Zhihao Jiang

Zhihao Jiang

Assistant Professor

ShanghaiTech University

Biography

Zhihao Jiang is currently an assistant professor in the School of Information Science and Technology (SIST) at ShanghaiTech University, and the director of the Human-Cyber-Physical-Systems Lab.

Download my resumé.

Interests
  • Human-Cyber-Physical Systems
  • Decision Support Systems
  • Digital Twins
  • Formal Methods
Education
  • PhD in Computer and Information Science, 2016

    University of Pennsylvania

  • MS.E in Robotics, 2010

    University of Pennsylvania

  • BS.E in Technology and Instruments in Measurement and Control, 2008

    University of Electronic Science and Technology of China

Experience

 
 
 
 
 
ShanghaiTech University
Assistant Professor
ShanghaiTech University
Jul 2018 – Present Shanghai, China
Director of the Human-Cyber-Physical Systems Lab
 
 
 
 
 
Toyota InfoTechnology Center USA
Researcher
Toyota InfoTechnology Center USA
Jul 2017 – Jun 2018 Mountain View, California
Project lead - Digital Twins for Safe Connected Cars.

Research

My research develops theoretical foundations for Human-Cyber-Physical Systems (HCPS) in safety-critical domains. To ensure safe and effective decision-making, two requirements must be met: (1) explicit mechanism-to-observation and decision-to-outcome causality; (2) real-time understanding of human operators' cognitive states and preferences.

I propose a dual-digital-twin framework resolving these challenges: the Environment Digital Twin enables counterfactual analysis for causality establishment, while the Cognitive Digital Twin infers decision-makers’ cognitive parameters and predicts their responses to decision supports. This architecture enables AI systems to complement—rather than replace—human experts in medical and automotive applications, achieving safe and effective human-machine collaboration. Crucially, decisions guided by these twins ensure decision-makers operate with the correct contextual understanding, while the AI-generated support becomes inherently more intuitive, easier to accept, and ultimately more effective in guiding the human towards optimal choices.​

Research Overview
Research Overview

Recent Publications

Cognitive-Digital-Twin-Based Driving Assistance
Digital-Twin-Based Patient Evaluation during Stroke Rehabilitation
Predicting Synthetic Lethality in Human Cancers Via Multi-Graph Ensemble Neural Network

Contact

  • jiangzhh at shanghaitech.edu.cn