Stefano Ermon

Stefano Ermon    

Assistant Professor, Department of Computer Science
Fellow, Woods Institute for the Environment
Stanford University

Office: Gates Building #228
Phone: (650) 498-9942
Email: ermon AT cs.stanford.edu

Group Website       Research Blog

About Me

I am an Assistant Professor in the Department of Computer Science at Stanford University, where I am affiliated with the Artificial Intelligence Laboratory and a fellow of the Woods Institute for the Environment.

My research is centered on techniques for scalable and accurate inference in graphical models, statistical modeling of data, large-scale combinatorial optimization, and robust decision making under uncertainty, and is motivated by a range of applications, in particular ones in the emerging field of computational sustainability.

Teaching

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Publications

2018

2017

2016

2015

More Publications

2014

  • Stefano Ermon, Carla Gomes, Ashish Sabharwal, and Bart Selman
    Designing Fast Absorbing Markov Chains [PDF]
    AAAI-14. In Proc. 28th AAAI Conference on Artificial Intelligence, July 2014.
  • Stefano Ermon, Carla Gomes, Ashish Sabharwal, and Bart Selman
    Low-density Parity Constraints for Hashing-Based Discrete Integration [PDF] [Code]
    ICML-14. In Proc. 31st International Conference on Machine Learning, June 2014.

2013

  • Stefano Ermon, Carla Gomes, Ashish Sabharwal, and Bart Selman
    Embed and Project: Discrete Sampling with Universal Hashing [PDF] [Code]
    NIPS-13. In Proc. 27th Annual Conference on Neural Information Processing Systems, December 2013.
  • Stefano Ermon, Carla Gomes, Ashish Sabharwal, and Bart Selman
    Optimization With Parity Constraints: From Binary Codes to Discrete Integration [PDF] [Slides] [Poster] [Code]
    UAI-13. In Proc. 29th Conference on Uncertainty in Artificial Intelligence, July 2013.
    Best Student Paper Award. Best Paper Award Runner-up.
  • Stefano Ermon, Yexiang Xue, Carla Gomes, and Bart Selman.
    Learning Policies For Battery Usage Optimization in Electric Vehicles.
    Machine Learning. In Machine Learning: Volume 92, Issue 1, Page 177-194, 2013.
  • Stefano Ermon, Carla Gomes, Ashish Sabharwal, and Bart Selman
    Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization [PDF] [Slides] [Code]
    ICML-13. In Proc. 30th International Conference on Machine Learning, June 2013.

2012

  • Stefano Ermon, Carla Gomes, Ashish Sabharwal, and Bart Selman
    Density Propagation and Improved Bounds on the Partition Function. [PDF] [Poster]
    NIPS-12. In Proc. 26th Annual Conference on Neural Information Processing Systems, December 2012.
  • Stefano Ermon, Carla Gomes, and Bart Selman
    Uniform Solution Sampling Using a Constraint Solver As an Oracle [PDF] [Slides] [Code]
    UAI-12. In Proc. 28th Conference on Uncertainty in Artificial Intelligence, August 2012.
  • Liaoruo Wang, Stefano Ermon, and John Hopcroft
    Feature-Enhanced Probabilistic Models for Diffusion Network Inference. [PDF] [Slides] [Code]
    ECML-PKDD-12. In Proc. of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, September 2012.
  • Stefano Ermon, Yexiang Xue, Carla Gomes, and Bart Selman
    Learning Policies For Battery Usage Optimization in Electric Vehicles [PDF] [Slides] [Dataset]
    ECML-PKDD-12. In Proc. of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, September 2012.
  • Stefano Ermon, Ronan Le Bras, Carla Gomes, Bart Selman, and Bruce van Dover
    SMT-Aided Combinatorial Materials Discovery [PDF] [Code]
    SAT-12. In Proc. 15th International Conference on Theory and Applications of Satisfiability Testing, June 2012.
  • Stefano Ermon, Carla Gomes, Bart Selman, and Alexander Vladimirsky
    Probabilistic Planning With Non-linear Utility Functions and Worst Case Guarantees [PDF]
    AAMAS-12. In Proc. 11th International Conference on Autonomous Agents and Multiagent Systems, June 2012.

2011

  • Stefano Ermon, Carla Gomes, Ashish Sabharwal, and Bart Selman
    Accelerated Adaptive Markov Chain for Partition Function Computation [PDF] [Code] [Data]
    NIPS-11. In Proc. 25th Annual Conference on Neural Information Processing Systems, December 2011.
  • Stefano Ermon, Carla Gomes, and Bart Selman
    A Flat Histogram Method for Computing the Density of States of Combinatorial Problems [PDF]
    IJCAI-11. In Proc. 22nd International Joint Conference on Artificial Intelligence, July 2011. .
  • Stefano Ermon, Jon Conrad, Carla Gomes, and Bart Selman
    Risk-Sensitive Policies for Sustainable Renewable Resource Allocation [PDF]
    IJCAI-11. In Proc. 22nd International Joint Conference on Artificial Intelligence, July 2011.
  • Stefano Ermon, Carla Gomes, and Bart Selman
    A Message Passing Approach to Multiagent Gaussian Inference for Dynamic Processes (Short Paper) [PDF]
    AAMAS-11. In Proc. 10th International Conference on Autonomous Agents and Multiagent Systems, May 2011.

2010

  • Stefano Ermon, Carla Gomes, and Bart Selman
    Computing the Density of States of Boolean Formulas [PDF] [Slides] [Code] [Data]
    CP-10. In Proc. 16th International Conference on Principles and Practice of Constraint Programming, September 2010.
    Best Student Paper Award
  • Stefano Ermon, Jon Conrad, Carla Gomes, and Bart Selman
    Playing Games against Nature: Optimal Policies for Renewable Resource Allocation [PDF]
    UAI-10. In Proc. 26th Conference on Uncertainty in Artificial Intelligence, July 2010.
  • Stefano Ermon, Carla Gomes, and Bart Selman
    Collaborative Multiagent Gaussian Inference in a Dynamic Environment Using Belief Propagation (Short Paper) [PDF]
    AAMAS-10. In Proc. 9th International Conference on Autonomous Agents and Multiagent Systems, May 2010.

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Honors and Awards

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Professional Service

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Personal

You can find out more about me and see some pictures here.

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©2017 Stefano Ermon