ShanghaiTech University / School of Information Science and Technology / STAR Center / Multiphysical Agents and Intelligent Control Laboratory

About Us

Welcome to the Multiphysical Agents and Intelligent Control (MAgIC) Laboratory at ShanghaiTech University. Our research spans the development of bio-inspired underwater and aerial robots—such as robotic fish and flapping-wing vehicles—with a focus on perception, planning, control, and multi-agent coordination. Currently, the core of our work lies at advanced motion control for robotic systems operating in dynamic fluid environments.

Underlying these applications is our fundamental research into the modeling and control of complex, nonlinear, time-varying systems across multiple scales. We develop adaptive, data-driven, and learning-based control theories with provable guarantees, tackling challenges such as uncertainty, disturbance, and system constraints.

Led by Prof. Yang Wang, our team consists of passionate PhD and master students dedicated to pushing the boundaries of fluidic-interactive robotic systems and intelligent control theory. We welcome collaborations and discussions with researchers who share our interests.

News

Entrepreneurship-Pudong-Second-Prize

21 October 2026

MAgIC Lab Student Team Wins District-Level Second Prize at the 2026 "Entrepreneurship Pudong" Youth Innovation and Entrepreneurship Competition.

The team led by MAgIC Lab master's student Xinyue Zhang won Second Prize at the 2026 "Entrepreneurship Pudong" Youth Innovation and Entrepreneurship Competition, an official district-level competition in Shanghai's Pudong New Area. Their project, "Haiyi Lingkun," develops propeller-free biomimetic robotic fish integrating tail-fin propulsion, autonomous control, and multisensor perception for low-disturbance underwater monitoring in aquaculture and aquatic ecosystems.

The competition attracted 201 teams across four tracks: Hard Technology, Digital Economy, Technology-Driven Agriculture, and Early-Stage Startups, with only 24 teams receiving awards. ShanghaiTech University hosted the Early-Stage Startups track, providing a platform for young innovators to compete for district-level recognition and entrepreneurial support. This achievement highlights the team's innovation capabilities and entrepreneurial potential.

CDC2026

15 July 2026

Congratulations to MAgIC Lab for the paper accepted by CDC2026.

The paper entitled 'Adaptive Observers for Switched Nonlinear Systems: Exact Disturbance Decoupling and Reduced-Dimension Parameter Estimation' has been accepted for presentation at the 65th IEEE Conference on Decision and Control (CDC). The paper proposes a novel disturbance decoupling adaptive observer for multivariable switched nonlinear systems subject to unmeasurable disturbances and parameter jumps. Asymptotic convergence is achieved and a geometric approach-based design further lowers the dimensionality of the filters in the observer, yielding a scalable framework.

TiaoZhan-Bei-golden-award

06 June 2026

MAgIC Lab Student Team Wins Golden Award at the Shanghai “TiaoZhanBei” Competition.

The team led by MAgIC Lab master's student Yuhang Zhao won the Golden Award at “TiaoZhanBei” Chinese College Students' Entrepreneurship Plan Competition.

This achievement marks a historic breakthrough for ShanghaiTech University, as Zhao's team became the first from the university to reach the Shanghai final of the highly competitive regular track and went on to claim the Golden Award.

icra-conference

03 June 2026

MAgIC Lab Students Present Latest Research at IEEE ICRA.

MAgIC Lab Ph.D. student Xiaozhu Lin and graduate student Qinxiao Ma, both advised by Prof. Yang Wang, successfully attended IEEE ICRA and presented their latest research, receiving strong recognition from the robotics community.

Lin's work develops a bio-inspired reinforcement learning approach for agile and controllable fast-start maneuvers of robotic fish, while Ma's work introduces an ultra-fast deep photonic reservoir computing framework for feedforward dynamic compensation of UAVs in confined environments, together contributing to advances in bio-inspired robotics, aerial robotics, and intelligent robotic systems.

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