2020 - AAAI Distinguished Service Award For significant contributions to the field of artificial intelligence through sustained service to the Association for the Advancement of Artificial Intelligence and the furtherance of the field as a researcher, mentor and NSF IIS director.
2020 - AAAI Robert S. Engelmore Memorial Lecture Award For outstanding research contributions in the area of knowledge representation, data analytics, and data mining of social media for public good.
2018 - ACM AAAI Allen Newell Award For contributions to artificial intelligence and computational social science, including fundamental results on the complexity of inference, planning, and media analytics for public health.
2013 - ACM Fellow For contributions to artificial intelligence and pervasive computing with applications to assistive technology and health.
2006 - Fellow of the American Association for the Advancement of Science (AAAS)
1997 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For contributions to many areas of artificial intelligence, from plan recognition to knowledge representation to software agents.
Henry Kautz spends much of his time researching Artificial intelligence, Theoretical computer science, Satisfiability, Algorithm and Inference. His Artificial intelligence study frequently draws connections to other fields, such as Machine learning. His study in Theoretical computer science is interdisciplinary in nature, drawing from both #SAT, Structure and Graph, Graphplan.
He has researched Satisfiability in several fields, including WalkSAT, Guided Local Search, Backtracking and Distribution. His study in the field of Fragment also crosses realms of Point and Local consistency. His Inference research includes elements of Generality, Knowledge compilation, Knowledge base and Knowledge-based systems.
His scientific interests lie mostly in Artificial intelligence, Theoretical computer science, Machine learning, Inference and Algorithm. His research in Artificial intelligence is mostly concerned with Activity recognition. His work deals with themes such as Graphplan, Satplan and Knowledge representation and reasoning, which intersect with Theoretical computer science.
His Machine learning study combines topics from a wide range of disciplines, such as Domain and Conditional random field. His studies in Inference integrate themes in fields like Knowledge base, Data mining, Global Positioning System and Knowledge compilation. His study in Mathematical optimization extends to Algorithm with its themes.
Henry Kautz focuses on Artificial intelligence, Social media, Internet privacy, Natural language processing and Crowdsourcing. His Artificial intelligence research incorporates elements of Machine learning, Task and Identification. His Machine learning research is multidisciplinary, relying on both Mobile device and Probabilistic argumentation.
His Social media research also works with subjects such as
Henry Kautz mainly investigates Social media, Artificial intelligence, Internet privacy, Natural language processing and Natural language. Henry Kautz works mostly in the field of Social media, limiting it down to concerns involving Big data and, occasionally, Social computing and Multimedia. His Artificial intelligence research incorporates themes from Machine learning and Task.
His Machine learning research includes themes of Codebook, Mobile device and Human–computer interaction. The concepts of his Natural language processing study are interwoven with issues in Video tracking and Crowdsourcing. His study focuses on the intersection of Natural language and fields such as Speech recognition with connections in the field of Discriminative model, Pattern recognition, Image, Contrast and Matching.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Referral Web: combining social networks and collaborative filtering
Henry Kautz;Bart Selman;Mehul Shah.
Communications of The ACM (1997)
Planning as satisfiability
Henry Kautz;Bart Selman.
european conference on artificial intelligence (1992)
Constraint propagation algorithms for temporal reasoning: a revised report
Marc Vilain;Henry Kautz;Peter van Beek.
Pushing the envelope: planning, propositional logic, and stochastic search
Henry Kautz;Bart Selman.
national conference on artificial intelligence (1996)
Noise strategies for improving local search
Bart Selman;Henry A. Kautz;Brain Cohen.
national conference on artificial intelligence (1994)
Inferring activities from interactions with objects
M. Philipose;K.P. Fishkin;M. Perkowitz;D.J. Patterson.
IEEE Pervasive Computing (2004)
Learning and inferring transportation routines
Lin Liao;Donald J. Patterson;Dieter Fox;Henry Kautz.
Artificial Intelligence (2007)
Constraint propagation algorithms for temporal reasoning
Marc Vilain;Henry Kautz.
national conference on artificial intelligence (1986)
Local search strategies for satisfiability testing
Bart Selman;Henry A. Kautz;Bram Cohen.
Cliques, Coloring, and Satisfiability : 2nd DIMACS Implementation Challenge (1993)
Boosting combinatorial search through randomization
Carla P. Gomes;Bart Selman;Henry Kautz.
national conference on artificial intelligence (1998)
Profile was last updated on December 6th, 2021.
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