Stuart Russell, Curriculum Vitae


Professor of Computer Science and Michael H. Smith and Lotfi A. Zadeh Chair in Engineering,
Computer Science Division
University of California
Berkeley, CA 94720

Adjunct Professor of Neurological Surgery, University of California, San Francisco

Tel. (510) 642-4964
Fax (510) 642-5775
Email russell@cs.berkeley.edu
Home page http://www.cs.berkeley.edu/~russell

Education

B.A. (Hons.) 1st Class, Physics, Wadham College, University of Oxford, 1979--82.
Ph.D., Computer Science, Stanford University, 1982--86.

Employment history

2012--2014, Professeur Invité, Université Pierre et Marie Curie, Paris
2012--2014, Professeur, Fondation de l'École Normale Supérieure, Paris
2008--present, Adjunct Professor, Department of Neurological Surgery, University of California, San Francisco
2008--2010, Chair, Department of Electrical Engineering and Computer Sciences, University of California, Berkeley
2006--2010, Chair, Computer Science Division, University of California, Berkeley
1996--present, Professor, Computer Science Division, University of California, Berkeley
1991--96, Associate Professor, Computer Science Division, University of California, Berkeley
1986--91, Assistant Professor, Computer Science Division, University of California, Berkeley
1986, Summer employee, MCC, Austin, Texas, Machine learning research in the Large Scale KB Project (CYC)
1985--86, Research Assistant, Computer Science Dept., Stanford University
1983, Teaching Assistant, Computer Science Dept., Stanford University
1981, Programmer, graphics research project, IBM Los Angeles Scientific Center
1978--80 (1 year total), Programmer, IBM Systems Engineering Centre, Warwick, UK

Honours, Awards

Paper Prizes

Invited/Keynote Speeches


Professional and Service

Executive Council Member, American Association for Artificial Intelligence, 1997-2000
Founding board member and Secretary, International Machine Learning Society, 2001-2007
Secretary, JMLR Foundation (Journal of Machine Learning Research)

External Advisory Board, Center for the Study of Existential Risk, Cambridge
External Advisory Board, Future of Life Institute, Harvard/MIT
Vice-Chair, Global Advisory Council on AI and Robotics, World Economic Forum
Member, ACM Grace Murray Hopper Award Committee, 2013-present
Chair, ACM Grace Murray Hopper Award Committee, 2014-present
Member, ACM Awards Committee, 2014-present

Editor, Prentice Hall Series in Artificial Intelligence
Research Highlights Editor, Communications of the ACM, 2008-2012
Associate Editor (Artificial Intelligence), Journal of the ACM, 2000-2008
Associate Editor and Advisory Board member, Journal of Artificial Intelligence Research
Associate Editor, Journal of Machine Learning Research
Editorial Board, Machine Learning Journal (until 2000)
Associate Editor, Artificial Intelligence
Editorial Board, AI Communications
Advisory Board, Springer-Verlag Series in Cognitive Technology
Board member and US-UK Secretary, Machine Intelligence Series
Advisory Editor for AI and Computer Science, MIT Press Encyclopaedia of the Cognitive Sciences

Chair, AAMAS Workshop on the Future of Artificial Intelligence, 2014
Chair, IJCAI Panel on the Future of Artificial Intelligence, 2013
Chair, DARPA Workshop on Human-Level AI, 2004
Co-Chair, AAAI Fall Symposium on Learning Complex Behaviours, 1996
Co-Chair, Workshop on Learning in Bayesian Networks, NIPS 95
Program and Conference Co-Chair, Int'l Conference on Machine Learning, 1995
Program and Symposium Chair, AAAI Symposium on AI and Limited Rationality, Stanford, 1989

Program Area Chair, AI and Cognitive Science areas, NIPS 96
Program Area Chair (Decision Theory, Machine Learning, Search), AAAI 94
Program Area Chair (Machine Learning), AAAI 90

Organizing and Program Committee, International Workshop on Statistical Relational AI, 2012
Organizing and Program Committee, AAAI Spring Symposium on Decision-Theoretic Planning, 1994
Organizing and Program Committee, AAAI Fall Symposium on Planning and Learning in Games, 1993
Organizing and Program Committee, IEEE Workshop on Imprecise and Approximate Computation, 1992
Organizing and Program Committee, Workshop on Theoretical and Practical Design of Rational Agents, IJCAI 91

Member, Program Committee, AAAI 88, AAAI 90, AAAI 92, International Conference on Machine Learning 1992, 1993, 1994, 1996, Third International Conference on Multistrategy Learning, 1993, Int'l Conference on Knowledge Representation and Reasoning, 1994, 1998, 2002, ACM Workshop on Computational Learning Theory, 1998, European Conference on AI, 1996, European Conference on Machine Learning, 2000, KDD Workshop on Record Linkage, 2003, ICML Workshop on Statistical Relational Learning, 2004, ICML Workshop on Relational Reinforcement Learning, 2004, ICMl Workshop on Machine Learning for Clinical Data Analysis, 2012, Second Conference on Meaningful Use of Complex Medical Data, 2012.

National Science Foundation Review Panelist
Fellowship Panel, National Research Council
Proposal Reviewer, National Science Foundation, California MICRO Program, Air Force Office of Scientific Research
Panelist, Defense Threat Reduction Agency, 2001

Commentator, Behavioral and Brain Sciences
Reviewer, Artificial Intelligence Journal, Machine Learning Journal, Journal of Artificial Intelligence Research, Computational Intelligence Journal, International Journal of Intelligent Systems, Journal of the ACM, Journal of Logic and Computation, ACM Transactions on Programming Languages and Systems, ACM Transactions on Computer Systems, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Data and Knowledge Engineering, IEEE Transactions on Systems, Man and Cybernetics, Cognitive Science Journal.
Reviewer, ACM Dissertation Award, 1988
Reviewer, International Joint Conference on Artificial Intelligence (1987, 1989, 1991, 1993, 1995), Conference on Uncertainty in AI (1991, 1992), International Conference on Automata, Languages, and Programming (1987), Symposium on Parallel and Distributed Programming (1993), Fifth Generation Computer Systems (1992).
Book Reviewer, MIT Press, Pitman Press, Addison-Wesley, Morgan Kaufmann, Cambridge University Press

Organizing Committee, Newsletter Editor, and Spokesperson, British Scientists Abroad, 1990--92
Chairman, British Scientists Abroad, 1993--96

University Service

Computer Science Division
Chair (2006--10)
Chair, Faculty Search Committee (2000)
Faculty Search Committee (1994, 1995, 1997, 1999, 2001, 2002, 2003, 2004)
Chair, Competitions Committee(1990--92)
Reentry Program Committee(1986--90)
Undergraduate Study Committee (1991)
Graduate Admissions Committee (2002)
Scheduling Officer (1993--97)

EECS Department
Vice-Chair for Undergraduate Matters (2011-12)
Chair (2008--10)
Associate Chair (2006--8)
Executive Committee (2001--2, 2005--6)
Co-Chair, Faculty Retreat Committee (1998--99, 2003-04)
Co-Chair, Scheduling Committee (1993--97)
Undergraduate Advisor
Minority Graduate Student Mentor
Student Awards Committee
Faculty Search Committee (non-conventional computing)
Graduate Study Committee
Curriculum Revision Committee

Other departments
IEOR Dept Faculty Search Committee (1995)
Bioengineering Dept Faculty Search Committee (2000)
Cognitive Science Program Faculty Search Committee (2005)
Cognitive Science Program Ad Hoc Committee (2010)

College of Engineering
Committee on Undergraduate Studies (2011-12)

University
Committee on Undergraduate Scholarships and Honours (1996--2008)
Chair, Committee on Undergraduate Scholarships and Honours (2000--2006)
Chair, Truman Subcommittee, Committee on Undergraduate Scholarships and Honours (1999--2000)
Member, Coordination Board for Undergraduate Admissions, Financial Aid, and Enrollment Management (2002--2006)
Trustee, International Computer Science Institute (2006--2010)

UC Systemwide
Steering Committee on Life Science Informatics (1999)


