At Stellantis, we design battery management systems for hybrid and full electric vehicles (EVs) and validate them at different levels through extensive tests. We work on both production and R&D projects. In collaborations with universities, we define and co-supervise grad theses based on our industrial needs. Every semester, we welcome and mentor co-op and internship students.  

I designed and taught a range of fundamental and elective courses at undergrad and grad levels.

In addition to EVs, I had a chance to join the Brain Stimulation Engineering Lab at Duke University School of Medicine to learn, study and do some research in transcranial magnetic stimulation (TMS) engineering, which is a power-electronic-based non-invasive brain stimulation technology for studying the brain functions and cognitive science, and treating some of the psychiatric and neurological disorders.

Overall, our works/papers would be classified in the following theoretical and application domains:

Theoretical Topics:
– Estimation theory and system identification 
– Robust control theory: H-infinity, linear matrix inequality (LMI) and quantitative feedback theory (QFT)
– Fault diagnosis

Applications:
– EVs: Battery systems, electrochemical impedance spectroscopy (EIS), power electronics, and grid integration
– Transcranial magnetic stimulation
– Wireless sensor networks and networked control systems