledge Base Construction in 2009, and is the instigator and General Chair of the first international conference on Automated Knowledge Base Construction in 2019. He is also the creator of, which is being used for peer review management and/or reviewer assignment by ICLR, UAI, COLT, ICML, CVPR, and ECCV. For the past twenty years, McCallum has been active in research on statistical machine learning applied to text, especially information extraction, entity resolution, information integration, structured prediction, clustering, finite state models, semi-supervised learning, and social network analysis