[SINFRA 2024] 24-25 June

Save the date SINFRA 2024

Each year, the international IPAL laboratory (CNRS, NUS, A*STAR, Univ Toulouse 3, Toulouse INP, CYU) organizes a workshop which promotes collaboration between France and Singapore in the field of computer science (AI, Data, HCI, NLP, etc.). This workshop is an opportunity to take stock on existing IPAL collaborations and to launch new collaborative projects.

In 2019, SinFra notably made it possible to build the Descartes program, involving around eighty collaborators from France and Singapore, which is funded by the NRF to the tune of 35 million euros !

This year, SinFra will take place in Singapore from June 24 to 25. It will be followed by a satellite workshop on Actionable eXplainable AI on June 26. 

If you registered for the videoconference, here is the link to attend SINFRA online: https://cnrs.zoom.us/j/96577425238?pwd=DSjzux1zGQRagxA1fuffrRw8GyZArW.1

If you have any question, you can contact marie.cluzel@cnrs.fr

    SINFRA Day 1 – Monday 24 June 2024 at A*STAR

    Location: Infuse Theatre, Level 14, Connexis South Tower, Singapore 138632

    8.40 – 9 am Welcome
    9.00 – 9.30 am

    Opening ceremony
    TAN Cheston (IPAL co-director, A*STAR)

    – CHEW Lock Pin, Executive Director, Science and Engineering Research Council, A*STAR
    – TAN Kian Lee, Dean, School of Computing, NUS
    – DURAND-LOSE Jerome, CNRS Informatics, Deputy Director International Affairs (video)
    – VODISLAV Dan, CYU, Vice President for Research
    – ARLAT Mathieu, Vice President for Research, Univ Toulouse 3
    – MAUSSION Pascal, Vice President Toulouse INP

    – BANETH-NOUAILHETAS Emilienne, Counsellor for Culture, Education and Science, Embassy of France in Singapore

    – JOUFFRAIS Christophe (IPAL director, CNRS): outline of the SinFra 2024 workshop

    9.30 – 10.10 am Theme #1: Explainable and Trustable AI
    Blaise Genest (CNRS) & Abhik Roychoudhury (NUS)
    10.10 – 10.40 am Poster Teasing Session
    Caroline Chaux
    10.40 – 11.30 am Coffee Break and Poster Session
    11.30 – 12.10pm Theme #2: AI & HCI
    Suranga Nanayakkara (NUS), Cheston Tan (A*STAR) & Christophe Jouffrais (CNRS)
    12.10 – 1.30 pm Lunch break
    1.30 – 2.30 pm Visit to I2R Automated Inspection & Visualization (AIV) Lab, A*STAR
    Cheston Tan (A*STAR)
    2.30 – 3.30 pm

    Collaboration Opportunities by Cheston Tan (A*STAR)
    – Vincent Tang, Program Manager, NVIDIA Development SG (15 min)

    New topics by Cheston Tan (A*STAR)

    • Michele Linardi & Katerina Tzompanaki (CYU) (15 min)
    • Dimitris Kotzinos (CYU)  (15 min)
    3.30 – 3.50 pm Coffee Break
    3.50 – 5.50 pm

    Session on Collaborative Grant Funding (France/Singapore)
    Christophe Jouffrais (CNRS)

    CREATE AI 4 Science call (15 + 10 min)

    • News about the AI for Science call by D. Baillargeat (Director, CNRS@CREATE)
    • Presentation the AISSAI center by Jalal Fadili (Director, CNRS)

    AI lab program (15 + 10 min)
    by Michael Krajecki (AID, FR) and Chia Yuan Cho (FSTD, SG)


    Singaporean, French & European collaborative research funding (15 + 10 min)

    • ANR, Merlion, Horizon Europe by Marie Cluzel (CNRS)
    • NRF-CRP funding by Cheston Tan (A*STAR)
    • MOE funding by Wei Tsang Ooi (NUS)

    AI Research Grant Calls 2024 – 6th Call (5 + 5 min)
    by Cheston Tan (A*STAR)

    IPAL PhD funding schemes (15 + 10 min)

    • PhD ARAP co-funding by Cheston Tan (A*STAR)
    • PhD CYU and UT3 co-funding by Christophe Jouffrais (CNRS)
    • PhD NUS funding Wei Tsang Ooi (NUS)

    General Discussion


      VIPs attending Monday’s dinner will eat at the restaurant Clove (7.30pm). There will be a bus taking guests from A*STAR to the restaurant. Departure : 6.15pm at the Fusionopolis pickup point. Don’t be late !

      Marie will be leading the IPAL students to another dinner place. Please, meet her at the Fusionopolis pickup point at 6.15 pm too.

