INDUSTRIAL ARTIFICIAL INTELLIGENCE FORUM
James Clark Hall, Wednesday, December 04, 2024
7:00 AM Registration, Breakfast & Networking
8:00 AM HOST WELCOME AND INTRODUCTION
Dean, A. James Clark School of Engineering and Nariman Farvardin Professor
Professor and Chair, Mechanical Engineering Department
8:20 AM TRENDS OF AI AND INDUSTRIAL AI AND PRODUCTIVITY TRANSFORMATION IN 2030-2040
Director, Industrial AI Center, Clark Distinguished Professor
Mechanical Engineering
8:50 AM GOVERNMENT PERSPECTIVES ON AI
Representatives from both state and federal government as well as policy institution will share their perspectives, challenges, opportunities initiatives, and progress in AI.
Moderator: Prof. Jay Lee, UMD.
9:40 AM GLOBAL PERSPECTIVES ON AI DEVELOPMENT AND POLICY
10:30 AM BREAK
10:40 AM INDUSTRY PERSPECTIVES ON INDUSTRIAL AI
Industrial leaders will speak about their unmet needs and major challenges in applying AI to real-world applications.
Moderator: Prof. Jay Lee, UMD.
12:40 PM LUNCH AND NETWORKING
2:00 PM INDUSTRIAL AI RESEARCH AND PARTNERSHIP HIGHLIGHTS
Research presentation from Industrial AI Center and UMD faculty.
Moderator: Prof. Jay Lee, UMD.
Metaverse and Digital Twin Modeling and Simulation, Prof. Miao Yu and Prof. Bala Balachandran
Dr. Pradeep Kundu, KU Leuven
Prof. Carlos Eduardo Pereira, “Competence Center on Digital Agriculture - AI applications”, UFRGS and SENAI-RS, Brazil
NTU Singapore Industrial AI Center, Prof. Man Pun Wan, Prof. Tuan Tran and Prof. Mir Feroskhan, NTU Singapore
Dr. Huey Yuen Ng, SIMTech AI in Manufacturing, Singapore
Peter Schrader, Fraunhofer IPA
Ashley Gasque, IOP Publishing, Special Presentation on New
Journal Machine Learning: Engineering (Online)
3:45 PM BREAK
4:00 PM SELECTED UMD RESEARCH AND PROJECT PRESENTATION
Presentations from University of Maryland Research Institutes and Centers on AI-Related Research:
Prof. Peter Chung, Dept. of Mechanical Eng
Dr. Reza Ghanadan, UMD AI in College of Engineering
Prof. Michael Pack, Center for Advanced Transportation Technology Laboratory (CATT)
Prof. Michael Pecht, Center for Advanced Life Cycle Engineering (CALCE)
Prof. Bongtae Han, Laboratory for Optomechanics and Micro/nano Semiconductor/Photonics Systems, Mechanical Engineering
Prof. Dinesh Manocha, Dept. of Computer Science
5:30 PM POSTER SESSION/EXHIBITS & RECEPTION AND NETWORKING
Highlights of diversified AI research for industrial systems with posters.
Exhibits from different companies to showcase AI products and technologies.
INDUSTRIAL ADVISORY BOARD MEETING
(closed-door meeting for Industrial AI Center members, pending members, and invited guests )
Thursday, December 05, 2024
7:00 AM REGISTRATION, BREAKFAST & NETWORKING
8:00 AM INTRODUCTION TO INDUSTRIAL AI CENTER MEMBERSHIP STRATEGY, IMPACTS, AND ROADMAP
Founding Director, Center of Industrial AI Center Professor Jay Lee will provide an overview of Industrial AI Center’s operations including the membership strategy, company project formulation, company training, and growth roadmap to drive impact for its members.
Jay Lee
Director, Industrial AI Center, Clark Distinguished Professor
Mechanical Engineering
8:15 AM NEW MEMBER, PARTNER, AND INVITED PRESENTATION
Representatives from the industry will share their perspectives, challenges, opportunities, initiatives, and progress in Industrial AI. Attendees can expect to hear from platform providers, solutions providers, OEMs, and end-users.
Moderator: Prof. Jay Lee, UMD.
Ben Laskowski, Analatom
Leon Chan, Alpha X
Simon Lee, ASE Group
Alice Wu, Cosen
Connie Jiang/Joe Wang, Foxconn Interconnect Technology (FIT)
Takanobu Minami, Komatsu
Vincent Chan, LatticeWork
Shaw Sheng, NREL
Chun Chun, Hsieh, o9 Solutions
Che-Chieh Chen, PMC
Gavin Lee, Winbond
Chee Kheng Lim, Western Digital
Lee Tiedrich, NIST, Duke Univ.
Ken Ueno, Toshiba Corporation, Japan (Video)
Frank Lai/Matthias Huber, SuperMicro (Online)
12:00 PM LUNCH BREAK (Lunch Box and Poster Session)
1:00 PM INDUSTRIAL AI CORE RESEARCH PROJECTS
Industrial AI Team will give in-depth presentations about technologies and tools including Industrial Large Knowledge Model, Data Foundry, Non-Traditional Machine Learning Methods
Non-Traditional Machine Learning
(Transfer Learning and Domain Adaptation, Topological Data Analytics (TDA), Stream-of-X, Similarity-based Machine Learning, etc.)Industrial Large Knowledge Model and Retrieval Augmented Generation (RAG).
Data Quality
Jae Gyeong Choi, UNIST (new researcher) (Video)
2:30 PM INDUSTRIAL AI TALENT DEVELOPMENT
Moderator: Prof. Jay Lee, UMD.
EPFL Industrial AI Short Course, Elaine Moran, EPFL (Online)
Taoyuan Taiwan Industrial AI Training
Industrial AI Training and Workforce Development Plan in Michigan
Industrial AI Training: Aero-Engine Datasets, Sarah Wielgosz, Mark Rozzer, Ali Davoodanhosseini
Industrial AI Training: Semiconductor Manufacturing, Justin Ryan, Nathan Hill, Haoguang Wang
3:30 PM OPEN DISCUSSIONS
Industry members and invited guests will provide feedback about the proposed research areas and discuss the priorities for research and education.