I am a Ph.D. student working with Dr. Suresh Venkatasubramanian and Dr. Tucker Hermans. My long term goal is to understand intelligence. What is it? What are its limitations and manifestations? Can we create it? If so, how? To answer these and related questions I am taking a constructionist approach of building intelligent agents. As such my research has been on developing algorithms to address the motion planning and control problems using machine learning with a focus on deep learning methods and architectures. To this end I spent a year at L'institut des algorithmes d'apprentissage de Montréal studying deep learning under the supervision of Dr. Yoshua Bengio and Dr. Roland Memisevic. I am alo interested in the theoretical underpinngs of deep learning to better understand how it can be used to solve robotics problems.
I am currently planning to graduate in the spring of 2018. As such I am actively seeking job opportunities and postdoc positions.
On rare occasion I share my musings on my blog, Undefined Intelligence.
dustin at cs dot utah dot edu
Room 2180, School of Computing
50 S. Central Campus Drive
Salt Lake City, UT 84112
- Kyle L. Crandall, Dustin Webb, Adam Wickenheiser;
Learning Abstraction of a Swarm to Control a Parent System
The 4th International Conference on Control, Automation, and Robotics -- ICCAR, 2018
- Theano Development Team;
Theano: A Python framework for fast computation of mathematical expressions.
arXiv preprint arXiv:1605.02688, 2016
- John Moeller, Vivek Srikumar, Sarathkrishna Swaninathan,
Suresh Venkatasubramanian, Dustin Webb;
Continuous Kernel Learning.
Proc. European Conference on Machine Learning and Principles and Practice of Knowledge Discovvery - ECML-PKDD, 2016
- Dustin J. Webb, Kyle L. Crandall, Jur van den Berg;
Online Parameter Estimation via Real-Time Replanning of Continuous Gaussian POMDPs.
Proc. IEEE Int. Conf. on Robotics and Automation - ICRA, 2014.
[pdf, project website]
- Dustin J. Webb, Jur van den Berg;
Kinodynamic RRT*: Asymptotically Optimal Motion Planning for Robots with Linear Dynamics.
Proc. IEEE Int. Conf. on Robotics and Automation - ICRA, 2013.
[pdf, video, project website]
- Databases: MySQL, PostgreSQL
- Libraries: Keras*, Pylearn2, Robot Operating System (ROS), TensorFlow,* Theano
- Machine learning: Deep learning (CNNs, RNNs, GANs), Deep reinforcement learning*, Kernel machines, Reinforcement learning
- Mathematics: Algebra, Calculus*, Differential Equations*, Linear Algebra, Probabilities*, Statistics, Trigonometry
- Operating Systems: Linux*, OS X, Windows
- Programming Languages: C, C++, Java, Python*
- Software: Arduino, GIMP, iMovie, Inkscape, Keras, Latex*, Mathematica, Matlab, Microsoft Office
- Source Control: CVS, Git, SVN
* Most frequently used skills.
|University of Utah||School of Computing||Ph.D.||expected 2018|
|University of Utah||School of Computing||B.S.||2011|
|Salt Lake Community College||Computer Science||A.S.||2008|
- Fall 2015: Deep Learning Seminar (CS7931) Co-instructor
- Fall 2013: Machine Learning (CS5350/CS6350) Teaching Assistant
- Spring 2012: Artificial Intelligence (CS5300/CS6300) Teaching Assistant
Honors & Awards
- 2014 - 2015: Montréal Institute of Learning Algorithms (MILA) Internship with Dr. Yoshua Bengio.
- 2011 - 2013: Integrative Graduate Education and Research Traineeship (IGERT).
- 2011: Undergraduate Research Scholar Award.
- Institute of Electrical and Electronics Engineering (IEEE), Student Member 2012-Present.
- Assoc. for the Advancement of Artificial Intelligence (AAAI), Student Member 2010-Present.
Utah FIRST Lego League
- 2013-2014 Team Volcanoes Coach.
- 2013 State Championships Robot Design Judge.
- 2013 McGillis School Qualifier Robot Design Judge.
- 2012 McGillis School Qualifier Robot Design Judge.
- 2011 State Championships Robot Design Judge.
Utah FIRST Robotics Competition
- 2013 State Championships Judges Assistant.
- 2012 State Championships Judges Assistant.