      SINFRA Day 2 – Tuesday 25 June 2024 at NUS

      Location: I4 Seminar Room, I4-01-03
      Innovation 4.0 Builiding, 3 Research Link, Singapore 117602

      8.40 – 9 am Welcome
      9.00 – 9.10 am

      Opening by Wei Tsang OOI (IPAL co-director, NUS)

      Outline of the day

      9.10 – 9.50 am

      Theme #3: Natural Language Processing

      Farah Benamara (University of Toulouse) & Jian Su (A*STAR)

      9.50 – 10.30 am

      Theme #4: Data Science and Applications

      Stéphane Bressan (NUS) & Caroline Chaux (CNRS)

      10.30 – 10.50 am Coffee Break
      10.50 – 11.30 am

      Theme #5: Efficient AI

      Benoit Cottereau (CNRS) & Wei Tsang Ooi (NUS)

      11.30 – 12.30 pm

      Visit to NUS Augmented Human Lab

      Suranga Nanayakkara (NUS)

      12.30 – 1.30 pm Lunch break
      1.30 – 2.30 pm

      New topics by Wei Tsang Ooi (NUS)

      • David Novo (CNRS) (visio, 15 min)
      • Jean Martinet (CNRS)(15 min)

      Collaboration Opportunities by Wei Tsang Ooi (NUS)

      • Dunlin Tan, Director, Thales Research & Technology SG (15 min)
      • Denis Gagneux, Head of the Center of Excellence – Naval Group SG: AI for maritime (15 min)
      2.30 – 3.30 pm

      Lab brainstorming for the 2026-2030 program

      Seminar Room 11 (COM3-01-20) and 15 (COM3-01-25), COM3 Level 1

      By Christophe Jouffrais, Wei Tsang Ooi, Cheston Tan

      3.30 – 3.50 pm

      Coffee Break @ Innovation 4

      3.50 – 5.20 pm

      Lab brainstorming for the 2026-2030 program
      Synthesis and closing 

      Seminar Room 11 (COM3-01-20) and 15 (COM3-01-25), COM3 Level 1
      By Christophe Jouffrais, Wei Tsang Ooi, Cheston Tan

      Day 3 – 26 June 2024 at NUS

      Satellite workshop on Actionable eXplainable AI

      Location: NUS COM3-02-59 – Meeting Room 20 @ COM3 (Level 2)

      Organised by Vassilis Christophides, Michele Linardi and Aikaterini Tzompanaki, Jin-Song Dong, Huang Zhiyong

      8.45 – 9.15 am Welcome
      09.15 – 10.15 am Keynote Dr. Zhe Hou
      Global Logical Explanations, Feature Importance and Adversarial Samples
      10.15 – 10.45 am Coffee break
      10.45 am – 12.15 pm Actionable Explanations for Graph, Sequence & IID Data

    • Aikaterini Tzompanaki (Assistant Professor CYU) – Why-Not Explainable Graph Recommenders
    • Etienne Vareille (Ph.D. Student ENSEA) – Causal Variable Selection in Multivariate Time Series with Multiple Solutions
    • Nikos Myrtakis (Ph.D. Student ENSEA) (Ph.D. Student CYU – ETIS Lab – MIDI Team) Data Debugging using Influence-based Model Explanations
    • 12.15 – 2.00 pm Lunch break
      2.00 – 3.30 pm Actionable Explanations for Deep Learning (DL) Models

    • Xianglin Yang (Ph.D. Student NUS) – XAI for Debugging Training Strategies
    • Ruofan Liu (Ph.D. Student NUS) – Data Influence for Metric Learning Models
    • Michele Linardi (Assistant Professor CYU) – XAI for Model Adaptation in Crop Mapping
    • 3.30 – 3.45 pm Coffee break
      3.45 – 4.15 pm XAI Foundations

    • Jin-Song Dong (Professor NUS) Silas — A machine learning tool built from a logical background
    • 4.15 – 5.00 pm Closing Remarks & Discussion

      The CYU-NUS workshop on Actionable eXplainable AI will follow SINFRA, on June 26.

      Workshop on Actionable eXplainable AI:

      During the last years, several methods of Explainable Artificial Intelligence (xAI) have been developed especially with the goal to make opaque machine-learned models (e.g., Deep Learning (DL)) transparent, interpretable, and comprehensible. However, in many real use cases, e.g., for debugging ML models and data, or transferring models across domains, merely establishing transparency, interpretability and comprehensibility is not enough.

      Actionable xAI (aXAI) focuses on xAI methods that support safer and more effective human/AI-decision making in various disciplines (e.g., healthcare, precision agriculture, security). In particular, aXAI focuses on more expressive forms of explanations that can answer not only why questions (why do we obtain a specific prediction for a given input data?) but also why-not (why don’t we obtain an alternative prediction for particular input data?), how-to (what are the necessary actions to change the prediction of specific input data?) and what-if (what are the necessary and minimal sets of actions on input data required to obtain an alternative prediction prediction?). Answers to these questions are crucial to act on the models and data used in various classification, regression or recommendation tasks.

      The axAI workshop we propose aims to bring together interdisciplinary researchers from IPAL who are working on complementary aspects of Explainable Artificial Intelligence and who want to present and discuss new, groundbreaking research that goes beyond testing existing work in new application areas.
      This event will be co-organized by members of the DATA&AI team of ETIS (French partner) and members from NUSAil  (Signaporean partner from National University of Singapore Artificial Intelligence Laboratory). Both partners are affiliated to IPAL.

      Vassilis Christophides, Michele Linardi and Aikaterini Tzompanaki (DATA&AI team of ETIS lab) are the French organizer, whereas Jin-Song Dong and Huang Zhiyong are the responsible for the organization at the Singaporean side.

      Poster session

      The poster templates can be downloaded here: