Lee Der-Horng is an academician of the Singapore Academy of Engineering and a supported expert of the Zhejiang Province Kunpeng Action Program. He is a Qiushi Chair Professor at Zhejiang University, and the Dean of the Zhejiang University-University of Illinois Urbana-Champaign Institute. He holds a Ph.D. from the University of Illinois. He is also an Executive Committee member of the Singapore Academy of Engineering, as well as the Leader of the Transportation Engineering Group. Before joining Zhejiang University in 2021, he was a tenured professor in the Department of Civil and Environmental Engineering at the National University of Singapore, and an elected member of the NUS Senate. In 2002, he was named one of the “Innovators Under 35” by MIT Technology Review and has been listed among “World’s Top 2% Scientists” published by Stanford University. He has also been named as “Most Cited Chinese Researcher” by Elsevier. According to the Google Scholar database, Professor Lee ranks first in the field of maritime transportation, and third in the fields of port logistics, public transportation, and urban travel, and fifth in the field of transportation policy. Professor Lee’s research focuses on smart port and shipping logistics systems, maritime transportation systems, urban mobility systems, urban rail transit systems, transportation planning and policy, etc. He has made prime academic contributions in the fields of large-scale container port logistics operations, intelligent urban rail transit, ultra-flex autonomous mobility system, and high-fidelity traffic simulation. As a foreign academician working full-time in China, Professor Lee was received by President Xi Jinping in Beijing in October 2019.

Research Areas:
Port Logistics, Maritime Transportation, Urban Mobility, Public Transportation, Transportation Policy

Prof. MA Hao is the Vice Dean of ZJUI. He received the B.S., M.S. and Ph.D. degrees from Zhejiang University, Hangzhou, China, in 1991, 1994 and 1997 respectively, all in Electrical Engineering. Since 1997, he worked as a lecturer, associate professor and professor at Zhejiang University. He also served as Director of Academic Committee of China Power Supply Society and Vice Dean of college of electrical engineering, Zhejiang University (2013-2017), AdCom member of IEEE Industrial Electronics Society (2014-2015), Technical Pro ergy Conversion, IEEE IECON 2013, and Special Session Co-chair of IEEE IECON 2017.

Prof. Hongwei Wang is a tenured professor at ZJUI where he services as the vice dean and the director of the data and information sciences research program. He is the vice president of the Information Technology Branch of the Zhejiang Association of Scholars from Overseas. Prof. Wang serves as the associate editor of the IET Collaborative Intelligent Manufacturing Journal and an editorial board member of Journal of Service Oriented Computing and Applications. He has been invited to deliver keynote speeches twice in international conferences, and has won four best paper awards. Prior to joining Zhejiang University, he held a permanent academic position at the University of Portsmouth, UK. Prof. Wang got his bachelor’s degree from Zhejiang University, China, his master degree from Tsinghua University, China, and his Ph.D. degree from the University of Cambridge, UK, respectively.
Prof. Wang has a broad interest in the application of AI and Knowledge-Based Systems (KBS) in the design, analysis, manufacture and maintenance of complex systems. He has been focusing on industrial knowledge graph, knowledge-based reasoning and decision making, fault diagnosis, and multimodal learning in the past few years. He has received continuous research grants from EPSRC, NSFC, Key Project of the S&T Ministry, Zhejiang Natural Science Foundation, etc. His research outcomes have underpinned the development of industrial software systems in different areas, which have led to the winning of several important awards and honors such as the Wuwenjun AI award. He has published over 140 papers in well-established journals and conferences such as IEEE Trans. on Services Computing, IEEE Trans. on Neural Networks and Learning Systems, IEEE Trans. on Industrial Informatics, IEEE Trans. on SMC: Systems、Energy, Neurocomputing, Energy, Robotics and Computer-Integrated Manufacturing.

Introduction：
Dr.Chen is an assistant professor with ZJU-UIUC Institute, International Campus, Zhejiang University. His research interests include multi-physics computation methods and their applications for micro/nano-scale electronic devices and 3-D ICs. Dr.Chen received the Ph.D. degree in electrical and computer engineering from University of Florida, Gainesville, FL, USA, in 2014, the M.E. degree in electronic engineering from Shanghai Jiao Tong University, Shanghai, China, in 2009, and the B.E. degree in information engineeringfrom Xi’an Jiaotong University, Xi’an, China, in 2006. Dr.Chen has published over 20 peer-reviewed journal papers as well as 1 book chapter. He has been awarded for several awards in the past, including Chinese Government Award for Outstanding Self-financed Students Abroad, Best Student Paper Award in 2016 IEEE MTT-S IMWS. Dr. Chen also served as Technical Program Committee Member of IEEE MTT-S IMWS 2016, IEEE EDAPS 2017.

Direction：
Multi-physics Modeling and Computation of 3D Integrated Circuits and Device, Nano Electronics, Computational Electromagnetics

Director of Academic Affairs Office for Graduates. Responsible for Institute's graduate program management, etc.

