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.

Curriculum Vitae

Teaching

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Honors and Awards

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Publications

2019

2018

2017

2016

More Publications

2015

  • Stefan Hadjis, Stefano Ermon
    Importance sampling over sets: a new probabilistic inference scheme. [PDF] [Code]
    UAI-15. In Proc. 31st Conference on Uncertainty in Artificial Intelligence, July 2015.
  • Michael Zhu, Stefano Ermon
    A Hybrid Approach for Probabilistic Inference using Random Projections. [PDF]
    ICML-15. In Proc. 32nd International Conference on Machine Learning, July 2015.
  • Yexiang Xue, Stefano Ermon, Carla Gomes, Bart Selman
    Uncovering Hidden Structure through Parallel Problem Decomposition for the Set Basis Problem with Application to Materials Discovery. [PDF]
    IJCAI-15. In Proc. International Joint Conference on Artificial Intelligence, July 2015.
  • Stefano Ermon, Yexiang Xue, Russell Toth, Bistra Dilkina, Richard Bernstein, Theodoros Damoulas, Patrick Clark, Steve DeGloria, Andrew Mude, Christopher Barrett, and Carla Gomes
    Learning Large Scale Dynamic Discrete Choice Models of Spatio-Temporal Preferences with Application to Migratory Pastoralism in East Africa. [PDF]
    AAAI-15. In Proc. 29th AAAI Conference on Artificial Intelligence, January 2015.
  • Stefano Ermon, Ronan Le Bras, Santosh Suram, John M. Gregoire, Carla Gomes, Bart Selman, and Robert B. van Dover
    Pattern Decomposition with Complex Combinatorial Constraints: Application to Materials Discovery. [PDF]
    AAAI-15. In Proc. 29th AAAI Conference on Artificial Intelligence, January 2015.

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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Personal

You can find out more about me here.

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©2017 Stefano Ermon