About

Data Scientist @ Yale

I am a scientist at the Yale Child Study Center studying developmental psychopathology using high-density EEG.

I have worked with data for 13 years. I have built pipelines to facilitate the whole data life-cycle: collection, cleaning, mining, reduction, statistics, visualization and publication.

I worked with infant EEG in graduate school in University of Louisville. We tested newborns who were still in the hospital before going to their homes the first time. We tested their auditory processing using high-density EEG and used it to predict dyslexia in future development.

During my stages of being a Posdoctoral Researcher, Associate Research Scientist and Research Scientist, I worked with children and adolescents. I have programmed video games that were highly interactive and engaging for kids to play, and position them in a particular psychological mindset that we were interested in studying. Some of the games are: Cyberball for social rejection, Balloon games for risk evaluation, Bomb game for threat detection.

I have also implemented advanced statistic algorithms for data analysis, such as Principle Component Analysis, Independent Component Analysis, False Discovery Rate, Wavelet Analysis, Time Series Analysis.

At Yale I have worked with over 100 researchers and clinicians and have the domain knowledge in a wide range of mental health including: addiction, anxiety, depression, ADHD, TS, Autism, Obesity.

Besides working with academia data, I also self-learn industry data science. I completed the Python and R courses on Dataquest.io. I also work on side projects while volunteer in the community.

I believe in using technology to benefit society.