Publications

Books
  1. Stuart Russell The Use of Knowledge in Analogy and Induction. London: Pitman, 1989.
  2. Stuart Russell and Eric H. Wefald Do the Right Thing: Studies in Limited Rationality. Cambridge, MA: MIT Press, 1991.
  3. Stuart Russell and Peter Norvig Artificial Intelligence: A Modern Approach. Englewood Cliffs, NJ: Prentice Hall, 1995.
  4. Stuart Russell and Peter Norvig Solution Manual for ``Artificial Intelligence: A Modern Approach.'' Englewood Cliffs, NJ: Prentice Hall, 1995.
  5. Armand Prieditis and Stuart Russell (Eds.), Machine Learning: Proceedings of the Twelfth International Conference, Tahoe City, CA: Morgan Kaufmann, 1995.
  6. Stuart Russell and Peter Norvig, Inteligencia Artificial: Un Enfoque Moderno (R. Gutierrez, Tr.). Mexico City: Prentice Hall Hispanoamericana, 1997.
  7. Stuart Russell and Peter Norvig, [Artificial Intelligence: A Modern Approach] (in Japanese; Tr. Koichi Furukawa et al.). Tokyo: Kyoritsu Shuppan, 1997.
  8. Stuart Russell and Peter Norvig, Intelligenza Artificiale: Un Approccio Moderno (L. Aiello, Tr.). Turin, Italy: UTET Libreria Srl, 1998.
  9. Stuart Russell and Peter Norvig, Mesterséges Intelligencia Modern Megközelitésben. (Hungarian translation of Artificial Intelligence: A Modern Approach.) Budapest, Panem Publishing, 1999.
  10. Stuart Russell and Peter Norvig Artificial Intelligence: A Modern Approach (Second Edition). Upper Saddle River, NJ: Prentice Hall, 2003.
  11. Stuart Russell and Peter Norvig, ``Solution Manual for Artificial Intelligence: A Modern Approach.'' 2nd Edition, Prentice Hall, 2003.
  12. Stuart Russell and Peter Norvig, Inteligencia Artificial. (Portuguese translation of Artificial Intelligence: A Modern Approach, s\ econd edition.) Rio de Janeiro: Elsevier/Editora Campus, 2004.
  13. Stuart Russell and Peter Norvig, 《人工智能——一种现代方法(第二版)》 (Chinese Simplified translation of Artificial Intelligence: A Modern Approach, second edition.) Beijing: Posts and Telecommunications Press, 2004.
  14. Stuart Russell and Peter Norvig, Inteligencia Artificial: Un Enfoque Moderno. (Spanish translation of Artificial Intelligence: A Modern Approach, second edition.) Madrid: Pearson Educación, S. A., 2004.
  15. Stuart Russell and Peter Norvig, Τεχνητή Νοημοσύνη, Μια σύγχρονη προσέγγιση. (Greek translation of Artificial Intelligence: A Modern Approach, second edition.) Athens: Kleidarithmos, 2004.
  16. Stuart Russell and Peter Norvig, Intelligenza Artificiale Vol. 1 Un Approcio Moderno. (Vol. 1 of Italian translation of Artificial Intelligence: A Modern Approach, second edition.) Rome: Pearson Italia, 2005.
  17. Stuart Russell and Peter Norvig, Künstliche Intelligenz: Ein moderner Ansatz (2nd Edition). (German translation of Artificial Intelligence: A Modern Approach, second edition.) Munich: Verlag Pearson Studium, 2005.
  18. Stuart Russell and Peter Norvig, Искусственный интеллект: современный подход. (Russian translation of Artificial Intelligence: A Modern Approach, second edition.) Translated by Konstantin Ptitsyn. Moscow: Williams Publishing, 2005.
  19. Stuart Russell and Peter Norvig, Mesterséges Intelligencia Modern Megközelitésben. (Hungarian translation of Artificial Intelligence: A Modern Approach, second edition.) Budapest, Panem Publishing, 2006.
  20. Stuart Russell and Peter Norvig, Intelligenza Artificiale Vol. 2 Un Approcio Moderno. (Vol. 2 of Italian translation of Artificial Intelligence: A Modern Approach, second edition.) Rome: Pearson Italia, 2006.
  21. Stuart Russell and Peter Norvig, Intelligence artificielle, 2e éd.. (French translation of Artificial Intelligence: A Modern Approach, second edition.) Paris: Pearson Education France, 2006.
  22. Stuart Russell and Peter Norvig, (Japanese translation of Artificial Intelligence: A Modern Approach, second edition.) Koichi Furukawa, translator. Tokyo: Kyoritsu Shuppan, 2008.
  23. Stuart Russell and Peter Norvig, ``Artificial Intelligence: A Modern Approach.'' 3rd Edition, Prentice Hall, 2010.
  24. Stuart Russell and Peter Norvig, Intelligence artificielle, 3e éd.. (French translation of Artificial Intelligence: A Modern Approach, third edition.) Paris: Pearson Education France, 2010.
  25. Stuart Russell and Peter Norvig, Intelligenza Artificiale 3/Ed. Vol. 1 - Un Approcio Moderno. (Vol. 1 of Italian translation of Artificial Intelligence: A Modern Approach, third edition.) Rome: Pearson Italia, 2010.
  26. Stuart Russell and Peter Norvig, Künstliche Intelligenz: Ein moderner Ansatz (3rd Edition). (German translation of Artificial Intelligence: A Modern Approach, third edition.) Munich: Verlag Pearson Studium, 2012.

Journal papers

  1. Stuart Russell ``Rationality as an Explanation of Language?'' (commentary). Behavioral and Brain Sciences 10, 1987.
  2. Stuart Russell and Eric Wefald ``Principles of Metareasoning.'' Artificial Intelligence 49, 1991 (invited paper).
  3. Stuart Russell ``An Architecture for Bounded Rationality.'' SIGART Bulletin 2(4), 1991.
  4. Stuart Russell ``Prior Knowledge and Autonomous Learning.'' Journal of Robotics and Autonomous Systems 8, 1991.
  5. Stuart Russell ``Inductive Learning by Machines.'' Philosophical Studies 64(1), 1991.
  6. Stuart Russell and Devika Subramanian ``Provably bounded-optimal agents.'' Journal of Artificial Intelligence Research, 2, 1995 (invited paper).
  7. Shlomo Zilberstein and Stuart Russell ``Optimal composition of real-time systems.'' Artificial Intelligence, 82, 181--213, 1996.
  8. Stuart Russell, ``Rationality and Intelligence.'' Artificial Intelligence, 94, 57--77, 1997 (invited paper).
  9. John Binder, Daphne Koller, Stuart Russell, Keiji Kanazawa, ``Adaptive Probabilistic Networks with Hidden variables.'' Machine Learning, 29, 213--244, 1997 (invited paper).
  10. Stuart Russell, Lewis Stiller, and Othar Hansson, ``PNPACK: Computing with Probabilities in Java.'' Concurrency: Practice and Experience, 9, 1333--1339, 1997.
  11. Prasad Tadepalli and Stuart Russell, ``Learning from Examples and Membership Queries with Structured Determinations.'' Machine Learning, 32, 245--95, 1998.
  12. Tim Huang and Stuart Russell, ``Object Identification: A Bayesian Analysis with Application to Traffic Surveillance.'' Artificial Intelligence, 103, 1-17, 1998 (invited paper).
  13. Geoffrey Zweig and Stuart Russell, ``Probabilistic modeling with Bayesian networks for automatic speech recognition.'' Australian Journal of Intelligent Information Processing Systems, 5(4), 253-60, 1999 (invited paper).
  14. Songhwai Oh, Stuart Russell, and S. Shankar Sastry, ``Markov Chain Monte Carlo Data Association for Multi-Target Tracking.'' IEEE Transactions on Automatic Control, 54(3), 481-497, 2009.
  15. Ahilan Sivaganesan, Yusuf Erol, Geoffrey Manley, and Stuart Russell, ``Modeling and Machine Learning of Cerebrovascular Dynamics: A Framework for Monitoring Unmeasurable Patient Variables.'' Neurosurgery, 71(2), E559, 2012.
  16. Nimar S. Arora, Stuart Russell, and Erik Sudderth, ``NET-VISA: Network Processing Vertically Integrated Seismic Analysis.'' In Bulletin of the Seismological Society of America, 103(2A), 709-729, 2013.

