Organizers

Dr. Madhusudan Singh, IEEE Senior Member

Penn State University, University Park, USA 

Madhusudan Singh is an Associate Teaching Professor and leads the Blockchain Data Intelligence (Blockchain Innovation) Lab in the Department of Computer Science & Engineering in the College of Engineering at Penn State University, University Park, PA. Dr. Singh is experienced in Artificial Intelligence (AI), Blockchain Technology, Data Science, Quantum Computing, and Security with privacy, and has worked in areas related to Autonomous Cars, Vehicle Data Analysis and Security with privacy, Health Information Management, Industrial Internet (industry 4.0). He has served in both Academic research and Industrial R&D. Dr. Singh has most recently researched the design and integration of decentralized network security with data privacy of Autonomous vehicles and Health Information Management.

Prof. Dhananjay Singh, IEEE Senior Member 

Penn State University, University Park, USA 

Dr. Dhananjay Singh is a Teaching Professor of Entrepreneurship and Innovation at Penn State's College of Information Sciences and Technology, with over 15 years of experience as a researcher, educator, and Entrepreneur in the USA and South Korea. He directs the ReSENSE Lab, fostering innovative solutions for smart community services. A Senior Member of IEEE and ACM, Dr. Singh’s expertise spans human-computer interaction, AI-powered IoT, intelligent vehicles, and applied data sciences. 

Kei Sakaguchi

Institute of Science Tokyo, Japan

Kei Sakaguchi received the M.E. degree in information processing and the Ph.D. degree in electrical and electronics engineering from Tokyo Institute Technology, Tokyo, Japan, in 1998 and 2006, respectively, where he is currently working as the Dean with Tokyo Tech Academy for Super Smart Society and a Professor with the School of Engineering. His current research interests include B5G/6G cellular networks, millimeter-wave communications, wireless energy transmission, V2X for automated driving, and super super-smart society. He was the recipient of the Outstanding Paper Awards from SDR-Forum and IEICE in 2004 and 2005, respectively, the three Best Paper Awards from IEICE Communication Society in 2012, 2013, and 2015, and the Tutorial Paper Award from IEICE Communication Society in 2006. He is a Fellow of IEICE.

Ziran Wang

Purdue University, USA

Ziran Wang (Senior Member, IEEE) received the Ph.D. degree in mechanical engineering from the University of California at Riverside, Riverside, CA, USA, in 2019. He is a Tenure-Track Assistant Professor with the College of Engineering, Purdue University, West Lafayette, IN, USA, where he leads the Purdue Digital Twin Lab. Prior to this, he was a Principal Researcher with Toyota Motor North America, Mountain View, CA, USA. He is the author of five book chapters, 50+ refereed papers, and 50+ patent applications. His research focuses on autonomous driving, human-autonomy teaming, and digital twins. Dr. Wang’s research achievements have been demonstrated at the Consumer Electronics Show and acknowledged by the U.S. Department of Transportation Dissertation Award, the IEEE “Shape the Future of ITS” 1st Prize Award, and five other best paper awards from IEEE and SAE. He is an Associate of four academic journals, including IEEE TRANSACTIONS ON NTELLIGENT VEHICLES and IEEE INTERNET OF THINGS JOURNAL. He serves as the Founding Chair of the IEEE Technical Committee on Internet of Things in Intelligent Transportation Systems, a member of three other IEEE technical committees, and a Technical Program Committee Member of multiple IEEE and ACM conferences. 

Tao Yu

Institute of Science Tokyo, Japan

Tao Yu received his M.E. degree from the Communication University of China in 2010, and his Dr.Eng. degree from the Tokyo Institute of Technology (now Institute of Science Tokyo) in 2017. After completing his doctorate, he worked as a postdoctoral researcher from 2017 to 2022 in School of Engineering at Tokyo Tech. Since 2022, he has been a specially appointed associate professor at the Tokyo Tech Academy for Super Smart Society (now Academy of Super Smart Society, Science Tokyo). His research interests include smart mobility, autonomous driving, digital twin, V2X, UAV communication, mmWave, sensor networks, localization, antenna design, and building energy management.

Mihai Kocsis

FZI Forschungszentrum Informatik Karlsruhe, Germany

Mihai Kocsis received a M. Sc. in computer science from the University in Hagen. In 2021, he completed a cooperative Ph.D. in the field of industrial engineering with a focus on autonomous vehicles in pedestrian environments at the University in Brasov and the University of Applied Science in Heilbronn. He joined FZI Research Center for Information Technology in 2024. Currently, his work is focused on the development of autonomous shuttles, V2X components, and services on demand using fleets of autonomous vehicles. His research interests include probabilistic sensor data fusion, software architecture, smart cities, and artificial intelligence in self-driving cars.

Abhijit Sarkar

Virginia Tech, Virginia, USA

Dr. Abhijit Sarkar is a Senior Research Associate at the Virginia Tech Transportation Institute (VTTI) and affiliate faculty at the Sanghani Center, leading the Computer Vision and Machine Learning team. His research focuses on automated driving systems, driver attention monitoring, intersection safety, UAVs, and multimodal sensor processing using naturalistic driving data, all at the intersection of AI and transportation. With a Ph.D. in Computer Vision and Remote Health Monitoring from Virginia Tech and advanced degrees from IIT Kharagpur and Jadavpur University, Dr. Sarkar combines expertise in AI and engineering to advance safety and innovation in transportation.

Marc-Rene Zofka

FZI Forschungszentrum Informatik Karlsruhe, Germany

Marc René Zofka received the B.Sc. degree in information engineering from the University of Konstanz in 2010 and the M.Sc. degree in computer science from the Karlsruhe Institute of Technology in 2012. He is currently the Department Manager of the TCS FZI Research Center for Information Technology. His research interests include validation, verification, and testing methods of highly automated driving functions, especially on proving grounds and test areas supported with smart and connected infrastructure testbeds.

Tobis Fleck

FZI Forschungszentrum Informatik Karlsruhe, Germany.

Tobias Fleck received an M.Sc. in computer science, with a special focus on cognitive systems, from the Karlsruhe Institute of Technology (KIT). Since 2017, he has joined the FZI Research Center for Information Technology as a researcher. His research interests include connected automated driving, in particular infrastructure-supported cooperative perception, and sensor fusion. 

Marius J. Zöllner

FZI Forschungszentrum Informatik Karlsruhe, Germany

J. Marius Zöllner received the degree in computer science, with special focus on artificial intelligence and robotics, from the Karlsruhe Institute of Technology (KIT) and the Ph.D. degree from KIT in 2005. Since 1999, he has been with the FZI Research Center for Information Technology, where he became the Division Manager in 2006. Since 2008, he has been a Professor of applied technical cognitive systems with KIT and the Director with FZI. Since 2012, he has been member of the Executive Board of the FZI. His main research interests include automated driving, service robotics, and machine learning. 

Raoul Zöllner

Heilbronn University, Germany 

Raoul D. Zöllner received his Ph.D. in AI and Humanoid Robots from KIT and DLR in 2005. For four years, he was leading several projects at Corporate Research Siemens before he became a full professor at Heilbronn University of Applied Science in 2009. He has held various positions at the University, including Vice Dean of the Faculty for Electronics and Mechanics for 7 years. Since 2017, he has been Vice President Research and Head of the Institute for Automotive Technology and Mechatronics, a member in several Advisory Boards. His main research interests include autonomous systems and machine learning.