WORKSHOP ON COMMON TASK FRAMEWORKS FOR SCIENCE AND ENGINEERING
(Virtual) February 14-15, 2023
Machine learning and AI are now being used broadly in the engineering and physical sciences, with a tremendous diversity of architectures and algorithms being developed across disciplines and applications. The AI Institute in Dynamic Systems aims to annually host practitioners in the field, domain experts and ML/AI developers, to help build a common task framework for evaluating algorithms. An overarching goal is to develop a taxonomy of enabling architectures and algorithms for the various tasks required in applications, including estimation, forecasting, sensing and control. This is in keeping with the AI Institute’s mission to build and support sustainable challenge data sets for evaluating algorithms and methods for solving modern problems in science and engineering.
Join us for this exciting opportunity to bring together a broad range of researchers at the interface of data-driven modeling of systems in engineering and science.
The event will be primarily virtual, but graduate students and postdocs are especially encouraged to attend in person on the University of Washington campus as the workshop will be followed up by a one day hands-on programming workshop (Feb. 16th) dedicated to training machine learning algorithms and learning how to implement a diversity of architectures for engineering problems.
Join us for this exciting opportunity to bring together a broad range of researchers at the interface of data-driven modeling of systems in engineering and science.
The event will be primarily virtual, but graduate students and postdocs are especially encouraged to attend in person on the University of Washington campus as the workshop will be followed up by a one day hands-on programming workshop (Feb. 16th) dedicated to training machine learning algorithms and learning how to implement a diversity of architectures for engineering problems.
REGISTRATION NOW CLOSED: TRAVEL/ATTENDEE INFO
Schedule for Tuesday, February 14
HUB 250 in person attendees | Zoom for online attendees
10-12 PST— The Impact of the CTF in AI
David L. Donoho, Professor of Statistics at Stanford; Sean Mooney, Chief Research Information Officer at UW Medicine; Jake Albrecht, Director, Challenges and Benchmarks at Sage Bionetworks
Break
1-3 PST — Framing Scientific and Engineering Challenges for the CTF
Hod Lipson, Professor of Mechanical Engineering, Columbia University & Thrust Co-Lead: AI for Modeling, AI Institute in Dynamic Systems; Jorn Dunkel, Professor of Mathematics at MIT; Laure Zanna, Professor of Mathematics & Atmosphere/Ocean Science at the Courant Institute; Ishanu Chattopadhyay, Assistant Professor at University of Chicago Medicine
10-12 PST— The Impact of the CTF in AI
David L. Donoho, Professor of Statistics at Stanford; Sean Mooney, Chief Research Information Officer at UW Medicine; Jake Albrecht, Director, Challenges and Benchmarks at Sage Bionetworks
Break
1-3 PST — Framing Scientific and Engineering Challenges for the CTF
Hod Lipson, Professor of Mechanical Engineering, Columbia University & Thrust Co-Lead: AI for Modeling, AI Institute in Dynamic Systems; Jorn Dunkel, Professor of Mathematics at MIT; Laure Zanna, Professor of Mathematics & Atmosphere/Ocean Science at the Courant Institute; Ishanu Chattopadhyay, Assistant Professor at University of Chicago Medicine
Schedule for Wednesday, February 15
10-12 PST — CTF in Dynamic Systems
J. Nathan Kutz, Robert Bolles and Yasuko Endo Professor, University of Washington & Director, AI Institute in Dynamic Systems; Aditya Nair Assistant Professor of Mechanical Engineering, University of Nevada, Reno & Thrust Co-Lead: AI for Control, AI Institute in Dynamic Systems; Floris van Breugel, Assistant Professor of Mechanical Engineering, University of Nevada, Reno & PI, AI Institute in Dynamic Systems; Scott McCalla, Associate Professor of Mathematical Sciences, Montana State University & Thrust Co-Lead: AI for Modeling, AI Institute in Dynamic Systems
Break
1-3 PST — The CTF for Education and DEI
Steven L. Brunton, James Morrison Profesor, University of Washington & Associate Director, AI Institute in Dynamic Systems; Jeff Basoah, Wisdom O. Ikezogwo, Kyle Johnson of AVELA (A Vision for Electronic Literacy & Access), University of Washington; Frances Zhu, Assistant Professor, Hawaiian Institute of Geophysics and Planetology, University of Hawai'i at Mānoa & Co-Lead: AI for Applications, AI Institute in Dynamic Systems
4-6 PST — Workshop reception and poster session | For registered, in-person attendees
J. Nathan Kutz, Robert Bolles and Yasuko Endo Professor, University of Washington & Director, AI Institute in Dynamic Systems; Aditya Nair Assistant Professor of Mechanical Engineering, University of Nevada, Reno & Thrust Co-Lead: AI for Control, AI Institute in Dynamic Systems; Floris van Breugel, Assistant Professor of Mechanical Engineering, University of Nevada, Reno & PI, AI Institute in Dynamic Systems; Scott McCalla, Associate Professor of Mathematical Sciences, Montana State University & Thrust Co-Lead: AI for Modeling, AI Institute in Dynamic Systems
Break
1-3 PST — The CTF for Education and DEI
Steven L. Brunton, James Morrison Profesor, University of Washington & Associate Director, AI Institute in Dynamic Systems; Jeff Basoah, Wisdom O. Ikezogwo, Kyle Johnson of AVELA (A Vision for Electronic Literacy & Access), University of Washington; Frances Zhu, Assistant Professor, Hawaiian Institute of Geophysics and Planetology, University of Hawai'i at Mānoa & Co-Lead: AI for Applications, AI Institute in Dynamic Systems
4-6 PST — Workshop reception and poster session | For registered, in-person attendees
Schedule for Thursday, February 16 | For in-person graduate students and postdocs registered for the workshop
9-11 PST — Autoencoders and Latent Dynamics
Joe Bakarji, Postdoctoral Researcher, University of Washington
Break
11:30-1 PST — Mentorship Lunch Panel
Join panelists for an informal session to discuss careers, opportunities, and diversity & ethics in AI broadly
Myra Rolden, Sr. Technical Program Manager, AWS Machine Learning University; Kathleen Champion, Applied Scientist, Amazon; Brian de Silva, Applied Scientist, Amazon; Erdi Kara, Assistant Professor, Spelman College
1-2:30 PST — Sparsifying Neural Networks
Olivia Thomas, Doctoral Student, University of Washington
Break
3-4:30 PST — Temporal Dynamics and Recurrent Neural Networks
Jan Williams, Doctoral Student, University of Washington
Joe Bakarji, Postdoctoral Researcher, University of Washington
Break
11:30-1 PST — Mentorship Lunch Panel
Join panelists for an informal session to discuss careers, opportunities, and diversity & ethics in AI broadly
Myra Rolden, Sr. Technical Program Manager, AWS Machine Learning University; Kathleen Champion, Applied Scientist, Amazon; Brian de Silva, Applied Scientist, Amazon; Erdi Kara, Assistant Professor, Spelman College
1-2:30 PST — Sparsifying Neural Networks
Olivia Thomas, Doctoral Student, University of Washington
Break
3-4:30 PST — Temporal Dynamics and Recurrent Neural Networks
Jan Williams, Doctoral Student, University of Washington