Doctoral Consortium program

A preliminary version of the proceedings can be found here: ICCBR_DC_Preliminary_Proceedings

Sunday (Sep 11)

We will have a 2-hour (17-19) session to get to know each other. This will take place at Brasserie l’Excelsior 50 (Rue Henri-Poincaré, 54000 Nancy, Open Location in Google Maps). Afterward, we will join the other ICCBR participants for dinner at Grand café (Foy 1 Pl. Stanislas, 54000 Nancy, Open Location in Google Maps).

17:30 Opening
17:40 Introduction of the Participants
18:00 Meeting of mentors and mentees 1:1
19:00 Final Remarks and Closing

Monday (Sep 12)

Full day DC program between 9:00-15:30. Each student will be asked to present her/his research proposal in 20 min, followed by a 10 min Q&A lead by your mentor.

Session I

9:15 Opening
9:30 Craig Pirie: Explaining and Upsampling Anomalies in Time Series Data (Mentor: Mark Keane)
10:00 Michael Clemens: The Three E’s of Explainability in Collaborative Computational Co-Creativity: Emotionality, Effectiveness, and Explicitness (Mentor: David Wilson)

10:30-11:00 Coffee Break

Session II

11:00 Greta Warren: Counterfactual Explanations for eXplainable AI (XAI) (Mentor: David Leake)
11:30 Paola Marin: The Use of Case-Based Reasoning for Personalizing Musculoskeletal Pain Treatment Recommendations (Mentor: Nirmalie Wiratunga)
12:00 Ciara Feely: Using Machine Learning Techniques to Support Marathon Runners (Mentor: Kyle Martin)
12:30 Malavika Suresh: CBR For Interpretable Response Selection In Conversational Modelling (Mentor: Rosina Weber)
13:00-14:30 Lunch Break

Session III

14:30 Pedram Salimi: Addressing Trust and Mutibility Issues in XAI utilising Case Based Reasoning (Mentor: Jean Lieber)
15:00 Eoin Delaney: Case-based Explanation for Black-Box Time Series and Image Models with Applications in Smart Agriculture (Mentor: Mirjam Minor)
15:30 Mark van der Pas: Developing a Decision Support System leveraging Distributed and Heterogeneous Sources: Case-Based Reasoning for Manufacturing Incident Handling (Mentor: Stewart Massie)

Additional Contribution (not on-site)

Zachary Wilkerson: DL-CBR Hybridization for Feature Generation and Similarity Assessment (Mentor: David Aha)

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