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--- xrai:start [2024/07/27 13:45] – [Important Dates] sbk
+++ xrai:start [2024/09/20 07:40] (current) – [Workshop Schedule] sbk
@@ Line 4: / Line 4: @@
 The 1st edition of X-RAI will be at the [[https://2024.ecmlpkdd.org/|ECML-PKDD 2024]] conference.
 ===== Organizers =====
-  * Sepideh Pashami, Halmstad University, Sweden, sepideh.pashami@hh.se
+  * Sepideh Pashami, Halmstad University and RISE, Sweden, sepideh.pashami@hh.se
   * Joao Gama, University of Porto, Porto, Portugal, jgama@fep.up.pt
   * Bruno Veloso, University of Porto, Porto, Portugal, bveloso@gmail.com
@@ Line 15: / Line 16: @@
   * Szymon Bobek, Jagiellonian University, Krakow, Poland, szymon.bobek@uj.edu.pl
-{{:xrai:uj-logo.jpg?200 |}}{{:xrai:halmstad-logo.svg?200|}}{{:xrai:porto-logo.jpg?200 |}}
+{{:xrai:uj-logo.jpg?200 |}}{{:xrai:halmstad-logo.svg?200|}}{{:xrai:porto-logo.jpg?200|}}
+{{:xrai:rise.svg ?200 }}
+==== Keynote Speaker ====
+<WRAP column 15%>
-===== Tentative Tutorial Schedule =====
+</WRAP>
-  - Introduction
+{{:xrai:raina.jpeg?200 |}}
-  - AI for industrial applications(45m)
+<WRAP column 75%>
-    - Predictive maintenance
-    - Optimizations of operations
+**Speaker**: Rafia Inam, Senior Research Manager, at Ericsson AB and Adjunct Professor, at KTH Royal Institute of Technology
-    - Decision support
-  - Explainable AI including types of Explanations and evaluations (50m)
+**Title**: Use of Explainable AI in Telcom domain
-  -  Robustness for ML (40m)
-  - Use Cases (60m)
-    - Metro Trains
+**Biogram**:
-    - Commercial Vehicles
+Rafia Inam is a senior research manager at Ericsson Research and Adjunct Professor at KTH in research area Trustworthy Artificial Intelligence, Sweden. She has conducted research for Ericsson for the past 8 years on 5G for industries, 5G network slices and management, using AI for automation, service modeling for Intelligent Transport Systems. She is specialized in automation and safety for CPS and collaborative robots, trustworthy AI, explainable AI, explainable RL, risk assessment and mitigations using AI methods, reusability of real-time software. She wonEricsson Top Performance Competition 2021 on her work on AI for 5G network slice assurance, and was awardedEricsson Key Impact Award 2020,and Key contributor award 2020, 2023,.
-    - Steel Plant
-  - Discussion and Open Questions (10m)
+Rafia received her Ph.D. from Mälardalen University, Sweden, in 2014 on predictable real-time embedded software. She is a Program Committee member, referee, guest editor for several international conferences and journals. Rafia has co-authored 40+ refereed scientific publications and 55+ patent families. She has wonbest paper awards on her two papers: “Towards automated service-oriented lifecycle management for 5G networks”, at the IEEE’s 9th International Workshop on Service Oriented Cyber-Physical Systems in Converging Networked Environments (SOCNE) in 2015, and “Support for Hierarchical Scheduling in FreeRTOS” in 16th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA’11), September 2011.
+</WRAP>
+<WRAP clear></WRAP>
+===== Tutorial Schedule =====
+^ Time          ^ Topic                                                                       ^
+| 09:00 - 09:10 | Introduction                                                                |
+| 09:10 - 10:10 | AI for Industrial Applications such as Predictive Maintenance                |
+| 10:10 - 11:00 | Explainable AI, including Types of Explanations and Evaluations              |
+^^
+| 11:00 - 11:20 | Break                                                                       |
+^^
+| 11:20 - 11:50 | Robustness in Machine Learning                                               |
+| 11:50 - 12:20 | Metro Train Use Case and Neurosymbolic Explanation                           |
+| 12:20 - 12:35 | Steel Plant Use Case                                                        |
+| 12:35 - 12:50 | Commercial Vehicle Use Case                                                 |
+| 12:50 - 13:00 | Discussion and Open Questions                                                |
+==== Workshop Schedule ====
+The workshop will take place on Friday, 13th of September 2024.
+^Time^Title^Speaker^
+| 14:00-14:50 |**Keynote: Use of Explainable AI in Telcom domain**| Rafia Inam|
+^^
+| 14:50-15:00 | **Break**||
+^^
+| 15:00-15:20 | **Edge-MixShap: Shapley Value Attributed Explainable and Robust Model for Cardiovascular Disease Classification Using Electrocardiogram** | Arijit Ukil |
+| 15:20-15:40 | **A SAT-based approach to rigorous verification of Bayesian networks** |Ignacy Stępka|
+| 15:40-16:00 | **Forecasting Auxiliary Energy Consumption for Electric Heavy-Duty Vehicles** | Yuantao Fan|
+===== Workshop information ======
-===== Workshop ======
 ==== Important Dates ====
    * **Submission Deadline**:  <del>2024-06-15</del> 2024-06-22
@@ Line 39: / Line 72: @@
    * **Workshop Date**: 2024-09-13
-==== Accepted Papers ====
-  * Edge-MixShap: Shapley Value Attributed Explainable and Robust Model for Cardiovascular Disease Classification Using Electrocardiogram
-  * A SAT-based approach to rigorous verification of Bayesian networks
-  * Forecasting Auxiliary Energy Consumption for Electric Heavy-Duty Vehicles
 ==== Aims and Scope ====
 The X-RAI tutorial & workshop aims to bring industrial AI professionals together with explainability experts to discuss the latest developments in XAI and their practical applications as well as theoretical works aiming at solving real-life problems in industrial settings. The tutorial & workshop will provide an opportunity for attendees to learn about the latest research, best practices, and challenges in this area. It is an opportunity to bridge researchers and engineers to discuss emerging topics and the newest trends. The integration of explainability in Industry 4.0 and 5.0 is crucial to ensure AI systems' reliability, trustworthiness, transparency and robustness.