Refereed conference papers in published proceedings

  1. Stuart Russell ``A Quantitative Analysis of Analogy by Similarity.'' In Proceedings of the Fifth National Conference on Artificial Intelligence, Philadelphia, PA: Morgan Kaufmann, 1986.
  2. Stuart Russell ``Preliminary Steps Toward the Automation of Induction.'' In Proceedings of the Fifth National Conference on Artificial Intelligence, Philadelphia, PA: Morgan Kaufmann, 1986.
  3. Stuart Russell ``Analogy and Single-Instance Generalization.'' In Proceedings of the Fourth International Machine Learning Workshop, Irvine, CA: Morgan Kaufmann, 1987.
  4. Todd R. Davies and Stuart Russell ``A Logical Approach to Reasoning by Analogy.'' In Proceedings of the Tenth International Joint Conference on Artificial Intelligence, Milan, Italy: Morgan Kaufmann, 1987.
  5. Stuart Russell and Benjamin Grosof ``A Declarative Approach to Bias in Concept Learning.'' In Proceedings of the Sixth National Conference on Artificial Intelligence, Seattle, WA: Morgan Kaufmann, 1987.
  6. Michael Braverman and Stuart Russell ``Boundaries of Operationality.'' In Proceedings of the Fifth International Conference on Machine Learning, Ann Arbor, MI: Morgan Kaufmann, 1989.
  7. Michael Braverman and Stuart Russell ``IMEX: Overcoming Intractability in Explanation-Based Learning.'' In Proceedings of the Seventh National Conference on Artificial Intelligence, Minneapolis, MN: Morgan Kaufmann, 1988.
  8. Stuart Russell ``Tree-Structured Bias.'' In Proceedings of the Seventh National Conference on Artificial Intelligence, Minneapolis, MN: Morgan Kaufmann, 1988.
  9. Alice Agogino, Ramanathan Guha and Stuart Russell ``Sensor Fusion using Influence Diagrams and Reasoning by Analogy: Application to Milling Machine Monitoring and Control.'' In Proceedings of the Third International Conference on Applications of Artificial Intelligence in Engineering, Stanford, CA: Computational Mechanics Institute, 1988.
  10. Stuart Russell and Eric Wefald ``Principles of Meta-Reasoning.'' In Proceedings of the First International Conference on Principles of Knowledge Representation and Reasoning, Toronto, Ontario: Morgan Kaufmann, 1989.
  11. Stuart J. Russell ``Execution architectures and compilation.'' In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, Detroit, MI: Morgan Kaufmann, 1989.
  12. Stuart Russell and Eric Wefald ``On optimal game-tree search using rational metareasoning.'' In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, Detroit, MI: Morgan Kaufmann, 1989.
  13. Eric Wefald and Stuart Russell ``Adaptive Learning of Decision-Theoretic Search Control Knowledge.'' In Proceedings of the Sixth International Workshop on Machine Learning, Ithaca, NY: Morgan Kaufmann, 1989.
  14. Benjamin Grosof and Stuart Russell ``Declarative Bias for Structural Domains.'' In Proceedings of the Sixth International Workshop on Machine Learning, Ithaca, NY: Morgan Kaufmann, 1989.
  15. Sampath Srinivas, Stuart Russell, and Alice Agogino, ``Automated construction of sparse Bayesian networks from unstructured probabilistic models and domain information.'' In Proceedings of the Fifth Workshop on Uncertainty in Artificial Intelligence, Windsor, Ontario, 1989.
  16. Stuart Russell ``Fine-grained decision-theoretic search control.'' In Proceedings of the Sixth Conference on Uncertainty in Artificial Intelligence, Cambridge, MA: Morgan Kaufmann, 1990.
  17. Stuart Russell and Shlomo Zilberstein ``Composing Real-Time Systems.'' In Proceedings of the Twelfth International Joint Conference on Artificial Intelligence, Sydney, Australia: Morgan Kaufmann, 1991.
  18. Shlomo Zilberstein and Stuart Russell ``Efficient Resource-Bounded Reasoning in AT-RALPH.'' In Proceedings of the First International Conference on AI Planning Systems, College Park, Maryland: Morgan Kaufmann, 1992.
  19. Ronald Musick and Stuart Russell ``How Long Will It Take?'' In Proceedings of the Tenth National Conference on Artificial Intelligence, San Jose, CA: AAAI Press, 1992.
  20. Saso Dzeroski, Stephen Muggleton and Stuart Russell ``PAC-Learnability of Determinate Logic Programs.'' In Proceedings of the Fifth Annual ACM Workshop on Computational Learning Theory (COLT-92), Pittsburgh, PA: ACM Press, 1992.
  21. Stuart Russell ``Efficient Memory-Bounded Search Methods.'' In Proceedings of the Tenth European Conference on Artificial Intelligence, Vienna: Wiley, 1992.
  22. Saso Dzeroski, Stephen Muggleton and Stuart Russell ``PAC-Learnability of Constrained, Nonrecursive Logic Programs.'' In Proceedings of the Third International Workshop on Computational Learning Theory and Natural Learning Systems (CLNL-92), Madison, WI, 1992.
  23. Musick, R., Catlett, J. and Russell, S. ``An Efficient Method for Constructing Approximate Decision Trees for Large Databases.'' In Proceedings of the Tenth International Conference in Machine Learning, Amherst, MA, 1993.
  24. Gary Ogasawara and Stuart Russell ``Planning Using Multiple Execution Architectures.'' In Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, Chambery, France: Morgan Kaufmann, 1993.
  25. Stuart Russell and Devika Subramanian ``Provably bounded optimal agents.'' In Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, Chambery, France, 1993.
  26. S. Zilberstein and S. J. Russell. ``Anytime Sensing, Planning and Action: A Practical Model for Robot Control.'' In Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, Chambery, France, 1993.
  27. T. Huang, D. Koller, J. Malik, G. Ogasawara, B. Rao, S. Russell, and J. Weber. ``Automatic symbolic traffic scene analysis using belief networks.'' In Proceedings of the Twelfth National Conference on Artificial Intelligence, Seattle, WA, 1994.
  28. J. Tash and S. Russell ``Control strategies for a stochastic planner.'' In Proceedings of the Twelfth National Conference on Artificial Intelligence, Seattle, WA, 1994.
  29. D. Koller, J Weber, T. Huang, J. Malik, G. Ogasawara, B. Rao, and S. Russell, ``Towards Robust Automatic Traffic Scene Analysis in Real-Time.'' In Proceedings of the International Conference on Pattern Recognition, Israel, Nov. 1994.
  30. D. Koller, J Weber, T. Huang, J. Malik, G. Ogasawara, B. Rao, and S. Russell, ``Towards robust automatic traffic scene analysis in real-time.'' In Proceedings of the 33rd IEEE Conference on Decision and Control, Lake Buena Vista, Florida, Dec. 1994: IEEE Press.
  31. Stuart Russell, John Binder, Daphne Koller, and Keiji Kanazawa, ``Local learning in probabilistic networks with hidden variables.'' In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, Montreal, Canada, 1995.
  32. Ron Parr and Stuart Russell, ``Approximating Optimal Policies for Partially Observable Stochastic Domains.'' In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, Montreal, Canada, 1995.
  33. Jeff Forbes, Tim Huang, Keiji Kanazawa, and Stuart Russell, ``The BATmobile: Towards a Bayesian Automated Taxi.'' In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, Montreal, Canada, 1995.
  34. Stuart Russell, ``Rationality and Intelligence.'' Invited paper (Computers and Thought Award), in Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, Montreal, Canada, 1995.
