Please select the name from the list. If the name is not there, means it is not connected with a GND -ID?
GND: 140354522
Click on the author name for her/his data, if available
List of co-authors associated with the respective author. The font size represents the frequency of co-authorship.
Click on a term to reduce result list
The result list below will be reduced to the selected search terms. The terms are generated from the titles, abstracts and STW thesaurus of publications by the respective author.
b
Match by:
Sort by:
Records:
The information on the author is retrieved from: Entity Facts (by DNB = German National Library data service), DBPedia and Wikidata
Kevin Leyton-Brown
Alternative spellings: Kevin Leyton-Brown
B:1975 Biblio: Assistant Prof. of Computer Science, Univ. of British Columbia
Information about the license status of integrated media files (e.g. pictures or videos) can usually be called up by clicking on the Wikimedia Commons URL above.
Kevin Leyton-Brown (born May 12, 1975) is a Professor of Computer Science at the University of British Columbia. He received his Ph.D. at Stanford University in 2003. He was the recipient of a 2014 NSERC E.W.R. Steacie Memorial Fellowship, a 2013/14 Killam Teaching Prize, and a 2013 Outstanding Young Computer Science Researcher Prize from the Canadian Association of Computer Science. Leyton-Brown co-teaches a popular game theory course on Coursera.org, along with Matthew O. Jackson and Yoav Shoham. Leyton-Brown serves as an associate editor for the Journal of Artificial Intelligence Research, the Artificial Intelligence journal, and ACM Transactions on Economics and Computation', and was program chair for the ACM Conference on Electronic Commerce in 2012.Leyton-Brown and coauthors have received the IJCAI-JAIR Best Paper Prize and numerous medals in international SAT competitions (2003–12). Leyton-Brown's research is at the intersection of computer science and microeconomics, addressing computational problems in economic contexts and incentive issues in multiagent systems. He also studies the application of machine learning to the automated design and analysis of algorithms for solving hard computational problems. (Source: DBPedia)