The first edition of the Montréal Data Systems meet Data Science workshop brings together the Montreal Systems community with an interest in Data Science, Data Systems, and AI. The vision is to interact, to get to know the work that is being done in the community, and to exchange experiences. Technical presentations from guest speakers in industry and academia will be augmented with poster and demo sessions from students, as well as time and space for discussions.
The workshop will take place at Concordia University and is co-organized by Bettina Kemme, Essam Mansour, and Oana Balmau.
Where: Concordia University, 2155 Guy St. Montréal, 10th floor.
When: Friday, October 28. Doors open 8:30 AM, workshop starts at 8:45 AM
Best poster/demo competition: Vote here
Doina Precup, DeepMind & McGill
Talk title: On the Need for Systems Know-how in Large-scale Machine Learning and Vice Versa
Bang Liu, Université de Montréal
Talk title: Identify Event Causality with Knowledge and Analogy
Benjamin Fung, McGill
Talk title: Machine Learning for Cybersecurity and Privacy
Chamseddine Talhi, ETS Montréal
Talk title: 5G and Beyond to Enable Context-Aware and Robust ML-based Cybersecurity
Essam Mansour, Concordia
Talk title: Linked Data Science and System Challenges
Foutse Khomh, Polytechnique Montréal
Talk title: Data quality and model under-specification issues
Joseph Vinish D'Silva, McGill
Talk title: In-database Analytics
Khaled Ammar, Borealis AI - RBC
Talk title: Managing data throughout the ML product lifecycle
Oana Balmau, McGill
Talk title: Storage Benchmarking in ML
Xue Liu, Samsung AI & McGill
Talk title: High Performance Approximate Nearest Neighbor Query for Big Data
Yan Liu, Concordia
Talk title: Learning-based Resource Provision for Large-scale Cloud Services
Blindspots at the Intersection of Data Science and Data Systems
Eric Kolaczyk McGill
Tristan Glatard Concordia
Mohammed Al-Kateb Amazon
Panel moderator: Oana Balmau
8:30 AM Doors Open
8:45 AM Welcome!
9:00 AM Keynote Talk: Doina Precup: On the Need for Systems Know-how in Large-scale Machine Learning and Vice Versa
10:00 AM Break
10:15 AM Talks session 1 (session chair: Oana Balmau)
Bang Liu: Identify Event Causality with Knowledge and Analogy
Benjamin Fung: Machine Learning for Cybersecurity and Privacy
Khaled Ammar: Managing data throughout the machine learning product lifecycle
Essam Mansour: Linked Data Science and System Challenges
11:45 AM Lunch, Posters & Demos @ Concordia
1:45 PM Talks session 2 (session chair: Essam Mansour)
Yan Liu: Learning-based Resource Provision for Large Scale Cloud-based Services
Chamseddine Talhi: 5G and Beyond to Enable Context-Aware and Robust ML-based Cybersecurity
Steve Liu: High Performance Approximate Nearest Neighbor Query for Big Data
2:45 PM Break
3:00 PM Talks session 3 (session chair: Essam Mansour)
Oana Balmau: Storage Benchmarking in ML
Foutse Khomh: Data quality and model under-specification issues
Joseph Vinish D'Silva: In-database Analytics
4:00 PM Break
4:15 PM Panel discussion (panel moderator: Oana Balmau)
Panelists: Eric Kolaczyk, Tristan Glatard, Mohammed Al-Kateb.
5:30 PM Closing remarks
Demos and Posters
Registration deadline: October 10th, 2022 October 24th, 2022. Register your demo or poster here.
Acceptance notification: October 15th, 2022.
Camera-ready version due: October 25th, 2022.
Workshop day: October 28th, 2022
Registration: Contact us if you are interested in participating! Event registration is now closed