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Academic Credentials
  • 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
Licenses & Certifications
  • Professional Engineer Mechanical, California, #41692
  • NVIDIA-Certified Associate: Generative AI LLMs
  • SOLIDWORKS Certificate in Mechanical Design
  • TensorFlow Developer
  • UL Certified Autonomy Safety Professional (UL-CASP)
Additional Education & Training
  • AWS Cloud Technical Essentials, Amazon Web Services, November 2023
  • TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning, DeepLearning.AI, July 2022
  • GD&T and Stack-Up, Udemy, June 2022
  • Advanced CSRD Practitioner, Earth Academy, December 2024
  • Introduction to Foundry & AIP for Enterprise Organization, Palantir, February 2025
  • Planetary Scale Earth Observation with Google Earth Engine, Google Cloud, February 2025
  • Collaborative Robot Safety: Design & Deployment, SUNY Buffalo, February 2025
  • Introduction to CSRD and Reporting with ESRS, GRI, December 2024
  • ISO 26262 Functional Safety Mastery, Udemy, June 2024
  • Foundations of Project Management, Google, May 2023
  • Fusion 360, Autodesk, August 2021
  • SQL for Data Science, UC Davis, May 2021
  • Applied Data Science with Python, University of Michigan, June 2020
  • Management of Technology Innovation, UC Berkeley, May 2016
Professional Honors
  • 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
Professional Affiliations
  • Institute of Electrical and Electronics Engineers (IEEE)
  • 2023 Vice Chair, IEEE Robotics and Automation Society, Santa Clara Valley/Oakland-East Bay/San Francisco Joint Chapter
  • Member, IEEE P2940 Standard for Measuring Robot Agility Working Group
  • American Bar Association (ABA)
Languages
  • Cantonese Chinese
  • Chinese
  • English

Dr. Wang is a licensed Professional Engineer, certified as a TensorFlow Developer and is a certified SolidWorks Mechanical Designer (CSWA). His specialties include artificial intelligence (AI) and machine learning (ML), robotics and control, engineering software development, relational database and time series data analytics and visualization, Computer-Aided Design (CAD), and dimensional and tolerance analysis. He applies these technologies in solutions for product safety, risk assessment, failure analysis, regulatory and compliance, financial forecast, predictive analytics, industrial automation, and new product introduction (NPI). He brings technical and business solutions to clients in consumer electronics, oil and gas, energy and utility, automotive and autonomous driving, industrial and manufacturing, medical devices, semiconductors, and beyond.

Dr. Wang's technical skills include software toolchains (Jira, Confluence, git, GitHub, pytest), programming languages (Python, R, C++, Matlab/Simulink, SQL, SPARQL), cloud computing services (Amazon Web Services AWS SageMaker, Bedrock, Google Colab, Earth Engine), data management and data operating systems (Palantir Foundry), electromechanical prototyping tools, sensors and actuators (DC, servo, stepper motors), microcontrollers (Arduino, mbed) and single-board microcomputers (Raspberry Pi), enterprise resource planning ERP software (SAP), customer relationship management CRM software (Salesforce), and business intelligence platform (Power BI).

Beyond technical skills, Dr. Wang has practical knowledge with sustainability frameworks and experience supporting clients with sustainability reporting activities, including adopting United Nations' Sustainable Development Goals (SDGs), Global Reporting Initiative (GRI) standards, and European Union (EU) Corporate Sustainability Reporting Directive (CSRD, 2022/2464/EU) and European Sustainability Reporting Standards (ESRS, 2023/2772/EU).

Prior to joining Ä¢¹½tv, Dr. Wang was a data science researcher at Siemens and developed fault diagnosis algorithms for intelligent car manufacturing by integrating physics engines, ontologies and semantic web, signal processing, and artificial intelligence.

As an investment data analyst at Runway Innovation, he used machine learning to predict companies' future revenue based on present innovation effort and helped Fortune Global 500 companies with their digital transformation innovation journey. He also performed technology due diligence and deal flow analysis for venture capital investors and asset management firms. For his work and expertise, he was named a finalist for The Technical Analyst Award.

During his postdoctoral research at UC Berkeley, he designed and developed an automatic robotic repair system while also performing fatigue testing on a folding-based hexapod robots using a treadmill and a motion capture system. Dr. Wang received a doctoral degree from ETH Zurich, where he developed both climbing and pick-and-place robots constructed from thermoplastic adhesives. He performed mechanical testing for adhesive strength on various materials while developing and validating model-based control of deformation using thermal imaging and temperature sensors.