  35. Keiji Kanazawa, Daphne Koller, and Stuart Russell, ``Stochastic simulation algorithms for dynamic probabilistic networks.'' In Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, Montreal, Canada: Morgan Kaufmann, 1995.
  36. M. Wellman, C. Liu, D. Pynadath, S. Russell, J. Forbes, T. Huang, and K. Kanazawa. ``Decision-Theoretic Reasoning for Traffic Monitoring and Vehicle Control.'' In Proceedings of the Intelligent Vehicles '95 Symposium, Detroit, Michigan, September 1995.
  37. Timothy Huang and Stuart Russell, ``Object identification in a Bayesian context.'' Distinguished Paper Prize, in Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, Nagoya, Japan, 1997.
  38. John Binder, Kevin Murphy, Stuart Russell, ``Space-Efficient Inference in Dynamic Probabilistic Networks.'' In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, Nagoya, Japan, 1997.
  39. Nir Friedman, Moises Goldszmidt, David Heckerman, Stuart Russell, ``Where is the Impact of Bayesian Networks in Learning?'' In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, Nagoya, Japan, 1997.
  40. Nir Friedman and Stuart Russell, ``Image Segmentation in Video Sequences.'' In Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, Providence, Rhode Island: Morgan Kaufmann, 1997.
  41. Ron Parr and Stuart Russell, ``Reinforcement Learning with Hierarchies of Machines.'' In Advances in Neural Information Processing Systems 10, MIT Press, 1998.
  42. Nir Friedman, Kevin Murphy, and Stuart Russell, ``Learning the Structure of Dynamic Probabilistic Networks.'' In Proceedings of the Conference on Automated Learning and Discovery, Pittsburgh, June 1998.
  43. Geoff Zweig and Stuart Russell, ``Speech Recognition with Dynamic Bayesian Networks.'' In Proceedings of the Fifteenth National Conference on Artificial Intelligence, Madison, Wisconsin: AAAI Press, 1998.
  44. R. Dearden, N. Friedman, and S. Russell, ``Bayesian Q-Learning.'' In Proceedings of the Fifteenth National Conference on Artificial Intelligence, Madison, Wisconsin: AAAI Press, 1998.
  45. N. Friedman, K. Murphy, and S. Russell, ``Learning the Structure of Dynamic Probabilistic Networks.'' In Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, Madison, Wisconsin: Morgan Kaufmann, 1998.
  46. S. Russell, ``Learning agents for uncertain environments (extended abstract).'' Invited paper, in Proceedings of the Eleventh Annual ACM Workshop on Computational Learning Theory (COLT-98), Madison, Wisconsin: ACM Press, 1998.
  47. G. Zweig and S. Russell, ``Probabilistic Modeling with Bayesian Networks for ASR.'' In Proceedings of the International Conference on Spoken Language Processing, Sydney, Australia: IEEE Press, 1998.
  48. Andrew Y. Ng, Daishi Harada, and Stuart Russell, ``Policy invariance under reward transformations: Theory and application to reward shaping.'' In Proceedings of the Sixteenth International Conference on Machine Learning, Bled, Slovenia: Morgan Kaufmann, 1999.
  49. Vassilis Papavassiliou and Stuart Russell, ``Convergence of reinforcement learning with general function approximators.'' In Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, Stockholm: Morgan Kaufmann, 1999.
  50. Hanna Pasula, Stuart Russell, Michael Ostland, and Ya'acov Ritov, ``Tracking many objects with many sensors.'' In Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, Stockholm: Morgan Kaufmann, 1999.
  51. Stuart Russell, ``Expressive probability models for speech recognition and understanding.'' In Proc. International Workshop on Automatic Speech Recognition and Understanding (ASRU), Keystone, Colorado, 1999 (invited paper).
  52. Stuart Russell, ``Expressive probability models in science.'' In Proceedings of the Second International Conference on Discovery Science, Tokyo, Japan: Springer Verlag, 1999 (invited paper).
  53. Andrew Y. Ng and Stuart Russell, ``Algorithms for inverse reinforcement learning.'' In Proceedings of the Seventeenth International Conference on Machine Learning, Stanford, California: Morgan Kaufmann, 2000.
  54. Arnaud Doucet, Nando de Freitas, Kevin Murphy, and Stuart Russell, ``Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks.'' In Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence , Stanford, California: Morgan Kaufmann, 2000.
  55. David Andre and Stuart Russell, ``Programmable Reinforcement Learning Agents.'' In Advances in Neural Information Processing Systems 13, MIT Press, 2001.
  56. Nikunj Oza and Stuart Russell, ``Online Bagging and Boosting.'' In Eighth International Workshop on Artificial Intelligence and Statistics, Key West, Florida. 2001
  57. Nikunj Oza and Stuart Russell, ``Experimental Comparisons of Online and Batch Versions of Bagging and Boosting.'' In Proc. KDD-01, San Francisco, 2001.
  58. Stuart Russell, ``Identity uncertainty.'' In Proc. IFSA-01, Vancouver, 2001. (Invited paper)
  59. Joao de Freitas, Pedro Hoejen-Soerensen, Michael Jordan, and Stuart Russell, ``Variational MCMC.'' In Proc. UAI-01, Seattle, 2001.
  60. Hanna Pasula and Stuart Russell, ``Approximate inference for first-order probabilistic languages.'' In Proc. IJCAI-01, Seattle, 2001.
  61. Bhaskara Marthi, Hanna Pasula, Stuart Russell, Yuval Peres, ``Decayed MCMC Filtering.'' In Proc. UAI-02, Edmonton, Alberta: Morgan Kaufmann, 2002.
  62. David Andre and Stuart Russell, ``State Abstraction for Programmable Reinforcement Learning Agents.'' In Proc. AAAI-02, Edmonton, Alberta: AAAI Press, 2002.
  63. Eric P. Xing, Andrew Y. Ng, Michael I. Jordan, and Stuart Russell, ``Distance Metric Learning, with application to Clustering with side-information.'' In Advances in Neural Information Processing Systems 15, MIT Press, 2003.
  64. Hanna Pasula, Bhaskara Marthi, Brian Milch, Stuart Russell, and Ilya Shpitser, ``Identity Uncertainty and Citation Matching.'' In Advances in Neural Information Processing Systems 15, MIT Press, 2003.
  65. Eric P.Xing, Michael I. Jordan, Richard M. Karp, and Stuart Russell, ``A Hierarchical Bayesian Markovian Model for Motifs in Biopolymer Sequences.'' In Advances in Neural Information Processing Systems 15, MIT Press, 2003.
  66. Eyal Amir and Stuart Russell, ``Temporal Logical Filtering---Preliminary Results.'' In Proc. Common Sense 2003, Stanford, CA, 2003.
  67. Eyal Amir and Stuart Russell, ``Logical Filtering.'' In Proc. IJCAI-03, Acapulco, Mexico, 2003.
  68. Stuart Russell and Andrew Zimdars, ``Q-Decomposition for Reinforcement Learning Agents.'' In Proc. ICML-03, Washington, DC, 2003.
  69. Greg Lawrence, Noah Cowan, and Stuart Russell, ``Efficient Gradient Estimation for Motor Control Learning.'' In Proc. UAI-03, Acapulco, Mexico, 2003.
  70. Eric P. Xing, Michael I. Jordan, and Stuart Russell, ``A generalized mean field algorithm for variational inference in exponential families.'' In Proc. UAI-03, Acapulco, Mexico, 2003.
  71. Eric Xing, Michael Jordan, and Stuart Russell, ``Graph partition strategies for generalized mean field inference.'' In Proc. UAI-04, Banff, Alberta, 2004.
  72. Songhwai Oh, Stuart Russell, and Shankar Sastry, ``Markov Chain Monte Carlo Data Association for General Multiple Target Tracking Problems.'' In Proc. 43rd IEEE Conference on Decision and Control (CDC-04), Paradise Island, Bahamas, 2004.
