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Author Information
Michael Holmes (RGM Advisors, LLC)
Alexander Gray (Skytree Inc. and Georgia Tech)
Charles Isbell (Georgia Tech)

Dr. Charles Isbell received his bachelor's in Information and Computer Science from Georgia Tech, and his MS and PhD at MIT's AI Lab. Upon graduation, he worked at AT&T Labs/Research until 2002, when he returned to Georgia Tech to join the faculty as an Assistant Professor. He has served many roles since returning and is now The John P. Imlay Jr. Dean of the College of Computing. Charles’s research interests are varied but the unifying theme of his work has been using machine learning to build autonomous agents who engage directly with humans. His work has been featured in the popular press, congressional testimony, and in several technical collections. In parallel, Charles has also pursued reform in computing education. He was a chief architect of Threads, Georgia Tech’s structuring principle for computing curricula. Charles was also an architect for Georgia Tech’s First-of-its’s-kind MOOC-supported MS in Computer Science. Both efforts have received international attention, and been presented in the academic and popular press. In all his roles, he has continued to focus on issues of broadening participation in computing, and is the founding Executive Director for the Constellations Center for Equity in Computing. He is an AAAI Fellow and a Fellow of the ACM. Appropriately, his citation for ACM Fellow reads “for contributions to interactive machine learning; and for contributions to increasing access and diversity in computing”.
More from the Same Authors
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2020 Invited Talk: You Can’t Escape Hyperparameters and Latent Variables: Machine Learning as a Software Engineering Enterprise »
Charles Isbell -
2017 Poster: State Aware Imitation Learning »
Yannick Schroecker · Charles Isbell -
2016 Workshop: The Future of Interactive Machine Learning »
Kory Mathewson @korymath · Kaushik Subramanian · Mark Ho · Robert Loftin · Joseph L Austerweil · Anna Harutyunyan · Doina Precup · Layla El Asri · Matthew Gombolay · Jerry Zhu · Sonia Chernova · Charles Isbell · Patrick M Pilarski · Weng-Keen Wong · Manuela Veloso · Julie A Shah · Matthew Taylor · Brenna Argall · Michael Littman -
2013 Poster: Point Based Value Iteration with Optimal Belief Compression for Dec-POMDPs »
Liam MacDermed · Charles Isbell -
2013 Poster: Policy Shaping: Integrating Human Feedback with Reinforcement Learning »
Shane Griffith · Kaushik Subramanian · Jonathan Scholz · Charles Isbell · Andrea L Thomaz -
2013 Poster: Which Space Partitioning Tree to Use for Search? »
Parikshit Ram · Alexander Gray -
2012 Poster: Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL »
Nishant A Mehta · Dongryeol Lee · Alexander Gray -
2009 Workshop: Large-Scale Machine Learning: Parallelism and Massive Datasets »
Alexander Gray · Arthur Gretton · Alexander Smola · Joseph E Gonzalez · Carlos Guestrin -
2009 Poster: Submanifold density estimation »
Arkadas Ozakin · Alexander Gray -
2009 Poster: Linear-time Algorithms for Pairwise Statistical Problems »
Parikshit Ram · Dongryeol Lee · William B March · Alexander Gray -
2009 Spotlight: Linear-time Algorithms for Pairwise Statistical Problems »
Parikshit Ram · Dongryeol Lee · William B March · Alexander Gray -
2009 Poster: Rank-Approximate Nearest Neighbor Search: Retaining Meaning and Speed in High Dimensions »
Parikshit Ram · Dongryeol Lee · Hua Ouyang · Alexander Gray -
2009 Poster: Solving Stochastic Games »
Liam MacDermed · Charles Isbell -
2008 Poster: QUIC-SVD: Fast SVD Using Cosine Trees »
Michael Holmes · Alexander Gray · Charles Isbell -
2008 Demonstration: MLPACK: Scalable Machine Learning Software »
Alexander Gray -
2008 Poster: Fast High-dimensional Kernel Summations Using the Monte Carlo Multipole Method »
Dongryeol Lee · Alexander Gray