Download Akshat Kumar - UMass Amherst

Akshat Kumar
Research Scientist
IBM Research India
[email protected]
http://www.cs.umass.edu/∼akshat
E DUCATION
4 Block C, Institutional Area
New Delhi
110070, India
University of Massachusetts, Amherst, MA, USA. (Fall 2007 – Sep. 2012)
Ph.D. in Computer Science
University of Massachusetts, Amherst, MA, USA. (Fall 2007 – Feb. 2010)
M.S. in Computer Science
Indian Institute of Technology (IIT), Guwahati, India. (2001 – 2005)
Bachelor of Technology in Computer Science and Engineering
R ESEARCH
INTERESTS
AWARDS
Artificial intelligence and machine learning – decision theoretic planning, multiagent systems,
graphical models, probabilistic inference, mathematical optimization, operations research.
2013 School of Computer Science Outstanding Dissertation Award, UMass Amherst
IFAAMAS Victor Lesser Distinguished Dissertation Runner-up Award at the International
Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2013.
Awarded UMass graduate school fellowship, academic year 2010-11.
Passed PhD candidacy with distinction (Fall-09), awarded to only two students per year in the
department.
Phi Kappa Phi honor society member (2010-11).
Department nominee for UMass graduate school fellowship, years 2009, 2007.
Letter of recognition from Amdocs development center, India (March-06) – typically awarded
to top employees of the company.
Received one year scholarship from EPFL AI Lab (July 2006 – June 2007).
Received scholarships to attend IJCAI-(07,09,11), AAAI-08, AAMAS-(09,10), NIPS-10, UAI-11.
P UBLICATIONS
P. Varkantham, A. Kumar Optimization Approaches for Solving Chance Constrained Stochastic Orienteering Problems. Accepted in International Conference on Uncertainty in Artificial Intelligence (ADT), 2013.
A. Kumar, D. Sheldon, B. Srivastava, Collective Diffusion Over Networks: Models and Inference.
Accepted in International Conference on Uncertainty in Artificial Intelligence (UAI), 2013.
D. Sheldon, T. Sun, A. Kumar, T. Dietterich, Approximate Inference in Collective Graphical Models.
Accepted in International Conference On Machine Learning (ICML), 2013.
W. Yeoh, A. Kumar, S. Zilberstein, Automated Generation of Interaction Graphs for Value-Factored
Decentralized POMDPs. Accepted in International Joint Conference on Artificial Intelligence
(IJCAI), 2013.
X. Wu, A. Kumar, D. Sheldon, S. Zilberstein, Parameter Learning For Latent Network Diffusion.
Accepted in International Joint Conference on Artificial Intelligence (IJCAI), 2013.
A. Kumar, X. Wu, S. Zilberstein, Lagrangian Relaxation Techniques for Scalable Spatial Conservation
Planning. In AAAI Conference on Artificial Intelligence (AAAI), 2012, pages 309–315.
Akshat Kumar
A. Kumar, S. Zilberstein, M. Toussaint, Message Passing Algorithms for MAP Estimation Using
DC Programming. In International Conference on Artificial Intelligence and Statistics (AISTATS), 2012, pages 656–664.
A. Kumar, S. Zilberstein, M. Toussaint, Scalable Multiagent Planning using Probabilistic Inference.
In International Joint Conference on Artificial Intelligence (IJCAI), 2011, pages 2140–2146.
A. Kumar, S. Zilberstein, Message-Passing Algorithms for Quadratic Programming Formulations
of MAP Estimation. In International Conference on Uncertainty in Artificial Intelligence (UAI),
2011, pages 428–435.
X. Wu, A. Kumar, S. Zilberstein, Influence Diagrams With Memory States: Representation and
Algorithms. In International Conference on Algorithmic Decision Theory (ADT), 2011, pages
306–319.
A. Kumar, S. Zilberstein, Message-Passing Algorithms for Large Structured Decentralized POMDPs
(extended abstract). In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2011, pages 1087–1088.
A. Kumar, S. Zilberstein, MAP Estimation for Graphical Models by Likelihood Maximization. In
Neural Information Processing Systems (NIPS), 2010, pages 1180–1188.
A. Kumar, S. Zilberstein, Anytime Planning for Decentralized POMDPs using Expectation Maximization. In International Conference on Uncertainty in Artificial Intelligence (UAI), 2010,
pages 294–301.
A. Kumar, S. Zilberstein, Point-Based Backup for Decentralized POMPDs: Complexity and New Algorithms. In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2010, pages 1315–1322.
A. Kumar, S. Zilberstein, Event-Detecting Multi-Agent MDPs: Complexity and Constant-Factor
Approximation. In International Joint Conference on Artificial Intelligence (IJCAI), 2009, pages
201–207.
