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Oliver Schulte

Professor
School of Computing Science
Simon Fraser University
Burnaby, B.C. V5A 1S6
Canada
Phone: +1-778-782-3390
Fax: +1-778-782-3045
Machine Learning for Structured Data
Learning Theory
Computational Game Theory

Ph.D.: 1997, Carnegie Mellon University, Logic and Computation
M.Sc.: 1993, Carnegie Mellon University, Logic and Computation
B.Sc.: 1992, University of Toronto, Computing Science.

Find time for a meeting: Work Schedule

Affiliations

Director Structured Machine Learning Lab
Associate Member Department of Statistics
Member of the VINCI institute
Member of SFU Sports Analytics Group

Noteworthy Events

  • Check out my talk on when causal reasoning should be used in reinforcement learning. Thank you to UBC CAIDA for hosting.
  • Our repository of relational databases, known as the Prague Relational Learning Repository, has migrated. The new hostname is db.relational-data.org. The other connection info is the same as before (Port 3306, username=guest,pwd=relational). Thank you to getML for hosting and migrating the server. That is great industry support for the relational learning community.
  • Our repository of relational databases is getting more and more users. (I know because people email me when it's down.) Here is a blog post discussing it.
  • I gave a keynote on hockey analytics at LINHAC 2022, here are the talk and slides. Series on Reinforcement Learning. On reinforcement learning for sports analytics.
  • I gave a brief talk in the Aggregate Intellect Science Series on Reinforcement Learning. On reinforcement learning for sports analytics.
  • Director Sliq Lab (ended 2022). for Predictive Analytics. I have started work as the founding director for a research lab on predictive analytics, that is part of SportLogiq.
  • Strategic Project award. I was the PI on a partnership award from the Natural Sciences and Engineering Research Council of Canada, totalling over $500K for 3 years. The success rate is 20%. Our company partner is SportLogiq. My co-applicants are Greg Mori and Pascal Poupart.
  • Best paper award from the StarAI@IJCAI workshop for the contribution from Manfred Jaeger and myself. The paper discusses how inference and learning for relational network data depends on the population size (node size).
  • NSERC Discovery and Accelerator award. The Natural Sciences and Engineering Research Council of Canada has renewed my operating grant and given me a bonus award. The Accelerator awards aim to provide substantial and timely additional resources to accelerate progress and maximize the impact of outstanding research programs.
  • SFU News and Faculty of Applied Sciences News published an article about our paper at MIT Sloan conference. We said that Erik Karlsson was the best player in the 2015-2016 NHL season and hasn't he been great in 2016-17?
  • My undergraduate RA and coauthor Zeyu Zhao has won the Dean's convocation medal for the Faculty of Applies Sciences. Next he'll be entering the M.Sc. Program at Harvard.
  • Check out my tutorial in learning Bayesian networks for complex relational data . Presented at AAAI 2017, ECML 2016 and Canadian AI 2015.
  • The faculty of Applied Sciences has made a video about some of my research on hockey analytics. I must learn to keep my eyes open while I talk.
  • I co-organized the Vancouver Hockey Analytics Conferences in 2016 , 2017 , and 2018 . You can see the 2016 presentations on-line. I especially recommend the media panel. #vanhac was hashtag number 4 in Canada on the day of the conference! The 2018 conference was sponsored by SFU's Big Data Hub.
  • Fatemeh Riahi received the best student paper award at the IEEE Symposium on Computational Intelligence for her paper "Model-based Outlier Detection for Object-Relational Data"
  • Kurt Routley received an award for the best Canadian AI Master's Thesis of 2015 from the Canadian Artificial Intelligence Association.
  • The IJCAI conference gave me a blue ribbon for my service on the Senior Program Committee 2016.
  • The CTU Prague Relational Learning Repository is live now. It contains over 80 relational datasets for learning. I developed this together with Jan Motl. Here's a write-up of what you can find in it, including how to connect to the database server.