Photo of Ziebart, Brian

Brian Ziebart

Associate Professor

Department of Computer Science

Contact

Building & Room:

3-190H LIB

Address:

801 S. Morgan St., Chicago, IL, 60607

Office Phone:

(312) 355-1733

Related Sites:

About

I am primarily interested in machine learning and its applications to problems in robotics, assistive technologies, and human-computer interaction. I develop and apply new techniques for predicting structured data. I was awarded a Ph.D. in Machine Learning from Carnegie Mellon University in 2010.

Research:

Adversarial prediction: Approximating our training data and optimizing over the exact performance measure to provide greater flexibility for:

  • Learning under covariate shift (input distribution bias) and active learning;
  • Cost-sensitive classification and inductive optimization of univariate performance measures;
  • Learning to optimize for F-measure, discounted cumulative gain, and other multivariate performance measures; and
  • Structured prediction problems over sequences, trees, graphs, etc.

Inverse optimal control: Using maximum entropy structured prediction techniques to forecast future human behavior for intelligent robotics and vehicle navigation applications.

My research is supported by the following grants:

  • NSF CAREER (RI)-1652530Adversarial Machine Learning for Structured Prediction
  • NSF EAGER (SCH)-1650900The Virtual Assistant Health Coach: Summarization and Assessment of Goal-Setting Dialogues with Barbara Di Eugenio, Ben Gerber, Bing Liu, and Lisa Sharp
  • NSF IIS-1526379Robust Optimization of Loss Functions with Application to Active Learning with Lev Reyzin
  • NSF III-1514126Computational tools for extracting individual, dyadic, and network behavior from remotely sensed data with Tanya Berger-Wolf and Meg Crofoot
  • Future of Life Institute: Towards Safer Inductive Learning
  • NSF NRI-1227495Purposeful Prediction: Co-robot Interaction via Understanding Intent and Goals (sub-contract) with Drew Bagnell, Martial Hebert, Anind Dey, Dieter Fox, Josh Tenenbaum

 

