Yankai Wang-School of Software, Tsinghua University

Faculty

Name: Yankai WANG

Title: Assistant Professor

Email: wyk2022@mail.tsinghua.edu.cn

Address: 1-106, FIT Building,Tsinghua University, Beijing, China

Research Fields: Intelligent manufacturing, digital and intelligent systems for complex equipment, intelligent software systems for industrial data, edge artificial intelligence, embodied intelligence, optimal control integrating mechanism intelligent learning, AI agent and collaborative control of intelligent agent groups

Introduction: Assistant Researcher at the School of Software, Tsinghua University, Special Researcher in Industrial Data Software, Postdoctoral Fellow at Tsinghua University, Ph.D. in Mechanical Engineering from Chongqing University, and Ph.D. in the Interdisciplinary Joint Program of Computer Science and Mechanical Engineering at the National University of Singapore. Up to now, he has published more than 30 academic papers in TOP journals and obtained 13 national invention patents; Served as a young editorial board member of Journal of Automation and Intelligence in 2024; Served as a member of the Embodied Intelligence Committee of the Chinese Association for Artificial Intelligence from 2025; Led or participated in more than ten national-level projects.

Education background

Ph.D. Chongqing University, Mechanical Engineering, 2018-2022

M.S. Chongqing University, Mechanical Engineering, 2015-2018

B.E. Chongqing University, Mechanical Electronics Engineering, 2011-2015

Experience

Aug. 2025 – Present, Assistant researcher, School of Software, Tsinghua University

Jul. 2022 – Jul. 2025, Postdoctoral Researcher, School of Software, Tsinghua University

Academic Achievements

An adaptive multi-objective multi-task service composition approach considering practical constraints in Fog Manufacturing[J]. IEEE Transactions on Industrial Informatics, 2021.

An effective dynamic service composition reconfiguration approach when service exceptions occur in real-life cloud manufacturing[J]. Robotics and Computer-Integrated Manufacturing, 71.

Adaptive multi-objective service composition reconfiguration approach considering dynamic practical constraints in cloud manufacturing[J]. Knowledge-Based Systems, 2021, 234:107607.

A digital-twin-based self-adaptive multi-objective Harris Hawks Optimizer for dynamic hybrid flow green scheduling problem with dynamic events[J]. APPLIED SOFT COMPUTING, 2023.

Time-tired compaction: An elastic compaction scheme for LSM-tree based time-series database[J]. Advanced Engineering Informatics, 2024, 59(2194):102224.