Thomas G. Dietterich
Distinguished Professor (Emeritus) and Director of Intelligent Systems
Institute for Collaborative Robotics and Intelligence Systems (CoRIS)
School of Electrical Engineering and Computer Science
1148 Kelley Engineering Center
Oregon State University
Corvallis,
Oregon 97331-5501
E-mail:
tgd@cs.orst.edu
Twitter: @tdietterich
Phone: +1-541-737-5559
Office: KEC 2067
PGP Public Key
(Last updated June 12, 2020)
Page Contents:
Research
Prospective Students
Publications
Talks
CV
Software
Students and Staff
Course Materials
Bio Sketch
"If you invent a breakthrough in artificial intelligence,
so machines can learn," Mr. Gates responded, "that is worth
10 Microsofts." (Quoted in NY Times, Monday March 3, 2004)
The focus of my research is artificial intelligence and machine learning. How can we make computer
systems that adapt and learn from their experience? How can we
combine machine learning with other advances in AI to build
Integrated Intelligent Systems? How can we make those integrated AI
systems robust to errors, both known and unknown? How can we
combine human knowledge with massive data sets to expand scientific
knowledge and build more useful computer applications? My
laboratory combines research on machine learning and AI fundamentals
with applications to problems in science and engineering.
- Scientific Projects
- Robust Artificial Intelligence. AI methods are
widely deployed in many parts of the economy including search
engines, speech-enabled systems, computer vision, and natural
language translation. Automated reasoning tools developed in AI
have been integrated with traditional algorithms from operations
research to create very powerful optimization programs such as
Gurobi
and CPLEX.
Of particular concern are AI applications that involve life-and-death
decision making such as self-driving cars, AI control of the power
grid, and autonomous weapons systems. Before we deploy AI in such
applications, we need to be confident that it will behave
correctly.
With my colleagues and students, I'm pursuing research in safe
artificial intelligence including open category supervised
learning, safe reinforcement learning,
and explainable
artificial intelligence. I've reviewed the research challenges in this area
in my AAAI Presidential Address, Steps Toward Robust
Artificial Intelligence. Slides, Video, Paper.
- Ecosystem Informatics and Computational
Sustainability: Oregon State University is a leader in combining
computer science and the ecological sciences to build the new
discipline of Ecosystem Informatics. Ecosystem Informatics studies
methods for collecting, analyzing, and visualizing data on the
structure and function of ecosystems. It is part of the larger field
of Computational Sustainability.
Oregon State is also part of the Institute for
Computational Sustainability led by Cornell University.
This effort seeks to develop novel computational methods to address
problems in ecosystem science and sustainable management of the
biosphere.
My group is involved in many Ecosystem Informatics and
Computational Sustainability activities:
- Approximate Optimization for Bio-Economic Models. Many
sustainability applications require solving large spatio-temporal
optimization problems under uncertainty. We are collaborating
with natural resource economists on methods for approximate solution of
spatio-temporal optimization problems involving land management
for wildfire control and counter-measures for controlling invasive
species.
- Project TAHMO: Deployment, Cleaning, and Analysis of Sensor
Network Data. We are part of
the Project TAHMO that seeks to
construct and deploy a network of 20,000 hydro-meteorological
stations in Africa. We are developing algorithms for sensor
placement, data cleaning, recovery from damaged sensors, and
analysis of the resulting data. We are building on our previous
work with Ethan Dereszynski on dynamic Bayesian network models for
sensor data cleaning.
- NIPS 2012
Posner Lecture: Challenges for Machine Learning in
Computational Sustainability.
- ICML 2011 Tutorial
on Machine Learning in Ecology and Ecosystem
Management
- Intelligent Desktop Assistants. We have been involved in two
large efforts to develop intelligent assistants for the computer desktop.
- TaskTracer. When you come into work in the morning,
you don't want to say to your computer "I want to run Word", but
rather, "I want to work on my CS534 homework". In other words,
you would like a user interface that was organized around your
projects and activities rather than around application programs,
files, folders, etc. You would also like all of your information
in one place rather than scattered across the local file system,
network file systems, dropbox, web sites, email folders, calendar,
contacts, etc. TaskTracer extends the Windows UI to provide
exactly this functionality. This research is supported by a gift
from Keysight, Inc. with previous support from Google, Intel, and
the DARPA CALO project.
- Fundamental Machine Learning and Artificial Intelligence Research
- Reviews, tutorials, and
books. I have written several review articles and tutorials on
machine learning.
If you are seeking a research career in machine learning, data mining,
artificial intelligence and related areas, and you have a strong
background in mathematics and programming, please read my Information for Prospective Students
page.
If you are interested in robotics, I encourage you to visit
the Robotics Team
Pages to learn more about our excellent robotics program.
Professional Service, Journals, and Book Series
Entrepreneurial Activities
- I am a co-founder of Strands
(formerly MyStrands; formerly MusicStrands), a recommendation company.
- I am a co-founder of Smart Desktop. Smart Desktop
is now part of Decho, Inc., which is a "cloud
computing" effort of EMC.
Decho was a spinout of the TaskTracer project.
- I am a co-founder and Chief Scientist of BigML. The
goal of this startup is to develop large scale cloud-based machine
learning services.
Former Students and Staff
- Majid Alkaee Taleghan. Machine Learning Scientist at Context Relevant.