  73. Brian Milch, Bhaskara Marthi, David Sontag, Stuart Russell, Daniel L. Ong and Andrey Kolobov, ``Approximate Inference for Infinite Contingent Bayesian Networks.'' In Proc. Tenth International Workshop on Artificial Intelligence and Statistics, Barbados, 2005.
  74. Brian Milch, Bhaskara Marthi, David Sontag, Stuart Russell, Daniel L. Ong and Andrey Kolobov, ``BLOG: Probabilistic Models with Unknown Objects.'' In Proc. IJCAI-05, Edinburgh, Scotland, 2005.
  75. Stuart Russell and Jason Wolfe, ``Efficient belief-state AND-OR search, with application to Kriegspiel.'' In Proc. IJCAI-05, Edinburgh, Scotland, 2005.
  76. Bhaskara Marthi, Stuart Russell, David Latham, and Carlos Guestrin, ``Concurrent hierarchical reinforcement learning.'' In Proc. IJCAI-05, Edinburgh, Scotland, 2005.
  77. Brian Milch and Stuart Russell, ``General-Purpose MCMC Inference over Relational Structures.'' In Proc. UAI-06, Cambridge, MA, 2006.
  78. Bhaskara Marthi and Stuart Russell, ``A Compact, Hierarchical Q-Function Decomposition.'' In Proc. UAI-06, Cambridge, MA, 2006.
  79. T. K. Satish Kumar and Stuart Russell, ``On Some Tractable Cases of Logical Filtering.'' In Proceedings of the Sixteenth International Conference on Automated Planning and Scheduling (ICAPS 2006), Ambleside, UK, 2006.
  80. Brian Milch and Stuart Russell, ``First-Order Probabilistic Languages: Into the Unknown.'' In ILP: Proceedings of the 16th International Conference on Inductive Logic Programming. Berlin: Springer, 2007.
  81. B. Marthi, S. J. Russell, and J. Wolfe, ``Angelic Semantics for High-Level Actions.'' In Proceedings of the Seventeenth International Conference on Automated Planning and Scheduling (ICAPS 2007), Providence, Rhode Island, 2007.
  82. Gregory Lawrence and Stuart Russell, ``Improving Gradient Estimation by Incorporating Sensor Data.'' In Proceedings of the 24th International Conference on Uncertainty in Artificial Intelligence (UAI-08), Helsinki, 2008.
  83. Bhaskara Marthi, Stuart Russell, and Jason Wolfe, ``Angelic Hierarchical Planning: Optimal and Online Algorithms.'' In Proceedings of the Eighteenth International Conference on Automated Planning and Scheduling (ICAPS 2008), Sydney, 2008.
  84. Norm Aleks, Stuart Russell, Michael G. Madden, Kristan Staudenmayer, Mitchell Cohen, Diane Morabito, and Geoffrey Manley, ``Probabilistic detection of short events, with application to critical care monitoring.'' In Advances in Neural Information Processing Systems 21, MIT Press, 2009.
  85. Emma Brunskill and Stuart Russell, ``RAPID: A Reachable Anytime Planner for Imprecisely-sensed Domains.'' In Proc. 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010), Catalina Island, California, 2010.
  86. Nimar Arora, Stuart Russell, Rodrigo de Salvo Braz, and Erik Sudderth, ``Gibbs sampling in open-universe stochastic languages.'' In Proc. 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010), Catalina Island, California, 2010.
  87. Shaunak Chatterjee and Stuart Russell, ``Why are DBNs sparse?.'' In Proc. Thirteenth International Conference on Artificial Intelligence and Statistics, Sardinia, 2010.
  88. Ronan Le Bras, Sheila Vaidya, Jeffrey Schneider, Stuart Russell, and Nimar Arora, ``Status of the Machine Learning Efforts at the International Data Centre of the CTBTO.'' In Proc. Monitoring Research Review (MRR 2010), Orlando, Florida, 2010.
  89. Jason Wolfe, Bhaskara Marthi, and Stuart Russell, ``Combined Task and Motion Planning for Mobile Manipulation.'' In Proceedings of the Twentieth International Conference on Automated Planning and Scheduling (ICAPS 2010), Toronto, 2010.
  90. Nimar S. Arora, Stuart J. Russell, Paul Kidwell, and Erik Sudderth, ``Global seismic monitoring as probabilistic inference.'' In Advances in Neural Information Processing Systems 23, MIT Press, 2011.
  91. Ronan Le Bras, Stuart Russell, Nimar Arora, and Vera Miljanovic, ``Machine Learning at the CTBTO. Testing and evaluation of the False Events Identification (FEI) and Vertically Integrated Seismic Association (VISA) project.'' In Proc. Monitoring Research Review (MRR 2011), Tucson, Arizona, 2011.
  92. Stuart J. Russell, Stephen C. Myers, Nimar S. Arora, David A. Moore, and Erik Sudderth, ``Bayesian Treaty Monitoring: Preliminary Report.'' In Proc. Monitoring Research Review (MRR 2011), Tucson, Arizona, 2011.
  93. Shaunak Chatterjee and Stuart Russell, ``A temporally abstracted Viterbi algorithm.'' In Proc. UAI-11, Barcelona, 2011.
  94. Nimar S. Arora, Stuart J. Russell, Paul Kidwell, and Erik Sudderth, ``Global seismic monitoring: A Bayesian approach.'' In Proc. AAAI-11, San Francisco, 2011.
  95. Jason Wolfe and Stuart Russell, ``Bounded Intention Planning.'' In Proc. IJCAI-11, Barcelona, 2011.
  96. Emma Brunskill and Stuart Russell, ``Partially observable sequential decision making for problem selection in an intelligent tutoring system.'' In Proc. International Conference on Educational Data Mining (EDM), 2011.
  97. Nicholas Hay, Stuart Russell, Solomon Eyal Shimony, and David Tolpin, ``Selecting Computations: Theory and Applications.'' In Proc. UAI-12, Catalina Island, 2012.
  98. Shaunak Chatterjee and Stuart Russell, ``Uncertain observation times.'' In Proc. 6th International Conference on Scalable Uncertainty Management (SUM-12), Marburg, Germany, 2012.
  99. David A. Moore, Kevin Mayeda, Steve Myers, Min Joon Seo, and Stuart Russell, ``Progress in Signal-Based Bayesian Monitoring.'' In Proc. Monitoring Research Review (MRR 2012), Albuquerque, New Mexico, 2012.
  100. Nimar S. Arora, Jeffrey Given, Elena Tomuta, Stuart Russell, and Spilios Spiliopoulos, ``Analyst Evaluation of NET-VISA (Network Processing Vertically Integrated Seismic Analysis) at the CTBTO.'' In Proc. Monitoring Research Review (MRR 2012), Albuquerque, New Mexico, 2012.
  101. Lei Li, Bharath Ramsundar, and Stuart Russell, ``Dynamic Scaled Sampling for Deterministic Constraints.'' In Proc. Sixteenth International Conference on Artificial Intelligence and Statistics, Scottsdale, Arizona, 2013.
  102. Yusuf B. Erol, Lei Li, Bharath Ramsundar, and Stuart Russell, ``The Extended Parameter Filter.'' In Proc. Thirtieth International Conference on Machine Learning, Atlanta, 2013.
  103. Sharad Vikram, Lei Li, and Stuart J. Russell, ``Writing and sketching in the air, recognizing and controlling on the fly.'' In CHI Extended Abstracts, Paris, 2013.
  104. Mark Rogers, Lei Li, and Stuart Russell, ``Multilinear Dynamical Systems for Tensor Time Series.'' In Advances in Neural Information Processing Systems 23, MIT Press, 2014.
  105. Siddharth Srivastava, Eugene Fang, Lorenzo Riano, Rohan Chitnis, Stuart Russell, and Pieter Abbeel, ``Combined Task and Motion Planning Through an Extensible Planner-Independent Interface Layer.'' In Proc. ICRA-14, Hong Kong, 2014.
  106. Siddharth Srivastava, Stuart Russell, and Paul Ruan, ``First-Order Open-Universe POMDPs.'' In Proc. UAI-14, Quebec City, Canada, 2014.
  107. David Moore and Stuart Russell, ``Fast Gaussian Process Posteriors with Product Trees.'' In Proc. UAI-14, Quebec City, Canada, 2014.
  108. Stuart Russell, ``Unifying Logic and Probability: A New Dawn for AI?'' (Invited paper.) In Proc. IPMU-14, Montpellier, France, 2014.

