I work in the Biophysics department and Donders institute for an STW project that aims to develop an objective measure system (EEG involved) to automatically optimize individualized parameter settings (from million possibilities) for hearing devices (hearing aids and cochlear implants). • We have developed objective methods evaluating the hearing performance via the auditory steady-state responses (ASSRs) extracted from EEG. The objective methods consist of (1) an on-line detector of ASSRs and (2) a new system-identification method based on phase coherence that quantifies the underlying nonlinearities (e.g., subsystems, multiple latencies) of the human auditory system.• Teaching assistant for the Python programming (a master course of RU), 2018.

I work in the signal processing system (SPS) group of the Department of Electrical Engineering. My Ph.D. topic was automated seizure detection by using scalp EEG signals (ECG, EMG, EOG signals also involved). • Task i: Developed a software (MATLAB GUI + .XML) for neurologists to easily annotate long-term EEG recordings (ambulant, 24-hours) and to visually demonstrate the algorithm performance.• Task ii: Feature engineering (implemented the time/frequency -domain analysis and developed new algorithms: dynamic warping, complex networks, a broadband method of quantifying phase synchronization and cross-frequency coherence, etc.) and machine learning (L/Q/RDA, Bayesian, Boosting, SVM, random forests) as well as deep learning (CNNs, RNNs).

I worked here for my master project, to implement a prediction control algorithm/module (using C++) for the distributed control system (DCS, Honeywell) of the largest cement plant in Zhejiang province.

I worked in the IT department at GE Hydro Asia Co. Ltd. We developed a PC-based software platform using C++ (MFC) for monitoring and reporting (automated emails and SMS) the update of the database (Oracle) of the factory inventory.

We (3-persons team) developed an EEG analysis software (using MATLAB) for automatic estimation of the depth of anesthesia from EEG recordings during surgery.