2015 - AAAI Feigenbaum Prize "For sustained and high-impact contributions to the field of artificial intelligence through the development of computational models of perception, reflection and action, and their application in time-critical decision making, and intelligent information, traffic and healthcare systems."
2015 - ACM AAAI Allen Newell Award For contributions to artificial intelligence and human-computer interaction spanning the computing and decision sciences through developing principles and models of sensing, reflection, and rational action.
2014 - ACM Fellow For contributions to artificial intelligence, and human-computer interaction.
2013 - Member of the National Academy of Engineering For computational mechanisms for decision making under uncertainty and with bounded resources.
2011 - Fellow of the American Academy of Arts and Sciences
2009 - Fellow of the American Association for the Advancement of Science (AAAS)
2002 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to principles and applications of probability and utility in computation, including reasoning and decision making under limited resources, human-computer interaction, and machine learning.
His primary areas of investigation include Human–computer interaction, World Wide Web, Artificial intelligence, Information retrieval and Data mining. The Human–computer interaction study combines topics in areas such as Context, User interface, Task and Control. His Context research includes themes of Real-time computing, Focus and Component.
His study on World Wide Web is mostly dedicated to connecting different topics, such as Internet privacy. Eric Horvitz focuses mostly in the field of Artificial intelligence, narrowing it down to matters related to Machine learning and, in some cases, The Internet. His Information retrieval research is multidisciplinary, incorporating perspectives in Timeline and Index.
Eric Horvitz mainly investigates Artificial intelligence, World Wide Web, Human–computer interaction, Machine learning and Context. His biological study spans a wide range of topics, including Data mining, Computer vision and Natural language processing. His studies deal with areas such as Information retrieval and Component as well as World Wide Web.
His Information retrieval research is mostly focused on the topic Web search query. His studies in Human–computer interaction integrate themes in fields like User interface, User modeling, Dialog box and Set.
Eric Horvitz focuses on Artificial intelligence, Data science, Machine learning, Set and World Wide Web. Eric Horvitz works mostly in the field of Artificial intelligence, limiting it down to topics relating to Perception and, in certain cases, Focus. His Data science study incorporates themes from Key and Missing data.
His study focuses on the intersection of Machine learning and fields such as Blind spot with connections in the field of Noise. In his work, Quality is strongly intertwined with Debugging, which is a subfield of Set. Eric Horvitz studies The Internet, a branch of World Wide Web.
His primary scientific interests are in Artificial intelligence, Set, Data science, Machine learning and World Wide Web. His Artificial intelligence research is multidisciplinary, relying on both Pattern recognition, Perception and Natural language processing. Eric Horvitz interconnects Pathfinder, Expert system, Health screening, False positive rate and Key in the investigation of issues within Data science.
His Machine learning research incorporates themes from Classifier, Intellect, Troubleshooting, Workflow and Component. His World Wide Web research includes elements of Psychological intervention and Adenocarcinoma. His work in Context tackles topics such as Receiver operating characteristic which are related to areas like Data mining.
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.
A Bayesian Approach to Filtering Junk E-Mail
Mehran Sahami;Susan Dumais;David Heckerman;Eric Horvitz.
national conference on artificial intelligence (1998)
Principles of mixed-initiative user interfaces
human factors in computing systems (1999)
Personalizing search via automated analysis of interests and activities
Jaime Teevan;Susan T. Dumais;Eric Horvitz.
international acm sigir conference on research and development in information retrieval (2005)
Predicting Depression via Social Media
Munmun De Choudhury;Michael Gamon;Scott Counts;Eric Horvitz.
international conference on weblogs and social media (2013)
The lumière project: Bayesian user modeling for inferring the goals and needs of software users
Eric Horvitz;Jack Breese;David Heckerman;David Hovel.
uncertainty in artificial intelligence (1998)
Technique which utilizes a probabilistic classifier to detect "junk" e-mail by automatically updating a training and re-training the classifier based on the updated training set
Eric Horvitz;David E. Heckerman;Susan T. Dumais;Mehran Sahami.
A diary study of task switching and interruptions
Mary Czerwinski;Eric Horvitz;Susan Wilhite.
human factors in computing systems (2004)
Notification platform architecture
Eric J. Horvitz;David O. Hovel;Andrew W. Jacobs;Carl M. Kadie.
Planetary-scale views on a large instant-messaging network
Jure Leskovec;Eric Horvitz.
the web conference (2008)
Sensing techniques for mobile interaction
Ken Hinckley;Jeff Pierce;Mike Sinclair;Eric Horvitz.
user interface software and technology (2000)
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