Refereed conference papers

  1. Stuart Russell and Eric Wefald ``Multi-Level Decision-Theoretic Search.'' In Proceedings of the AAAI Symposium on Computer Game-Playing, Stanford, March, 1988.
  2. Michael Braverman and Stuart Russell ``Explanation-Based Learning in Complex Domains.'' In Proceedings of the AAAI Symposium on Explanation-Based Learning, Stanford, March, 1988.
  3. Stuart Russell and Devika Subramanian ``Mutual Constraints on Representation and Inference.'' In Proceedings of the International Workshop on Machine Learning, Meta-Reasoning and Logics, Sesimbra, Portugal, 1988.
  4. Stuart Russell and Benjamin Grosof ``A Sketch of Autonomous Learning using Declarative Bias.'' In Proceedings of the International Workshop on Machine Learning, Meta-Reasoning and Logics, Sesimbra, Portugal, 1988.
  5. Benjamin Grosof and Stuart Russell ``Shift of Bias as Nonmonotonic Reasoning.'' In Proceedings of the International Workshop on Machine Learning, Meta-Reasoning and Logics, Sesimbra, Portugal, 1988.
  6. Eric Wefald and Stuart Russell, ``Estimating the value of computation: The case of real-time search.'' In Proceedings of the AAAI Symposium on AI and Limited Rationality, Stanford, March, 1989.
  7. Othar Hansson, Andrew Mayer, and Stuart Russell, ``Decision-theoretic planning in BPS.'' In Proceedings of the AAAI Symposium on Planning in Uncertain Environments, Stanford, March, 1990.
  8. Stuart Russell ``An Architecture for Bounded Rationality.'' In Proceedings of the AAAI Symposium on Integrated Architectures for Intelligent Agents, Stanford, March, 1991.
  9. Stuart Russell ``An Architecture for Bounded Rationality.'' In Proceedings of the IJCAI Workshop on Theoretical and Practical Design of Rational Agents, Sydney, August, 1991.
  10. Shlomo Zilberstein and Stuart Russell ``Reasoning about optimal allocation of time using conditional performance profiles.'' In Proceedings of the AAAI-92 Workshop on Implementations of Temporal Reasoning, San Jose, CA, July, 1992.
  11. Shlomo Zilberstein and Stuart Russell ``Control of Mobile Robots Using Anytime Computation.'' In Proceedings of the AAAI Fall Symposium on Applications of Artificial Intelligence to Real-World Autonomous Mobile Robots, Cambridge, MA, October, 1992.
  12. Shlomo Zilberstein and Stuart Russell ``Constructing utility-driven real-time systems using anytime algorithms.'' Proceedings of the IEEE Workshop on Imprecise and Approximate Computation, Phoenix, AZ, December, 1992.
  13. Gary Ogasawara and Stuart Russell ``Decision-theoretic planning with multiple execution architectures.'' Proceedings of the AAAI Spring Symposium on AI Planning, Stanford, CA, March 1993.
  14. Stuart Russell and Devika Subramanian ``Constructing bounded optimal systems.'' In Proceedings of the AAAI Spring Symposium on AI and NP-hard problems, Stanford, CA, March 1993.
  15. Brenda Barbour and Stuart Russell ``Experiments in Adaptive Indexing for Logic Programming.'' In Proceedings of the ICML-93 Workshop on Knowledge Compilation and Speedup Learning, Amherst, MA, June 1993.
  16. Tim Huang, Gary Ogasawara, and Stuart Russell ``Symbolic Traffic Scene Analysis Using Belief Networks.'' In Proceedings of the AAAI Workshop on AI in Intelligent Vehicle and Highway Systems, Washington, DC, 1993.
  17. Scott Davies and Stuart Russell, ``NP-completeness of searches for smallest possible feature sets.'' In Proceedings of the AAAI Fall Symposium on Relevance, New Orleans, Nov. 1994.
  18. Stuart Russell and Peter Norvig, ``A Modern, Agent-Oriented Approach to AI Instruction.'' In Proceedings of the AAAI Fall Symposium on Innovative Instruction for Introductory AI, New Orleans, Nov. 1994.
  19. Daishi Harada and Stuart Russell, ``Extended abstract: Learning search strategies.'' In Proceedings of the AAAI Spring Symposium on Search Techniques for Problem Solving under Uncertainty and Incomplete Information, Stanford, CA, 1999.
  20. Michael Shilman, Hanna Pasula, Stuart Russell, and Richard Newton, ``Statistical Visual Language Models for Ink Parsing.'' In Proc. AAAI Spring Symposium on Sketch Understanding, Stanford, March 2002.
  21. Bhaskara Marthi, Brian Milch, and Stuart Russell, ``First-Order Probabilistic Models for Information Extraction.'' In Proc. IJCAI-03 Workshop on Learning Statistical Models from Relational Data, Acapulco, Mexico, 2003.
  22. Brian Milch, Bhaskara Marthi, and Stuart Russell, ``BLOG: Relational Modeling with Unknown Objects.'' In Proc. ICML-04 Workshop on Statistical Relational Learning, Banff, Canada, 2004.
  23. Bhaskara Marthi, David Latham, Carlos Guestrin, Stuart Russell, ``Concurrent Hierarchical Reinforcement Learning.'' In Proc. AAAI-04 Workshop on Learning and Planning in Markov Processes, San Jose, 2004.
  24. Bhaskara Marthi, Stuart Russell, and David Latham, ``Writing Stratagus-Playing Agents in Concurrent ALisp.'' In Proc. IJCAI-05 Workshop on Reasoning, Representation, and Learning in Computer Games, Edinburgh, Scotland, 2005.
  25. Jason Wolfe and Stuart Russell, ``Exploiting Belief State Structure in Graph Search.'' In Proceedings of the ICAPS 2007 Workshop on Planning in Games, Providence, Rhode Island, 2007.
  26. Norm Aleks, Stuart Russell, Michael G. Madden, Diane Morabito, Geoffrey Manley, Kristan Staudenmayer, and Mitchell Cohen, ``Probabilistic modeling of sensor artifacts in critical care,'' In Proc. ICML-08 Workshop on Machine Learning in Health Care Applications, Helsinki, 2008.
  27. Rodrigo de Salvo Braz, Sriram Natarajan, Hung Bui, Jude Shavlik, and Stuart Russell, ``Anytime Lifted Belief Propagation,'' In Proc. SRL-2009, the International Workshop on Statistical Relational Learning, Leuven, Belgium, 2009.
  28. Siddharth Srivastava and Stuart Russell, ``First-Order Models for POMDPs.'' In Proc. 2nd International Workshop on Statistical Relational AI (StarAI-12), Catalina Island, 2012.
  29. Siddharth Srivastava, Lorenzo Riano, Stuart Russell, and Pieter Abbeel, ``Using Classical Planners for Tasks with Continuous Operators in Robotics.'' In ICAPS-13 Workshop on Planning and Robotics, Rome, 2013.

Book chapters

  1. Stuart Russell ``Analogy by Similarity.'' In David Helman (Ed.), Analogical Reasoning, Boston, MA: D. Reidel, 1988.
  2. Stuart Russell and Benjamin Grosof ``Declarative Bias: An Overview.'' In Benjamin, P. (Ed.) Change of Representation and Inductive Bias, Dordrecht: Kluwer Academic Publishers, 1989.
  3. Stuart Russell and Devika Subramanian ``Mutual Constraints on Representation and Inference.'' In Brazdil, P., and Konolige, K. (Eds.) Machine Learning, Meta-Reasoning and Logics. Dordrecht: Kluwer Academic Publishers, 1990.
  4. Stuart Russell and Benjamin Grosof ``A Sketch of Autonomous Learning using Declarative Bias.'' In Brazdil, P., and Konolige, K. (Eds.) Machine Learning, Meta-Reasoning and Logics. Dordrecht: Kluwer Academic Publishers, 1990.
  5. Benjamin Grosof and Stuart Russell ``Shift of Bias as Nonmonotonic Reasoning.'' In Brazdil, P., and Konolige, K. (Eds.) Machine Learning, Meta-Reasoning and Logics. Dordrecht: Kluwer Academic Publishers, 1990.
  6. Stuart Russell ``Prior Knowledge and Autonomous Learning.'' In Maes, P. and van der Velde, W. (Eds.) Representation and Learning in an Autonomous Agent. Cambridge, MA: MIT Press, 1990.
  7. Sampath Srinivas, Stuart Russell, and Alice Agogino, ``Automated construction of sparse Bayesian networks from unstructured probabilistic models and domain information.'' In M. Henrion, R. D. Shachter, L. N. Kanal, and J. F. Lemmer (Eds.) Uncertainty in Artificial Intelligence 5. Amsterdam: North Holland, 1990.
  8. Todd R. Davies and Stuart Russell ``A Logical Approach to Reasoning by Analogy.'' In T. Dietterich (Ed.) Readings in Machine Learning. San Mateo, CA: Morgan Kaufmann, 1990.
  9. Stuart Russell and Devika Subramanian ``On Provably RALPHs.'' In E. Baum (Ed.) Computational Learning and Cognition: Proceedings of the Third NEC Research Symposium. SIAM Press, 1993.
  10. Saso Dzeroski, Stephen Muggleton and Stuart Russell ``PAC-Learnability of Constrained, Nonrecursive Logic Programs.'' In T. Petsche, S. Hanson, and J. Shavlik (Eds.), Computational Learning Theory and Natural Learning Systems, Volume III: Selecting Good Models, MIT Press, 1995.
  11. Shlomo Zilberstein and Stuart Russell, ``Approximate reasoning using anytime algorithms.'' In S. Natarajan (Ed.) Imprecise and Approximate Computation, Kluwer Academic Publishers, Dordrecht, 1995.
  12. Stuart Russell, ``Machine Learning.'' Chapter 4 of M. A. Boden (Ed.), Artificial Intelligence, Academic Press, 1996. Part of the Handbook of Perception and Cognition.
  13. Michael Jordan and Stuart Russell, ``Computational Intelligence.'' In The MIT Encyclopedia of the Cognitive Sciences, MIT Press, 1999.
  14. Stuart Russell, ``Metareasoning.'' In The MIT Encyclopedia of the Cognitive Sciences, MIT Press, 1999.
  15. Kevin Murphy and Stuart Russell, ``Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks.'' In Sequential Monte Carlo Methods in Practice, A. Doucet, N. de Freitas and N.J. Gordon (eds), Springer-Verlag, 2001.
  16. Stuart Russell, ``Rationality and Intelligence.'' In Renee Elio (Ed.), Common sense, reasoning, and rationality, Oxford University Press, 2002.
  17. Judea Pearl and Stuart Russell, ``Bayesian Networks.'' In Michael A. Arbib, Ed., The Handbook of Brain Theory and Neural Networks, 2nd edition, MIT Press, 2003.
  18. Brian Milch, Bhaskara Marthi, Stuart Russell, David Sontag, Daniel L. Ong and Andrey Kolobov, ``BLOG: Probabilistic Models with Unknown Objects.'' In L. Getoor and B. Taskar, Eds., Introduction to Statistical Relational Learning. Cambridge, MA: MIT Press, 2007.
  19. Brian Milch and Stuart Russell, ``Extending Bayesian Networks to the Open-Universe Case.'' In Rina Dechter, Hector Geffner, and Joseph Y Halpern, Eds., Heuristics, Probability and Causality. A Tribute to Judea Pearl. College Publications, 2010.
  20. J. Claude Hemphill III, Marco D. Sorani, Stuart Russell, and Geoffrey T. Manley, ``Medical informatics.'' In P. D. Le Roux, J. M. Levine, and W. A. Kofke (Eds.), Monitoring in Neurocritical Care. Philadelphia: Elsevier, 2010.
  21. Stuart Russell, ``Rationality and Intelligence: A Brief Update.'' In Vincent C. Müller (ed.), Fundamental Issues of Artificial Intelligence (Synthese Library). Berlin: Springe, 2014.

