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High-dimensional spatio-temporal modeling
Deep representation learning and dynamic analysis of multi-source industrial time-series signals.
From factory floors to the lectern — building Industrial AI that works in real production lines.
Associate Professor & Doctoral Supervisor, School of Advanced Manufacturing, Sun Yat-sen University; Director of SAM Lab (AI³). Previously CTO at Xinrun Fulian Digital Technology, Industrial AI product lead at Foxconn Industrial Internet, and research scientist collaborating with General Motors R&D.
Deep representation learning and dynamic analysis of multi-source industrial time-series signals.
Time-series–vision–signal fusion for domain foundation models and embodied closed-loop decisions.
Multimodal sensing and process optimization for semiconductors, EV, and high-end equipment.
All three directions live as 30+ funded projects at SAM Lab — real production lines, real data.
Explore them at SAM Lab ↗Sequential Bayesian ARX with time-variant parameters tracks slow process drift; a sample-importance test screens online updates. Beat JIT and deep-learning baselines on PHM 2016 CMP data.
Cross-trajectory Gaussian process regression exploits correlations across cells for efficient, adaptive online capacity prediction — without inflating GPR complexity.
Offshore wind farm maintenance scheduling & routing that prices turbine production loss from forecasted wind; a GA solver outputs schedules, vessel routes and cost breakdowns. Validated on real 4 MW farm data.
Fault detection that keeps the engineer in the loop: feature-based UVA extended with parameter correlations, drift rejection, and automatic limit setting — visualized for SME decision-making.
A cyber-physical gait-training system: physiological + machine data fused at the edge to quantify recovery, personalize treatment, and tune machine parameters — toward a "virtual doctor".
A systematic methodology for online evolving PHM with an adaptive sampling mechanism, robust to continuous stream data and in-process changes.
Ph.D. & M.Sc. positions in Industrial AI at SYSU (Shenzhen). Well-funded, real production data, industry co-projects with GM, Xiaomi, Applied Materials and more. Backgrounds in ME, EE, CS or automation welcome.