美国亚利桑那州立大学 ASU | 智能交通网络物理系统 | PhD/MS Sp/Fa25

美国亚利桑那州立大学 ASU | 智能交通网络物理系统 | PhD/MS Sp/Fa25


王砚冰博士将在2025年春季以终身制教职序列（tenure-track）助理教授加入美国亚利桑那州立大学可持续工程与建成环境学院。她将作为交通网络物理系统实验室（Transportation Cyber-Physical Systems Lab）负责人，主要关注协同感知、自动化和数据驱动方法提升交通系统安全和效率。实验室目前有多个博士/硕士研究助理职位（入学时间灵活，可选2025年春季/夏季/秋季入学），可根据职级水平（position level）提供全额奖学金、学费豁免、研究津贴等资助方式。申请者将在以下研究主题工作：

• 交通数据分析: 处理路侧传感器数据，开发数据驱动的实证数据分析方法，辨识交通特征
• 交通仿真和建模: 通过多源真实世界交通数据构建交通仿真、标定，进行数据融合
• 自动驾驶系统：开发部署基于机器学习的自动驾驶行为预测、决策和控制方法
• 软件硬件集成：集成软件并部署到测试车辆、进行实际场景现场测试

要求
申请者应拥有或正在攻读工程学科的硕士/学士学位，例如电气与计算机工程、机械工程、土木工程、工业工程或计算机科学。在交通建模、机器学习、数据科学或机器人技术方面有研究经验者优先。有意向的申请者请将简历或CV发送邮件到yanbing.wang@asu.edu，邮件标题为“[Position] Application-[Full Name]”.


背景
亚利桑那州立大学（ASU）在2024年《美国新闻与世界报道》的“最佳大学”排名中被评为全美最具创新性的大学。Ira A. Fulton工程学院总体排名第34位，且在公立工程学院中跻身前20名。在加入ASU之前，王砚冰博士在阿贡国家实验室工作，领导了由美国能源部资助的服务于能源评估的交通微观仿真平台开发。她在2023年9月于美国范德堡大学获得博士学位，在Dan Work教授的指导下领导了田纳西I-24 MOTION测试平台的算法开发。王博士获得了2023年美国国家自然科学基金网络物理系统新星奖、5项美国交通部Dwight David Eisenhower交通奖学金，并被评为Sidney P. Colowick研究生学者和Harold Stirling Vanderbilt学者。她曾在丰田信息技术实验室（Toyota Infotech Labs）、三菱电机研究实验室（MERL）实习，并且是加州大学洛杉矶分校理论与应用数学研究所（UCLA IPAM）的访问研究员。更多信息，请访问https://yanbingwang.com.







Description 
Dr. Yanbing Wang will be joining Arizona State University as a tenure-track Assistant Professor in the School of Sustainable Engineering and the Built Environment (SSEBE) starting Spring 2025. She will be leading the Transportation Cyber-Physical Systems Lab, which aims to improve transportation safety and efficiency through collaborative sensing, automation and data-driven methods. Her lab has multiple PhD/MS positions with flexible starting dates (spring/summer/fall 2025), with research assistance funding and tuition waivers available based on the position level. Desirable candidates are expected to work on one of the following topics:

• Transportation Data Analysis: Clean and process raw roadside sensor data, develop data-driven methods to analyze empirical data, and identify travel patterns
• Traffic Simulation and Modeling: Perform traffic simulation, calibration and data fusion using real-world traffic data from multiple data sources
• Automated Driving System: Develop and implement machine learning-based algorithms for behavior prediction, decision-making, and control of automated vehicles
• Software-Hardware Integration: Integrate and deploy software onto test vehicles for real-world field testing

Requirements
Desirable candidates should either have or be currently pursuing an MS/BS degree in an engineering discipline, such as Electrical and Computer Engineering, Mechanical Engineering, Civil Engineering, Industrial Engineering, or Computer Science. Research experience in traffic modeling, machine learning, data science, and/or robotics is a plus. Interested candidates are encouraged to send resume/CV to yanbing.wang@asu.edu with the email title “[Position] Application-[Full Name]”.


Background
Arizona State University (ASU) ranks No. 1 in innovation among American universities in the 2024 U.S. News & World Report's "Best Colleges" rankings. The Ira A. Fulton Schools of Engineering tied for No. 34 overall and placed in the top 20 for public engineering schools. Before joining ASU, Dr. Yanbing Wang worked at Argonne National Laboratory, leading the development of traffic micro-simulation platforms for energy evaluation funded by the Department of Energy. She received her Ph.D. from Vanderbilt University in September 2023, where she led algorithm development for Tennessee's I-24 MOTION testbed under Prof. Dan Work. Dr. Wang received the NSF Cyber Physical Systems Rising Star award (2023), five USDOT Dwight David Eisenhower Transportation Fellowships, and was a Sidney P. Colowick Graduate Scholar and Harold Stirling Vanderbilt Scholar. She has interned at Toyota Infotech Labs, MERL, and was a visiting researcher at IPAM, UCLA. For more information, visit https://yanbingwang.com.