Technical reports, non-refereed conference papers, magazine articles

  1. Stuart Russell The Compleat Guide to MRS. Stanford University Computer Science Department Report No. STAN-CS-85-1080; June 1985 126pp. Also published as Stanford Knowledge Systems Laboratory Report No. KSL-85-12.
  2. Todd R. Davies and Stuart Russell A Logical Approach to Reasoning by Analogy. SRI AI Center Technical Note 385; 1986.
  3. Stuart Russell Analogical and Inductive Reasoning. Ph. D. Thesis, Stanford University Department of Computer Science, December 1986. Also appeared as Stanford University Computer Science Department Technical Report STAN-CS-87-1150.
  4. Stuart Russell and Eric Wefald, Decision-Theoretic Search Control: General Theory and an Application to Game-Playing, Computer Science Division Technical Report 88/435, University of California, Berkeley, CA, 1988.
  5. Alice Agogino, Ramanathan Guha and Stuart Russell ``Sensor Fusion using Influence Diagrams and Reasoning by Analogy: Application to Milling Machine Monitoring and Control.'' Working paper 88-0304-P, Department of Mechanical Engineering, University of California, Berkeley, CA, 1988.
  6. Stuart Russell and Benjamin Grosof ``A Sketch of Autonomous Learning using Declarative Bias.'' Research report no. RC 14613 (#64812), IBM Research Division, 1989.
  7. Benjamin Grosof and Stuart Russell ``Shift of Bias as Nonmonotonic Reasoning.'' Research report no. RC 14614 (#65293), IBM Research Division, 1989.
  8. Benjamin Grosof and Stuart Russell ``Declarative Bias for Structural Domains.'' Research report no. RC 14620 (#64608), IBM Research Division, 1989.
  9. Ann Nicholson and Stuart Russell, ``Techniques for Handling Inference Complexity in Dynamic Belief Networks.'' Technical report no. CS-93-31, Computer Science Department, Brown University, 1993.
  10. Stuart Russell, John Binder, and Daphne Koller, ``Adaptive probabilistic networks.'' Technical report UCB//CSD-94-824, July 24, 1994.
  11. Jeff Forbes, Tim Huang, Keiji Kanazawa, and Stuart Russell, ``The BATmobile: Towards a Bayesian Automated Taxi.'' In SAE Future Transportation Technology Conference, Costa Mesa, CA, August, 1995.
  12. Jitendra Malik, Stuart Russell. ``Traffic Surveillance and Detection Technology Development: New Traffic Sensor Technology Final Report.'' California PATH Research Report UCB-ITS-PRR-97-6, Institute of Transportation Studies, University of California, Berkeley. January 1997.
  13. Simon Kasif and Stuart Russell (Eds.), Proceedings of the AAAI Fall Symposium on Learning Complex Behaviours, Cambridge, Massachusetts: AAAI Press.
  14. Jeffrey Forbes, Nikunj Oza, Ronald Parr, and Stuart Russell. ``Feasibility Study of Fully Automated Traffic Using Decision-Theoretic Control.'' California PATH Research Report UCB-ITS-PRR-97-18, Institute of Transportation Studies, University of California, Berkeley. April 1997.
  15. Geoffrey Zweig and Stuart Russell. ``Compositional Modeling with DPNs.'' Technical Report No. UCB-CSD-97-970, Computer Science Division, University of California, Berkeley. December 1997.
  16. Vassilis Papavassiliou and Stuart Russell, ``Value Determination with General Function Approximators.'' Technical Report CSD-98-1005, Computer Science Division, UC Berkeley, 1998.
  17. David Andre and Stuart Russell, ``State Abstraction for Programmable Reinforcement Learning Agents.'' Technical Report CSD-01-1156, Computer Science Division, UC Berkeley, 2001.
  18. Songhwai Oh, Stuart Russell, and Shankar Sastry, ``Markov Chain Monte Carlo Data Association for Multiple-Target Tracking,'' University of California, Berkeley, Technical Report UCB//ERL M05/19, June 2005.
  19. B. Marthi, S. J. Russell, and J. Wolfe, ``Angelic Semantics for High-Level Actions,'' Tech. Rep. UCB/EECS-2007-89, EECS Department, University of California, Berkeley, July 2007.
  20. Bhaskara Marthi, Stuart Russell, and Jason Wolfe, ``Angelic Hierarchical Planning: Optimal and Online Algorithms,'' Tech. Rep. UCB/EECS-2008-150, EECS Department, University of California, Berkeley, Dec 2008.
  21. Stuart Russell, Sheila Vaidya, ``Machine Learning and Data Mining for Comprehensive Test Ban Treaty Monitoring.'' Technical Report LLNL-TR-416780, Lawrence Livermore National Laboratory, 2009.
  22. Stuart Russell, Nimar Arora, Michael Jordan, and Erik Sudderth, "Vertically Integrated Seismological Analysis I: Modeling." Eos Transactions of the American Geophysical Union, 90(52), Fall Meeting Supplement, Abstract S33D-08, 2009.
  23. Nimar Arora, Stuart Russell, and Erik Sudderth, "Vertically Integrated Seismological Analysis II: Inference." Eos Transactions of the American Geophysical Union, 90(52), Fall Meeting Supplement, Abstract S31B-1713, 2009.
  24. Nimar S. Arora, Stuart J. Russell, Paul Kidwell, and Erik Sudderth, ``Global seismic monitoring as probabilistic inference.'' Technical Report No. UCB/EECS-2010-108, EECS Department, University of California, Berkeley, 2010.
  25. Stuart Russell, Sheila Vaidya, and Ronan Le Bras, ``Machine Learning for Comprehensive Nuclear-Test-Ban Treaty Monitoring.'' CTBTO Spectrum, 14, 32-35, 2010.
  26. Nicholas J. Hay and Stuart Russell, ``Metareasoning for Monte Carlo Tree Search.'' Technical Report No. UCB/EECS-2011-119, EECS Department, University of California, Berkeley, 2010.
  27. Nimar Arora, Tony Dear, and Stuart Russell, ``Scalable Probabilistic Inference for Global Seismic Monitoring.'' Eos Transactions of the American Geophysical Union, 92(53), Fall Meeting Supplement, Abstract S43B-2238, 2011.
  28. Nimar Arora and Stuart Russell, ``A model of seismic coda arrivals to suppress spurious events (abstract).'' In Proc. European Geophysical Union General Assembly, Vienna, 2012.
  29. Ahilan Sivaganesan, Yusuf Erol, Geoffrey Manley, and Stuart Russell, ``Modeling and Machine Learning of Cerebrovascular Dynamics: A Framework for Monitoring Unmeasurable Patient Variables (abstract).'' Congress of Neurological Surgeons Annual Meeting, Chicago, 2012.
  30. Nimar Arora and Stuart Russell, ``A model of seismic coda arrivals to suppress spurious events (abstract).'' In Proc. European Geophysical Union General Assembly, Vienna, 2012.
  31. Siddharth Srivastava, Xiang Cheng, Stuart J. Russell and Avi Pfeffer, ``First-Order Open-Universe POMDPs: Formulation and Algorithms.'' Technical Report No. UCB/2013-243, EECS Department, University of California, Berkeley, 2013.
  32. Stephen Hawking, Stuart Russell, Max Tegmark, and Frank Wilczek, ``Transcending Complacency on Superintelligent Machines.'' Huffington Post, April 19, 2014.
  33. Stuart Russell, ``Transcendence: An AI Researcher Enjoys Watching His Own Execution.'' Huffington Post, April 29, 2014.

