about.md

# From a Master’s in Signal and Image Processing to a Ph.D. in Bioinformatics at Institut Pasteur, where I specialized in deep learning-augmented super-resolution microscopy, my journey has been about applying computational tools to biology and medicine.

# Today, as a Machine Learning Engineer in the health-tech industry, I bring 6+ years of machine learning and deep learning experience: designing algorithms for physiological time-series data and writing them in C/C++ for integration into embedded systems. I’m driven by translating complex data into real-world health impact.

Experience

Hackathon Projects

Scientific Communication

Publication


Ouyang, W.#, Bai, J.#, et al. (2022). ShareLoc — an open platform for sharing localization microscopy data, Nature Methods, 19(11), pp. 1331–1333. (# equal contribution) [paper]

Ito, T., Bai, J. and Ostry, D.J. (2020). Contribution of sensory memory to speech motor learning, Journal of Neurophysiology, 124(4), pp. 1103–1109. [paper]

Talk


Symposium Artificial Intelligence in Biology and Health - Paris (2023.07.04)

Single Molecule Localization Microscopy Symposium 2022 - Paris (2022.08.31)

3rd Imabio YSN conference, ENS de Lyon (2022.07.06)

2nd meeting of the GDR Architecture and Dynamics of the Nucleus and Genomes, ENS de Lyon (2022.06.22)

Department day, Biologie Computationnelle department, Institut Pasteur (2021.11.29)

Seminar WIP (Work In Progress), Cell Biology and Infection Department, Institut Pasteur (2020.12.14)

Poster


21st International European Light Microscopy Initiative Meeting, Turku(2022.06.07)

Education

Bio-informatics, Ph.D.

2023, Complexité du vivant, Sorbonne Université/Institut Pasteur


Signal Image Processing Methods and Application (SIGMA), Master 2

2019, Phelma, Grenoble INP


Electrical system, Master 1

2018, Université Grenoble Alpes


Electronic Engineering and Automation, Bachelor

2016, Hebei University of Engineering