ITE Student Chapter at the University of Washington
Education
Education, Mentoring & Workforce Development
Preparing students and transportation professionals to lead in a rapidly changing field through teaching, research mentoring, professional engagement, and lifelong workforce development.
Education & Mentoring
Developing People Alongside Technology
Education has been a central part of Professor Yinhai Wang's career. His approach goes beyond teaching transportation engineering concepts to helping students develop the technical skills, professional confidence, curiosity, and leadership needed to address real transportation challenges.
Professor Wang views mentoring as a long-term commitment. Students learn through coursework, research, professional organizations, seminars, field projects, collaboration with public agencies and industry, and opportunities to present and apply their work. The same philosophy extends to workforce development: transportation professionals need accessible opportunities to continually learn about emerging technologies such as artificial intelligence, advanced sensing, edge computing, and data science.
Supervised in design projects and research
A continuing forum for research discussion and student development
Traffic sensing, data analytics, control, simulation, and computing
Student Leadership
Faculty Advisor, ITE UW Student Chapter
2004
Present
More Than Two Decades of Student Professional Development
Professor Wang has served as faculty advisor for the Institute of Transportation Engineers (ITE) Student Chapter at the University of Washington since 2004. This long-running role has provided a sustained opportunity to mentor generations of transportation students as they build connections between university education and the professional community.
Student organizations are an important part of engineering education. They give students opportunities to develop leadership skills, engage with practitioners, learn about career pathways, build professional networks, and participate actively in the transportation profession before graduation.
His role as faculty advisor complements classroom teaching and research mentoring by helping students see transportation engineering as both a technical discipline and a professional community in which they can contribute and lead.
Graduate Education
Mentoring Researchers & Future Leaders
Graduate mentoring is closely integrated with research in the STAR Lab. Students work on problems involving artificial intelligence, sensing, transportation safety, traffic operations, connected and automated transportation, data science, and intelligent infrastructure.
Doctoral Mentoring
Professor Wang has chaired doctoral research spanning traffic sensing, safety, autonomous driving, machine learning, deep learning, transportation equity, and intelligent infrastructure.
Recent Ph.D. graduates have continued into careers in academia and industry, including the University of Utah, Johns Hopkins University, Amazon, Google, Instacart, SRF Consulting, and the Hong Kong University of Science and Technology.
Master's Mentoring
Master's students have completed thesis and applied research projects on topics ranging from large language models and traffic analytics to pedestrian safety, bicycle detection, signal control, visibility sensing, and transportation system operations.
Many projects are connected directly to transportation agencies, consulting firms, and real implementation needs.
Independent Study & Research
Professor Wang has supervised 30 students in independent study, design projects, and research. These projects have included traffic simulation, sensor data analysis, pedestrian tracking, mobile applications, signalized intersection design, and transportation data systems.
Learning Community
Seminars as a Mentoring Environment
STAR Lab Weekly Seminar
A long-running research forum where students discuss emerging ideas, present work in progress, receive feedback, and learn from one another across disciplinary boundaries.
PacTrans Seminar
A continuing platform connecting students, researchers, practitioners, and transportation leaders across the Pacific Northwest.
Workforce Development
Preparing the Transportation Workforce for Emerging Technologies
Transportation technology is evolving quickly, creating both new opportunities and new workforce needs. A major part of Professor Wang's education effort is helping students, practitioners, agencies, and communities understand and use emerging technologies effectively.
PacTrans Workforce Development Institute
Developed and taught professional training on emerging transportation topics, including Introduction to Artificial Intelligence in 2025 and 2026 and Transportation Challenges and Opportunities in 2019.
Transportation Workforce Summer Programs
Led WSDOT-supported efforts to develop summer-camp programming focused on transportation workforce development and introducing future students to transportation careers and technologies.
Engineering Workforce Pathways
Led the Washington engineering pathway study and quick-solutions effort addressing workforce challenges and pathways into the civil and transportation engineering professions.
Training for Practitioners
Short courses and professional education have covered artificial intelligence, transportation operations, traffic sensing, data analysis, signal control, and related technologies for transportation professionals and university audiences.
Textbooks
Machine Learning for Transportation Research and Applications
Professor Wang has co-authored textbooks that help connect modern machine learning methods with transportation research and applications. The books support students, researchers, and practitioners seeking a transportation-focused introduction to data-driven and machine-learning approaches.
Machine Learning for Transportation Research and Applications
Yinhai Wang, Zhiyong Cui, Ruimin Ke, and Kai Zhang
Tsinghua University Press · May 2026
ISBN 9787302718604
Machine Learning for Transportation Research and Applications
Yinhai Wang, Zhiyong Cui, and Ruimin Ke
Elsevier · April 2023
ISBN 9780323996808
Curriculum Development
Courses Developed
Advanced Traffic Detection Systems
Transportation Data Management and Analysis
Traffic System Operations (aka. Traffic System Control and Simulation)
Computer-Aided Construction
Recognition
Teaching & Mentoring Recognition
Outstanding Educator Award
Institute of Transportation Engineers Western District
Mentoring Award
Department of Civil & Environmental Engineering, University of Washington
Innovations in Education Award
ITE Transportation Education Council
Looking Forward
Education for a Changing Transportation Profession
The transportation workforce of the future will need strong engineering fundamentals as well as the ability to work across artificial intelligence, data science, sensing, automation, infrastructure, and human-centered transportation systems. Professor Wang's goal is to help students and professionals develop both the technical capabilities and the broader perspective needed to use these tools responsibly and effectively in practice.