The Data Systems Seminar Series provides a forum for exploring and discussing important topics in data systems, from current challenges to emerging trends. It complements our internal meetings by bringing fresh perspectives from invited external speakers.
The schedule for the 2026–27 academic year is outlined below and will be updated as speakers are confirmed.
Seminars are typically held monthly on Mondays at 10:30 a.m. in DC 1304, unless otherwise noted. Some sessions may be held virtually on Zoom; these will be clearly marked.
All talks are open to the public.
We will record and upload videos of presentations whenever possible. Past DSG Seminar Series videos are on the DSG YouTube channel.
The Data Systems Seminar Series is supported by
| Data Systems Seminar Series Speakers |
| Matthias Weidlich |
| Qizhen Zhang |
Monday, September 21, 2026 at 10:30 a.m. in DC 1304
| Title | Beyond Sets and Bags — The Behavioral Perspective in Data Management |
| Speaker | Matthias Weidlich, Hasso Plattner Institute, University of Potsdam |
| Abstract | In various application scenarios, the temporal perspective of data is of particular importance. That is, the ordering of data elements constitutes an essential aspect in their analysis, for instance, by identifying behavioral patterns in a dataset. In this talk, I give an overview of some of our work on answering the questions of why to query for certain behavior, how to support users in the definition of effective queries, and how to evaluate these queries efficiently. |
| Bio | Matthias is a full professor and chair for Data Systems at the Hasso Plattner Institute (HPI), at the Digital Engineering Faculty of the University of Potsdam. Before joining HPI in 2026, he held positions as a full professor and chair for Databases and Information Systems at Humboldt-Universität zu Berlin, research associate at Imperial College London, and as a research fellow and adjunct lecturer at the Technion - Israel Institute of Technology. His research focuses on data-driven process analysis, event stream processing, and exploratory data analysis. He serves as Co-Editor in Chief for the Information Systems journal and is a member of the steering committees of the ACM DEBS and BPM conference series. |
Monday, October 19, 2026 at 10:30 a.m. in DC 1304
| Title | Redesigning Cloud Databases for AI Data Centers |
| Speaker | Qizhen Zhang, Department of Computer Science, University of Toronto |
| Abstract | Cloud data centers are undergoing once-in-a-decade transformation as they evolve to house hyperscale services and AI workloads. What opportunities does this create for database systems? In this talk, I will explore this question through our recent work on data processing with DPUs and GPUs. I will first introduce DPDPU, a platform for building low-cost high-performance database systems using DPUs, and the latest progress on optimizing storage (with DDS) and compute (with dpKernels) under this umbrella. I will also present MGI, a communication interface for databases to access massive GPU infrastructures to unlock unprecedented scale of database acceleration. |
| Bio | Qizhen Zhang is an Assistant Professor of Computer Science at the University of Toronto, where he leads the Far Data Lab. His current research focuses on building infrastructures for large-scale data processing, and he is broadly interested in data management and computer systems and networking. His research appears at top-tier database and systems/networking conferences such as SIGMOD/VLDB and SIGCOMM/NSDI. He received his Ph.D. in the Department of Computer and Information Science at the University of Pennsylvania, where his work was recognized with the best Computer Science Ph.D. dissertation award. He spent a gap year in industry at Microsoft Research, Redmond, before joining UofT. His lab has been supported by Connaught New Researcher Award, Digital Research Alliance of Canada Resources for Research Groups Grant, NSERC Discovery and Alliance grants, and gifts from industrial sponsors such as Amazon and Google. More details can be found on Qizhen Zhang’s research site and the Far Data Lab site. |
Monday, November 23, 2026 at 10:30 a.m. in DC 1304
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Monday, January 11, 2027 at 10:30 a.m.
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Monday, April 12, 2027 at 10:30 a.m.
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Monday, May 10, 2027 at 10:30 a.m.
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Monday, June 7, 2027 at 10:30 a.m.
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Monday, July 19, 2027 at 10:30 a.m.
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Monday, August 16, 2027 at 10:30 a.m.
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