Principal External Grants and Awards


Theses supervised

Ph.D. Theses
  1. desJardins, Marie PAGODA: A Model for Autonomous Learning in Probabilistic Domains. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 1992.
  2. Zilberstein, Shlomo Operational Rationality Through Compilation of Anytime Algorithms. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 1993.
  3. Ogasawara, Gary RALPH-MEA: A Real-Time, Decision-Theoretic Agent Architecture. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 1994.
  4. Musick, Charles Ronald Belief network induction. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 1994.
  5. Mayer, Andrew Rational Search. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 1994.
  6. Tash, Jonathan Decision Theory Made Tractable: The Value of Deliberation, with Applications to Markov Decision Process Planning. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 1996.
  7. Zweig, Geoff, Speech recognition using dynamic Bayesian networks. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 1998.
  8. Parr, Ronald, Solution methods for large Markov decision processes. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 1998.
  9. Hansson, Othar, Bayesian Problem-Solving Applied to Scheduling. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 1998.
  10. Huang, Timothy, Probabilistic Methods for Intelligent Transportation Systems. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 1999.
  11. Oza, Nikunj, Online Ensemble Learning. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 2001.
  12. Forbes, Jeffrey, Learning Optimal Control for Autonomous Vehicles. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 2002.
  13. Murphy, Kevin, Dynamic Bayesian Networks: Representation, Inference, and Learning. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 2002.
  14. Andre, David, State Abstraction for Programmable Reinforcement Learning Agents. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 2003.
  15. Pasula, Hanna, Identity Uncertainty. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 2003.
  16. Papavassiliou, Vassilis, Value Determination with Function Approximation. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 2003.
  17. Paskin, Mark, Exploiting Locality in Probabilistic Inference. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 2004.
  18. Xing, Eric, Probabilistic Graphical Models and Algorithms for Genomic Analysis. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 2004.
  19. Milch, Brian, Probabilistic Models with Unknown Objects. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 2006.
  20. Marthi, Bhaskara, Concurrent Hierarchical Reinforcement Learning. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 2006.
  21. Lawrence, Gregory, Efficient Gradient Estimation for Reinforcement Learning Algorithms. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 2009.
  22. Canini, Kevin, Nonparametric Bayesian Models of Categorization. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 2011.
  23. Wolfe, Jason, Optimal Hierarchical Planning. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 2011.
  24. Arora, Nimar, Model-based Bayesian Seismic Monitoring. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 2012.
  25. Chatterjee, Shaunak, Efficient inference algorithms for near-deterministic systems. PhD thesis, Computer Science Division, University of California, Berkeley, CA, 2013.

MS Theses

  1. Dutta, Soumitra Inductive Learning of Rules of Determination. MS report, Computer Science Division, University of California, Berkeley, CA, 1987.
  2. Guha, Ramanathan Induction and Analogy in Engineering Expert Systems. MS report, Mechanical Engineering Department, University of California, Berkeley, CA, 1987.
  3. Barbour, Brenda Experiments on Indexing Schemes for Logic Programming. MS report, Computer Science Division, University of California, Berkeley, CA, 1987.
  4. Sampath Srinivas Creating Influence Diagrams from Examples. MS report, Mechanical Engineering Department, University of California, Berkeley, CA, 1988.
  5. Wefald, Eric The Expected Value of Search: A Decision-Theoretic Framework for Game-Playing Algorithms. MS report, Computer Science Division, University of California, Berkeley, CA, 1988.
  6. Malone, Christopher Planning, Execution and Knowledge Compilation in Real-Time Agents. MS report, Computer Science Division, University of California, Berkeley, CA, 1988.
  7. Getoor, Lise Learning efficiently using declarative bias. MS report, Computer Science Division, University of California, Berkeley, CA, 1989.
  8. Ogasawara, Gary A Distributed Decision-Theoretic Control System for a Mobile Robot. MS report, Computer Science Division, University of California, Berkeley, CA, 1989.
  9. Koenig, Sven Optimal Probabilistic and Decision-Theoretic Planning using Markovian Decision Theory. MS report, Computer Science Division, University of California, Berkeley, CA, 1991.
  10. Sarkar, Sudeshna Constructive Induction for Situated Agents. MS report, Computer Science Division, University of California, Berkeley, CA, 1991.
  11. Conroy, Jeffrey Decision-Theoretic Control of Search in Probabilistic Domains. MS report, Computer Science Division, University of California, Berkeley, CA, 1991.
  12. Marx, Sonia Using tree-structured bias in training neural networks. MS report, Computer Science Division, University of California, Berkeley, CA, 1991.
  13. Glesner, Sabine Constructing flexible dynamic belief networks from first-order probabilistic knowledge bases. MS thesis, Computer Science Division, University of California, Berkeley, CA, 1994.
  14. Zweig, Geoff, A comparison between dynamic belief networks and hidden Markov models. MS thesis, Computer Science Division, University of California, Berkeley, CA, 1996.
  15. Braverman, Michael, Caste; A Class System for Tcl. MS thesis, Computer Science Division, University of California, Berkeley, CA, 1997.
  16. Oza, Nikunj, Probabilistic Models of Driver Behavior. MS thesis, Computer Science Division, University of California, Berkeley, CA, 1998.
  17. Zimdars, Andrew, Additive Value Function Decomposition for Reinforcement Learning Agents. MS thesis, Computer Science Division, University of California, Berkeley, CA, 2004.
  18. Pearson, Mark, Utility-Directed Sampling in Influence Diagrams. MS thesis, Computer Science Division, University of California, Berkeley, CA, 2006.
  19. Canini, Kevin, Modeling Categorization as a Dirichlet Process Mixture, MS thesis, Computer Science Division, University of California, Berkeley, CA, 2007.
  20. Duckworth, Daniel, Monte Carlo Methods for Multiple Target Tracking and Parameter Estimation, MS thesis, Computer Science Division, University of California, Berkeley, CA, 2012.

Consulting, short courses

Vice President, Bayesian Logic Inc., 2011-present
Technical Advisory Board, Kaplan Inc., 2009-2012
Consultant, UN Comprehensive Test Ban Treaty Organization, 2009-2011
Consultant, Ciphergen Inc., Bioinformatics, 2001-2005
Consultant, Ikuni Inc., AI for Computer Games, 2001-present
Short Course, Universita di Roma ``La Sapienza,'' Probabilistic Methods in AI, 1999
Consultant, Chiron Corporation, Probabilistic inference in drug design, 1996
Principal, Consumer Financial Service Corporation, Advanced data analysis techniques, 1995-present
Consultant, AT&T Bell Laboratories, Relating complexity theory to artificial intelligence, 1993
Consultant, NEC, Search and game-playing algorithms, 1992
Consultant, Shell International Trading Company, AI techniques for global oil market modelling, 1992
Short Course, Oxford University, Advanced Methods in Artificial Intelligence, 1991
Consultant, MCC, Austin, TX , Representation and inference in the Large Scale KB Project (CYC), 1986--89
Consultant, Reasoning Systems Inc., Palo Alto, VHLL compilers and program transformation methods, 1985