Introduction：
Prof. Ruisheng Diao obtained his B.S. in Electrical Engineering from Zhejiang University in 2004, M.S. degree in Electric Power Systems & Automation from Zhejiang University in 2006 (Advisor: Prof. Zheng Xu, IEEE Fellow), and Ph.D. degree in Electrical Engineering from Arizona State University in 2009 (Advisor: Prof. Vijay Vittal, Member of the U.S. National Academy of Engineering, IEEE Fellow). His research areas include high-fidelity power system modeling, simulation and analysis, application of HPC, optimization and control and artificial intelligence in power systems. He served as a team lead, Advanced Grid Analytics, and a deputy program manager at the Pacific Northwest National Laboratory (affiliated with the U.S. Department of Energy) from July 2009 to May 2018 (funding level: $2-3M/year). Then, he joined GEIRI North America as Deputy Department Head, AI&System Analytics, and the Principal Investigator of developing AI-related technologies for power systems. He led and participated more than 30 R&D projects funded by the U.S. Department of Energy, multiple U.S. Power Companies and the State Grid Corporation of China, with a total funding level of approximately $30,000,000. He published around 100 SCI/EI indexed peer-reviewed articles, 1 book chapter, filed 19 patent applications (including 13 U.S. patents, 2 of which were granted by USPTO), and owned multiple software copyrights. Prof. Diao is the recipient of the 2018 R&D 100 Awards (one of the 100 most technologically significant new products of the year in software/services), 3 IEEE PES best paper awards (2017-2019, including 1 IEEE PES conference prize paper award), the MPCE Best Paper Award as well as the U.S. DOE PNNL Outstanding Performance Award (5 times). His team won the Championship of the 2019 Learn to Run Power Network (L2RPN) Global Power AI Competition. Prof. Diao is a senior member of IEEE, a registered professional engineer (PE) at Washington State, USA and serves as a R&D project reviewer for the U.S. DOE and power companies. He is on the editorial board for multiple top journals in power systems, including IEEE Transactions on Power Systems, IEEE Access, IET Generation, Transmission&Distribution, and International Journal of Numerical Modelling. Multiple research prototypes developed by Prof. Diao’s team were commercialized by vendors, which are now widely used by power companies in North America and China.

Direction：
Power system security and stability; power grid modeling, simulation and analysis; application of HPC and Artificial Intelligence; planning, operation and control of new-style power system

Introduction：
He earned the Bachelor's and Master's Degrees at Tsinghua University in China, and obtained his Ph.D. in the ECE department working with Prof. William P. King in 2014. He then joined IBM T. J. Watson Research Center as a postdoctoral research scientist for almost 3 years. He has led projects in both academia and industry, resulting to 20 peer-reviewed journal papers published in international-recognized journals including Advanced Materials, PNAS, Biomaterials and Nanotechnology. Moreover, he has a strong application-oriented mindset and filed 18 US patent disclosures (4 patents granted). In addition, he has also assisted and led several successful funded proposals including a 2 million dollars NSF EFRI award and a 200,000 dollars industrial award. He is interested in advanced nanomanufacturing, bio-inspired sensing, micro/nano-sensors, lab on chip. He is passionate in applying technology to the real world. He is now leading Nanomanufacturing and Biomimetics Research Group at ZJUI. Exciting research projects are currently active! Students (undergrads and graduates) and postdoc positions are open now! Please contact Dr. Huan Hu huanhu@intl.zju.edu.cn if interested in joining Nanomanufacturing and Biomimetics Research Group. More information can be found on the group webpage: http://zjui.intl.zju.edu.cn/en/content/870173

Direction：
Advanced Nanomanufacturing，Bio-inspired micro/nano sensors，Lab on a Chip integrating Nanotechnology

Introduction：
Dr Simon Hu is an Assistant Professor at the ZJU-UIUC Institute at Zhejiang University. He has a background in Civil Engineering and specialises in Transport and Environment Engineering. In 2006, he completed his Master degree in Transport and Sustainable Engineering from Imperial College London; he earned his PhD in Transport System Engineering in the same department in 2011. He is a member of Chartered Institute of Highways and Transport Engineering (CIHT) and Institute of Electrical and Electronics Engineering (IEEE). In the past, he obtained research grants and undertook research projects through the Royal Society, Engineering and Physical Sciences Research Council (EPSRC), UK Natural Environmental Research Council (NERC), Department for Transport (DfT), European Commission, INNOVATE UK and industry. To date, he has obtained total grant value of more than £2million. He has published over 10 peer reviewed journal papers, 30 conference proceedings and 2 government reports.