Selected Publications

Sima Behpour, Wei Xing, and Brian D. Ziebart
AAAI Conference on Artificial Intelligence2018.
Sima Behpour, Kris M. Kitani, and Brian D. Ziebart
arXiv2017.
Hong Wang, Ashkan Rezaei, and Brian D. Ziebart
arXiv2017.
Rizal Fathony, Mohammad Bashiri, and Brian D. Ziebart
Advances in Neural Information Processing Systems (NIPS)2017.
Chris Schultz, Sanket Gaurav, Mathew Monfort, Lingfei Zhang, and Brian D. Ziebart
International Conference on Robotics and Automation (ICRA)2017.
Rizal Fathony, Anqi Liu, Kaiser Asif, and Brian D. Ziebart
Advances in Neural Information Processing Systems (NIPS)2016.
Xiangli Chen, Mathew Monfort, Brian Ziebart, and Peter Carr
Uncertainty in Artificial Intelligence (UAI)2016.
Jia Li, Kaiser Asif, Hong Wang, Brian D. Ziebart, and Tanya Berger-Wolf
International Joint Conference on Artificial Intelligence (IJCAI)2016.
Xiangli Chen, Mathew Monfort, Anqi Liu, and Brian D. Ziebart
International Conference on Artificial Intelligence and Statistics (AISTATS)2016.
Hong Wang, Wei Xing, Kaiser Asif, and Brian D. Ziebart
Advances in Neural Information Processing Systems (NIPS)2015.
Mathew Monfort, Brenden Lake, Brian Ziebart, Patrick Lucey, and Joshua Tenenbaum
Advances in Neural Information Processing Systems (NIPS)2015.
Hong Wang, Anqi Liu, Jing Wang, Brian D. Ziebart, Clement T. Yu, Warren Shen
International Conference on The Theory of Information Retrieval (ICTIR)2015.
Kaiser Asif, Wei Xing, Sima Behpour, Brian D. Ziebart
International Conference on Uncertainty in Artificial Intelligence (UAI),2015.
Arunkumar Byravan, Mathew Monfort, Brian Ziebart, Byron Boots, Dieter Fox
International Joint Conference on Artificial Intelligence (IJCAI)2015.
Xiangli Chen and Brian D. Ziebart
International Conference on Artificial Intelligence and Statistics (AISTATS)2015.
Jing Wang, Mohit Bansal, Kevin Gimpel, Brian D. Ziebart, and Clement T. Yu
Transactions of the Association for Computational Linguistics2015.
Anqi Liu, Lev Reyzin, and Brian D. Ziebart
AAAI Conference on Artificial Intelligence2015.
Mathew Monfort, Anqi Liu, and Brian D. Ziebart
AAAI Conference on Artificial Intelligence2015.
Anqi Liu and Brian D. Ziebart
Advances in Neural Information Processing Systems (NIPS)2014.
Spotlight Presentation
Arunkumar Byravan, Mathew Monfort, Brian D. Ziebart, Byron Boots, and Dieter Fox
NIPS Workshop on Autonomous Learning Robots2014.
Mathew Monfort, Anqi Liu and Brian D. Ziebart
IROS Workshop on Assistance and Service Robotics in a Human Environment2014.
Brian D. Ziebart
Annual Allerton Conference on Communication, Control, and Computing2013.
Christian Koehler, Brian D. Ziebart, Jennifer Mankoff, and Anind K. Dey
ACM Joint Conference on Pervasive and Ubiquitous Computing,2013.
Xiangli Chen and Brian D. Ziebart
ICML Workshop on Machine Learning For System Identification,2013.
Brian D. Ziebart, J. Andrew Bagnell, and Anind K. Dey
IEEE Transactions on Information Theory2013.
Kris M. Kitani, Brian D. Ziebart, J. Andrew Bagnell, and Martial Hebert
European Conference on Computer Vision (ECCV)2012.
Best Paper Runner-Up
Brian D. Ziebart, Anind K. Dey, and J. Andrew Bagnell
International Conference on Intelligent User Inferfaces (IUI)2012.
Best Paper Nominee
Brian D. Ziebart, Miro Dudik, Geoff Gordon, Katia Sycara, Wendi Adair, Jeanne Brett
Hawaii International Conference on System Science (HICSS)2012.
Brian D. Ziebart
Allerton Conference on Communication, Control, and Computing (Allerton)2011.
Brian D. Ziebart
International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt)2011.
Kevin Wuagh, Brian D. Ziebart, and J. Andrew Bagnell
International Conference on Machine Learning (ICML)2011.
Best Paper Award
Brian D. Ziebart, J. Andrew Bagnell, and Anind K. Dey
International Conference on Autonomous Agents and Multiagent Systems (AAMAS)2011.
Scott Davidoff, Brian D. Ziebart, John Zimmerman, and Anind K. Dey
SIG CHI Conference on Human Factors in Computing Systems (CHI)2011.
Brian D. Ziebart
PhD Thesis. Department of Machine Learning, Carnegie Mellon UniversityDecember, 2010.
School of Computer Science Distinguished Dissertation Award, Honorable Mention
Brian D. Ziebart and J. Andrew Bagnell and Anind K. Dey
International Conference on Machine Learning (ICML)2010.
Best Student Paper Runner-Up
Brian D. Ziebart, Nathan Ratliff, Garratt Gallagher, Christoph Mertz, Kevin Peterson, J. Andrew Bagnell, Martial Hebert, Anind K. Dey, and Siddhartha Srinivasa
Proc. International Conference on Intelligent Robotics and Systems (IROS)2009.
Nathan Ratliff, Brian Ziebart, Kevin Peterson, J. Andrew Bagnell, Martial Hebert, Anind K. Dey, and Siddhartha Srinivasa
Proc. Aritifical Intelligence and Statistics (AISTATS)2009.
Brian D. Ziebart, Andrew Maas, J. Andrew Bagnell, and Anind K. Dey
AAAI Spring Symposium on Human Behavior Modeling2009.
Brian D. Ziebart, Andrew Maas, Anind K. Dey, and J. Andrew Bagnell
Proc. International Conference on Ubiquitous Computing (Ubicomp),2008.
Brian D. Ziebart, Anind K. Dey, and J. Andrew Bagnell
Proc. International Conference on Automated Planning and Scheduling (ICAPS)2008.
Brian D. Ziebart, Andrew Maas, J. Andrew Bagnell, and Anind K. Dey
Proc. AAAI Conference on Artificial Intelligence2008.
Brian D. Ziebart, Anind K. Dey, and J. Andrew Bagnell
Uncertainty in Artificial Intelligence (UAI)2007.
Brian D. Ziebart, Dan Roth, Roy H. Campbell, and Anind K. Dey
IEEE International Conference on Autonomic Computing (ICAC),2005.
Anand Ranganathan, Jalal Al-Muhtadi, Jacob Biehl, Brian Ziebart, Roy H. Campbell, and Brian Bailey
PerWare Workshop on Support for Pervasive Computing at Percom,2005.
Manuel Roman, Jalal Al-Muhtadi, Brian Ziebart, and Roy H. Campbell
Systems for Ubiquitous Computing Workshop at Ubicomp2003.
Manuel Roman, Brian Ziebart, and Roy H. Campbell
IEEE International Conference on Pervasive Computing and Communications (PerCom)2003.

Notable Honors

2012, Best Paper Runner-Up, European Conference on Computer Vision (ECCV)

2012, Best Paper Nominee, International Conference on User Interfaces (IUI)

2011, Best Paper Award, International Conference on Machine Learning (ICML)

2011, Honorable Mention for Dissertation Award, Carnegie Mellon University School of Computer Science

Education

Ph.D., Carnegie Mellon University, 2010