The state of Explainable AI/ML, a topic of much interest during the NAFEMS Americas April 2021 virtual event on, "AI, Data Driven Models & Machine Learning: How Will Advanced Technologies Shape Future Simulation Processes?" had attendees asking for more discussion.

In response, this one-hour panel discussion continued the conversation by setting the context of Explainable AI/ML as part of the larger topic on Artificial Intelligence trustworthiness. The panel addressed some unanswered audience questions from the last discussion, as well as hosting a live Q&A with participants.

About the Panellists

Dr. Mahmood Tabaddor, Manager, Predictive Modeling and Analytics, UL LLC

Dr. Mahmood Tabaddor has been involved in modeling and simulation for over 25 years, and is currently the Manager for the Predictive Modeling and Analytics Team at UL. He is a member of ASME V&V 50 and a member of the NAFEMS Americas Steering Committee. He has a graduate degrees in Mechanical Engineering from University of Michigan, Ann Arbor and Engineering Mechanics from Virginia Tech. His doctoral dissertation focused on the dynamics of nonlinear systems.

 Dr. Vladimir Balabanov, Associate Technical Fellow at Boeing Commercial Airplanes

Dr. Vladimir Balabanov has worked in the area of optimization and software development for more than 25 years. He has authored more than 70 research papers on optimization methods and applications. For 11 years he worked for Vanderplaats Research and Development, developing the commercial optimization and integration software VisualDOC that is used worldwide. Currently, Vladimir is an Associate Technical Fellow at Boeing Commercial Airplanes. His work is focused on improving performance of metallic and composite structures using production tools in combination with optimization and Machine Learning. He is actively involved in American Institute of Aeronautics and Astronautics (AIAA), where he chairs Multidisciplinary Analysis and Optimization (MDO) Technical committee. At NAFEMS, Vladimir chairs the Engineering Data Science Work Group.

 Dr Peter Chow, Research Fellow, Fujitsu UK

Dr. Peter Chow is a Research Fellow at Fujitsu UK. He received his BSc Hons and PhD from University of Greenwich, London, UK, 1988 and 1991 respectively (Ph.D. in Computational Science and Engineering). His current focus is Societal Digital Twin to a more sustainable and belonging world. AI for simulation is a key driver for verification and validation of the virtual and physical worlds, with real-time demands and responses are some of the challenges. Specialties include AI for simulation (AI4SIM) and AI for non-destructive testing (AI4NDT). His previous role at Fujitsu Laboratories of Europe was head of Industry 4.0 and innovation covering Engineering Cloud and AI for Design & Manufacturing.

 Dr. Ankit Patel, Assistant Professor in ECE at Rice University and Neuroscience at Baylor College of Medicine

Dr. Ankit B. Patel is currently an Assistant Professor at the Baylor College of Medicine in the Dept. of Neuroscience, and at Rice University in the Dept. of Electrical and Computer Engineering. Ankit is broadly interested in the intersection between machine learning and computational neuroscience, two research areas that are essential for understanding and building truly intelligent systems, with a focus on learning abstractions. In his current role, he is continuing to pursue the unification of traditional hierarchical machine learning with deep neural networks, with applications to a variety of fields, including neuroscience, robotics, and particle physics.