Postdoctoral Scientist2020 - PRESENTThe University of Chicago
Technologies: Statistical Methods, Bayesian Statistics, Linear Regression, Logistic Regression, Predictive Modeling, Machine Learning
- Led multiple projects on Bayesian statistics with international collaborations and challenging deadlines.
- Developed machine learning algorithms for sparse multiple regression.
- Introduced gradient descent technique for variational inference.
Postdoctoral Scientist2015 - 2020Max Planck Society
Technologies: Bayesian Statistics, Statistical Methods, Linear Regression, Logistic Regression, Predictive Modeling, Machine Learning
- Developed statistical methods to understand disease mechanisms from large-scale biomedical data.
- Collaborated with medical doctors leading to two peer-reviewed publications.
- Presented our work at the 2019 International Society for Computational Biology conference and 2020 e:Med; invited to hold a visiting lecture at the University of Göttingen.
- Supervised a master's thesis and mentored three internship students.