Direction：
Transportation and Environment, Vehicle Emission Measurement and Modelling, Connected and Autonomous Vehicles, Transportation Planning and Management, Sustainable Urban Transportation Systems

Binbin Li is an Assistant Professor in the Zhejiang University-University of Illinois Urbana-Champaign Institute at the Zhejiang University, International Campus. He obtained his Ph.D. in Civil Engineering from the University of California-Berkeley in 2016. Before joining ZJU, he worked as a research associate at the University of Liverpool. Prof. Li’s research focuses on developing innovative statistical methods to address safety, sustainability and resilience issues of the built civil infrastructure systems including bridges, buildings, and road/rail networks. His specific interests include Bayesian system identification, operational modal analysis, infrastructural network modeling and field test, for structure and infrastructure health management and resilience assessment. The ultimate goal of Prof. Li’s work is to equip the civil infrastructure systems with a smart brain so that they can sense, process and react properly to the external excitations, e.g., earthquakes, windstorms. Fully funded PhD positions in civil engineering are available. Motivated graduate and undergraduate students are welcome to apply by contacting Prof. Li bbl@zju.edu.cn. Postdoc positions are also open. Please contact Prof. Li for more information.
Direction：
Structural Dynamics, Risk & Uncertainty, Structural Health Monitoring, Bayesian statistics

Prof. Wee-Liat Ong is an Associate Professor at ZJUI. He graduated with a B.Eng in Mechanical Engineering from the National University of Singapore (NUS) and was the valedictorian of his class and recipient of the IES gold medal and Lee Kuan Yew gold medal in 2002. He also received a M.Eng from NUS in 2004 where he developed a robot for performing experiments used in drug discovery. In 2015 he received his Ph.D. in Mechanical Engineering at Carnegie Mellon University under Prof. Jonathan Malen and Prof. Alan McGaughey, where he studied nanoscale heat transfer focusing on organic-inorganic nanostructured materials using both experimental and simulation techniques. Before becoming a faculty at ZJUI, he was a joint post-doctoral fellow at Columbia University and Carnegie Mellon University working with chemists to characterize novel hybrid materials.

Introduction：
Dr Fangwei Shao graduated from Fudan University with BS and MS in Chemistry. She then moved to USA to pursue herPh.D. at California Institute of Technology under the supervision of Professor Jacqueline K. Barton from 2002 to 2007. She further obtained postdoctoral research training at Harvard Medical School/Massachusetts General Hospital from 2007-2010 at Professor (M.D.) Ralph Weissleder’s group. She has begun her independent academic career at Division of Chemistry and Biological Chemistry at Nanyang Technological University (Singapore) as Nanyang Assistant Professor since 2010.

Direction：
Nucleic Acid Chemistry, Bioinorganic Chemistry, Chemical Biology, and DNA Nanotechnology

Dr. Gaoang Wang joined the ZJU-UIUC as an assistant professor in September 2020. He is also an adjunct assistant professor at UIUC. His research interests are computer vision, machine learning, image and video processing, including multi-object tracking, pose estimation, deep neural networks, active learning, etc. Gaoang Wang received a B.S. degree from the electrical engineering department of Fudan University in 2013. He received a M.S. degree from the electrical and computer engineering department of the University of Wisconsin-Madison in 2015. He then received a Ph.D. degree from the information processing laboratory of the electrical and computer engineering department at the University of Washington in 2019. After that, he joined Megvii US office in July 2019 as a research scientist working on multi-frame fusion. He then joined Wyze Labs in November 2019, working on deep neural network design for edge-cloud collaboration. Gaoang Wang participated in AI City Challenge held by Nvidia from 2017 to 2019 each year and won the first and second prizes in several tracks. He has published papers in several renowned academic journals and international conferences, including IEEE T-IP, IEEE T-MM, IEEE T-CSVT, IEEE T-VT, CVPR, ICCV, ACM MM, etc.
Direction：
Computer Vision, Machine Learning, Image and Video Processing

Introduction：
Liangjing Yang received the B.Eng. and M.Eng. degrees in Mechanical Engineering from the National University of Singapore (NUS) in 2008 and 2011, respectively. He obtained the D.Eng. degree from the University of Tokyo (UTokyo) in 2014 with a scholarship to work in the Bio-Medical Precision Engineering Laboratory. Before joining ZJU-UIUC Institute, he was with the Singapore University of Technology and Design (SUTD), and Massachusetts Institute of Technology (MIT) under a joint postdoctoral fellowship award. Liangjing’s research interests are in Robotics and Computer Vision primarily focusing on biomedical applications. His work in UTokyo on image mapping for 3D ultrasound-guided endoscopic procedures is published in both engineering and medical journals including Surgical Endoscopy. The work is also recognized by two awards, namely, the Young Investigator Award 2013 from International Society of Computer Aided Surgery and the Best Paper Award in ACCAS 2015 from IEEE-Engineering in Medicine and Biology Society. In NUS, he developed a robotic system for overlapping ablation of large liver tumors, which is featured in a special issue on “Surgical and Interventional Medical Devices” of ASME/IEEE Transactions on Mechatronics. In SUTD and MIT, Liangjing combines his expertise in Robotics and Computer Vision to develop a vision-guided robotic micromanipulation platform which is published in IEEE Transactions on Automation Science and Engineering. He holds a US patent on a Robotic Surgical Training System. This development was named “Best Innovation in Biomedical Application” in a challenge organized by National Instrument in 2011.

Direction：
Robotics, Computer Vision, Vision-Guided Micromanipulation