Data Systems meet Data Science Workshop

Overview

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.

Keynote Speaker

• Doina Precup,  DeepMind & McGill

Talk title: On the Need for Systems Know-how in Large-scale Machine Learning and Vice Versa

Speakers

• 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

Panel Discussion

Blindspots at the Intersection of Data Science and Data Systems

• Eric Kolaczyk McGill

• Tristan Glatard Concordia

• Mohammed Al-Kateb Amazon

Panel moderator: Oana Balmau

Agenda

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

Important Dates

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