- Hussein Almuallim,
Oil and Energy Professional, Calgary, Canada.
- Eric Altendorf, Google.
- Adam Ashenfelter, BigML, Inc., Corvallis, Oregon.
- Ghulum Bakiri, President at MicroCenter, Bahrain.
- Christian Baumberger. Software Engineer at Zuehlke Group
- Xinlong Bao. Google Pittsburgh.
- Brian Breck.
- Waranun Bunjongsat.
- Giuseppe Cerbone. Independent Information Services Professional, Milan, Italy.
- Martha Chamberlin.
- Hei Chan. Assistant Professor / Project Researcher at the
Transdisciplinary Research Integration Center, UCLA.
- Richard Charon.
- Eric Chown, Full Professor, Bowdoin College.
- Selina Chu, JPL, Pasadena, CA.
- Dan Corpron
- Mark Crowley, Assistant Professor, Department of Electrical and
Computer Engineering, University of Waterloo.
- Diane Damon, Damon Consulting, Portland, OR.
- Ethan
Dereszynski, Research Scientist, WebTrends, Portland, OR.
- Phuoc Do, Vida Lab.
- Nicholas Flann Associate Professor, Utah State University
- Greg Foltz.
- Dan Forrest.
- Tony Fountain, Director of the Cyberinfrastructure Lab for Environmental Observing Systems (CLEOS), UC San Diego.
- Ashit Gandhi, Founder and Vice-President, Prism Gem, LLC - The Art of Diamond Coloring.
- Colin Gerety, Fort Collins, CO.
- Brandon Harvey, Symantec and Linn-Benton Community College.
- Arwen Griffioen.
- Guohua Hao, Senior Data Scientist at iHeartRadio.
- Hermann Hild, President, SMI Cognitive Software GmbH .
- Jesse Hostetler
- Rebecca
Hutchinson, Assistant Professor of Computer Science and
Fishers and Wildlife.
- Saket Joshi, Member of Technical Staff at Cycorp.
- Varad Joshi, Director of Engineering at Elemental Technologies.
- Caroline Koff, Hewlett-Packard Corporation, Fort Collins, CO.
- Victoria
Keiser, Research Programmer, CMU. Masters Thesis (PDF).
- Michael Kelm, Research Scientist, Siemens Healthcare.
- Eun Bae Kong, Professor, Computer Science, Chungnam National University, South Korea
- Bill Langford, Research Associate at RMIT, Melbourne, Australia.
- Junyuan
Lin, VMWare, Seattle.
- Liping Liu,
Postdoc with David Blei, Columbia University.
- Dragos Margineantu, The Boeing Company.
- Gonzalo Martinez, Assistant Professor, Autonomous University of Madrid.
- Sean McGregor. XPRIZE.
- Prafulla Mishra, Software Development Manager at eBay.
- Avis Ng.
- Soumya Ray, Assistant Professor, Case-Western Reserve University.
- Angelo Restificar, Principal Machine Learning Engineer, EBay, Seattle.
- Ritchey Ruff, Senior SDET, Microsoft.
- Dan Sheldon, Assistant Professor, University of Massachusetts, Amherst.
- Jianqiang Shen. Research Scientist, PARC. Doctoral dissertation.
- Rongkun Shen.
Post-doc, Oregon Health and Science University, Portland.
- Michael
Shindler, Lecturer at the University of Southern California
- Shriprakash Sinha. Ph.D. student TU Delft.
- Shahed
Sorower, Scientist at Philips Research North America
(Cambridge, MA.)
- Simone
Stumpf. Senior Lecturer, City University London.
- Amelia Snyder, Intern at World Resources Institute
- Tao Sun, Graduate Student at UMass Amherst.
- Dan Vega, Senior Software Engineer at Valley Inception, LLC.
- Mark Vulfson. Microsoft Corporation.
- Kiri Wagstaff, Principle Researcher at JPL.
- Xin
Wang, Senior Scientist at Inome (Intelius).
- Dietrich Wettschereck. Consultant, Cologne, Germany.
- Pengcheng Wu.
- Michael Wynkoop, Qualcomm.
- Qing Yao, College of Informatics and Electronics. Zhejiang Sci-Tech University. Hangzhou, China.
- Wei Zhang, The Boeing Company.
- Wei
Zhang. Senior Software Engineer, Google. Doctoral Dissertation (PDF).
- Valentina
Zubek, Principal Statistician, Boehringer Ingelheim.
- Tsinghua Short Course
on Trustable Machine Learning, Fall 2018
- CS519/GEO599: Principles of
Ecosystem Informatics, 2004-2005.
- CS 534, Spring 2005, Machine
Learning.
- CS430, Fall 2003, Introduction to
Artificial Intelligence
- CS539, Fall 2003, Seminar: Probabilistic
Relational Models
- CS 533, Applied Artificial
Intelligence for Engineeers.
- CS 539, Winter 2000, Selected Topics in
Artificial Intelligence: Probabilistic Agents
- CS 430/530, Fall 1999, Artificial Intelligence
Programming Techniques.
- CS 519, Fall 1996. Research Methods
in Computer Science.
- CS 450/550, Winter 1996, Introduction to Computer Graphics.
Machine Learning Resources
My Family's Musical Activities
Tom Dietterich, tgd@cs.orst.edu