A. Kumar, S. Zilberstein, Constraint-Based Dynamic Programming for Decentralized POMDPs with
Structured Interactions. In International Conference on Autonomous Agents and Multiagent
Systems (AAMAS), 2009, pages 561–568.
A. Kumar, B. Faltings, and A. Petcu, Distributed Constraint Optimization with Structured Resource Constraints. In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2009, pages 923–930.
A. Kumar, S. Zilberstein, Dynamic Programming Approximations for Partially Observable Stochastic games. In Florida Artificial Intelligence Research Society Conference (FLAIRS), 2009, pages
547–552.
A. Kumar, A. Petcu, and B. Faltings, H-DPOP: Using Hard Constraints for Search Space Pruning
in DCOP. In AAAI Conference on Artificial Intelligence (AAAI), 2008, pages 325–330.
A. Kumar, S. Nair, An Artificial Immune System based Approach for English Grammar Correction.
In International Conference on Artificial Immune Systems (ICARIS), 2007, pages 348–357.
S. Legg, M. Hutter and A. Kumar, Tournament versus Fitness Uniform Selection. In IEEE Congress
on Evolutionary Computation (CEC), 2004, pages 2144–2151.
W ORKSHOP
P UBLICATIONS
A. Kumar, W. Yeoh, and S. Zilberstein, On Message-Passing, MAP Estimation in Graphical Models
and DCOPs. In Distributed Constraint Reasoning Workshop, 2011, pages 57–70.
A. Kumar, A. Petcu, and B. Faltings, H-DPOP: Using Hard Constraints to Prune the Search Space.
In Distributed Constraint Reasoning Workshop, 2007, pages 40–55.
G RANT
P ROPOSALS
Major contributor to a three-year National Science Foundation (NSF) proposal titled Planning
Algorithms for Large Decentralized Multiagent Settings that was funded by NSF, start date – Fall
2011.
Akshat Kumar
Major contributor to a 18-month NSF funded proposal aimed to foster collaboration with the
Machine Learning Lab at FU Berlin, Germany headed by Prof. Marc Toussaint under the
Autonomous Learning program, start date – Feb. 2012.
I NVITED
TALKS
MAP Estimation for Graphical Models by Likelihood Maximization. Machine Learning and Friends
Lunch (MLFL) series, UMass Amherst, Dec. 2010.
Locality of Interaction in Decentralized POMDPs. Autonomous Intelligent Machines (MAIA)
lab., INRIA Lorraine, France, May 2008.
E MPLOYMENT /
I NTERNSHIPS
Research Scientist, IBM Research, New Delhi, India
(Oct. 2012 – present)
Business Analytics and Mathematical Sciences (BAMS) Department
Research Assistant, University of Massachusetts, Amherst
(Fall 2007 – Sep. 2012)
Resource bounded reasoning lab, advisor – Prof. Shlomo Zilberstein
Internship, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
(July 2006 – June 2007)
Advisor – Prof. Boi Faltings at the Artificial Intelligence Lab
Developed scalable algorithms for distributed constraint optimization (DCOP). Results published at AAAI-08 and AAMAS-09.
Subject Matter Expert, Amdocs Development Center, Pune, India
(Sept. 2005 – June 2006)
Worked on the order management system (OMS) project for AT&T. Awarded letter of recognition
To appreciate the dedication that exceeds what is reasonably demanded by the job function,
in fulfilling current tasks and achievements.
Internship, Jožef Stefan Institute, Ljubljana, Slovenia
(May 2004 – July 2004)
Advisor – Prof. Nada Lavrač, Dept. of Knowledge Technologies
C OMMUNITY
S ERVICE
Reviewer
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International Conf. on Automated Planning and Scheduling (ICAPS), 2008
AAAI Conf. on Artificial Intelligence, 2008
North-East Student Colloquium on Artificial Intelligence (NESCAI), 2010
Journal of Autonomous Agents and Mutiagent Systems (JAAMAS), 2010, 2011
International Conf. on Autonomous Agents and Multiagent Systems (AAMAS), 2012
Program Committee
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International Conf. on Automated Planning and Scheduling (ICAPS), 2013
International Conf. on Autonomous Agents and Multiagent Systems (AAMAS), 2013
International Joint Conf. on Artificial Intelligence (IJCAI), 2011, 2013
International Conf. on Uncertainty in Artificial Intelligence (UAI), 2012
International Workshop on Optimization in Multi-Agent Systems (OPTMAS), 2012, 2013
International Workshop on Multiagent Sequential Decision Making in Uncertain Domains (MSDM), 2013
Co-organizer of AAMAS 2012 Workshop on Multiagent Sequential Decision Making in Uncertain Domains (MSDM)
Co-organizer of the tutorial AI-Driven Analytics In Traffic Management at International Joint
Conference On Artificial Intelligence (IJCAI), 2013