Rajarshi Das

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	All	Since 2018
Citations	9433	1812
h-index	41	23
i10-index	71	37

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Jeff KephartDistinguished Research Staff Member, IBM ResearchVerified email at us.ibm.com
James E. HansonVerified email at jehanson.org
James CrutchfieldDistinguished Professor of Physics, University of California at DavisVerified email at ucdavis.edu
Charles LefurgyIBMVerified email at us.ibm.com
Canturk IsciMeta, Bloomberg CTO Office, IBM Research, VMwareVerified email at alumni.princeton.edu
L. Darrell WhitleyProfessor of Computer Science, Colorado State UniversityVerified email at cs.colostate.edu
Jeffrey K. MacKie-MasonUniversity Librarian, UC Berkeley; Professor of Information Science; Professor of EconomicsVerified email at berkeley.edu
Anshul GandhiStony Brook UniversityVerified email at cs.stonybrook.edu
Mor Harchol-BalterBruce J. Nelson Professor of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
J. David Schafferbinghamton universityVerified email at binghamton.edu
Robert FarrellIBM (retired)Verified email at us.ibm.com
Craig BoutilierPrincipal Scientist, GoogleVerified email at google.com
Charles Andersonprofessor of computer science, Colorado State University. Founder Pattern Exploration, LLC.Verified email at colostate.edu
Maja VukovicIBM T.J. Watson Research CenterVerified email at us.ibm.com
David C. ParkesGeorge F. Colony Professor of Computer Science, Harvard UniversityVerified email at eecs.harvard.edu
Nitendra RajputMastercardVerified email at acm.org
Scott FayProfessor of Marketing, Syracuse UniversityVerified email at syr.edu
Soundar KumaraAllen, E & Allen, M., Pearce Professor of Industrial Engeering, Professor of Computer Science andVerified email at psu.edu
Mike SpreitzerIBMVerified email at acm.org
Asser N. TantawiResearch Staff Member, IBM TJ Watson Research CenterVerified email at us.ibm.com

Rajarshi Das

FatBrain.io, Persistent.com

Verified email at fatbrain.io

Deep Learning Reinforcement Learning Artificial Intelligence Machine Learning


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A study of control parameters affecting online performance of genetic algorithms for function optimization JD Schaffer, R Caruana, LJ Eshelman, R Das Proceedings of the 3rd international conference on genetic algorithms, 51-60, 1989	1530	1989
Optimal power allocation in server farms A Gandhi, M Harchol-Balter, R Das, C Lefurgy ACM SIGMETRICS Performance Evaluation Review 37 (1), 157-168, 2009	646	2009
Utility functions in autonomic systems WE Walsh, G Tesauro, JO Kephart, R Das International Conference on Autonomic Computing, 2004. Proceedings., 70-77, 2004	615	2004
A hybrid reinforcement learning approach to autonomic resource allocation G Tesauro, NK Jong, R Das, MN Bennani 2006 IEEE International Conference on Autonomic Computing, 65-73, 2006	475	2006
Agent-human interactions in the continuous double auction R Das, JE Hanson, JO Kephart, G Tesauro International joint conference on artificial intelligence 17 (1), 1169-1178, 2001	375	2001
A multi-agent systems approach to autonomic computing G Tesauro, DM Chess, WE Walsh, R Das, A Segal, I Whalley, JO Kephart, ... Proceedings of the Third International Joint Conference on Autonomous Agents …, 2004	365	2004
Evolving cellular automata with genetic algorithms: A review of recent work M Mitchell, JP Crutchfield, R Das Proceedings of the First international conference on evolutionary …, 1996	315	1996
Genetic reinforcement learning for neurocontrol problems D Whitley, S Dominic, R Das, CW Anderson Machine Learning 13, 259-284, 1993	309	1993
Achieving self-management via utility functions JO Kephart, R Das IEEE Internet Computing 11 (1), 40-48, 2007	269	2007
Evolving globally synchronized cellular automata R Das, JP Crutchfield, M Mitchell, JM Hanson	247	1995
A genetic algorithm discovers particle-based computation in cellular automata R Das, M Mitchell, JP Crutchfield International conference on parallel problem solving from nature, 344-353, 1994	238	1994
Method and apparatus for automatic updating and testing of software R Das, ER Lassettre, A Segal, IN Whalley, SR White US Patent 7,216,343, 2007	225	2007
Analyzing complex strategic interactions in multi-agent systems WE Walsh, R Das, G Tesauro, JO Kephart AAAI-02 Workshop on Game-Theoretic and Decision-Theoretic Agents, 109-118, 2002	212	2002
Coordinating multiple autonomic managers to achieve specified power-performance tradeoffs JO Kephart, H Chan, R Das, DW Levine, G Tesauro, F Rawson, C Lefurgy Fourth International Conference on Autonomic Computing (ICAC'07), 24-24, 2007	204	2007
High-performance bidding agents for the continuous double auction G Tesauro, R Das Proceedings of the 3rd ACM Conference on Electronic Commerce, 206-209, 2001	191	2001
Autonomic multi-agent management of power and performance in data centers R Das, JO Kephart, C Lefurgy, G Tesauro, DW Levine, H Chan Proceedings of the 7th international joint conference on Autonomous agents …, 2008	172	2008
Managing power consumption and performance of computing systems using reinforcement learning G Tesauro, R Das, H Chan, J Kephart, D Levine, F Rawson, C Lefurgy Advances in neural information processing systems 20, 2007	171	2007
On the use of hybrid reinforcement learning for autonomic resource allocation G Tesauro, NK Jong, R Das, MN Bennani Cluster Computing 10, 287-299, 2007	155	2007
Adaptive problem determination and recovery in a computer system US Patent 20,040,059,966, 0	149*
Genetic reinforcement learning with multilayer neural networks D Whitley Proc. of the 4th Int. Conf. on Genetic Algorithm, 562-569, 1991	133	1991

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