- Ph.D., Mechanical Engineering, ETH Zurich, Switzerland, 2014
- M.Sc., Biomedical Engineering, University of Oxford, UK, 2007
- B.Eng., Optoelectronics Engineering, Zhejiang University, China, 2006
- Certified SOLIDWORKS Associate in Mechanical Design
- TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning, DeepLearning.AI, July 2022
- GD&T and Stack-Up, Udemy, June 2022
- Fusion 360, Autodesk, August 2021
- SQL for Data Science, UC Davis, May 2021
- Applied Data Science with Python, University of Michigan, June 2020
- The Technical Analyst Award Finalist, 2021
- Siemens Fellowship, 2017
- Haas Dean’s Seed Fund, 2016
- IET Travel Award, 2016
- Swiss National Science Foundation Fellowships, 2014, 2016
- Sloane Robinson Foundation Scholarship, 2007
- Institute of Electrical and Electronics Engineers (IEEE)
- The Institution of Engineering and Technology
- ASTM International
- 2023 Vice Chair, IEEE Robotics and Automation Society, Santa Clara Valley/Oakland-East Bay/San Francisco Joint Chapter
- Voting Member, IEEE P2940 Standard for Measuring Robot Agility working group
Dr. Wang specializes in the design, prototyping, and control of robotic and electromechanical systems. He is experienced in material characterization, mechanical testing, numerical simulation, data acquisition and analysis, and the building of data science models for anomaly detection and fault diagnosis for industrial automation.
Dr. Wang did his postdoctoral training at the University of California Berkeley, where his research focused on the design and development of a robotic system with twelve actuators, four types of sensors, and recovery capabilities from physical damage. He performed rigorous mechanical testing on the subsystems, including a 26-hour burn-in test by using a treadmill and a motion capture system, and a joint stiffness test using a tensile testing machine with a custom-built setup using linear actuators and a force plate.
Dr. Wang received his doctoral degree from ETH Zurich, where his research focused on the design and development of several robots involving handling thermoplastic adhesive materials for functions including vertical climbing and pick-and-place. For example, one of his vertical climbing robots could carry a payload up to 500% of the body mass, making it the highest specific payload for any climbing robot at the time. He performed mechanical testing for adhesive strength on various materials and developed and validated a deformation model by using thermal imaging and temperature sensors.
Prior to joining Exponent, Dr. Wang was a research fellow at Siemens, where he developed a fault diagnosis algorithm for intelligent manufacturing by integrating a physics engine, semantic web technologies, signal processing, and numerical optimization. He was also a consultant at Runway Innovation, where he helped Fortune Global 500 companies with their digital transformation journey in sectors including Construction, Manufacturing, Retail, Transportation, Warehousing, Information, Finance, and Insurance. In addition, Dr. Wang served as an innovation researcher, where he used machine learning techniques to predict companies' future revenue based on present innovation effort.
Dr. Wang is a Sustainable Development Goals Positive Change Ambassador by Rotterdam School of Management, and he is knowledgeable in quantifying electromechanical systems' environmental impacts. He has also earned certificates in Applied Data Science and Machine Learning from the University of Michigan along with Management of Technology Innovation and in Lean Startup from the UC Berkeley.