TINGTING ZHAO

Tingting Zhao

Tingting joins Bryant University in January 2022 as an Assistant Professor. Tingting received her Msc. and Ph.D. from the University of British Columbia in Statistics, advised by Prof. Alexandre Bouchard-Côté in 2013 and 2018. Before joining Bryant University, Tingting was a TRIPODS postdoctoral research associate of theoretical data science in the College of Information and Computer Sciences at UMass Amherst under the guidance of Prof. Patrick Flaherty in 2021. Before that, she completed her B.S. in Statistics from Zhejiang University in China. She was a postdoctoral research associate in the Department of Electrical and Computer Engineering at Northeastern University under the supervision of Prof. Jennifer Dy from January 2019 to December 2020. She was also a sponsored research fellow at Brigham and Women's Hospital of Harvard Medical School under the supervision of Prof. James Ross. Her research interests focus on Bayesian Statistics, Markov Chains Monte Carlo methods, deep learning, lifelong learning, feature selection, and blackbox model interpretation with applications to genetics and computational biology.

Ph D, University of British Columbia

M Sc, University of British Columbia

B Sc, Zhejiang University

Zhao, T.,Zhu, G.,Vardhan Dubey, H.,Flaherty, P., Identification of Significant Gene Expression Changes in Multiple Perturbation Experiments using Knockoffs (In Revision), Briefings in Bioinformatics (Impact Factor: 13.994).

Zhao, T.,Wang, Z.,Masoomi, A.,Dy, J., Deep Bayesian Unsupervised Lifelong Learning, Neural Networks (Impact Factor: 9.657), 2022.

Wang, Z.,Masoomi, A.,Xu, Z.,Boueiz, A.,Lee, S.,Zhao, T.,Bowler, R.,Cho, M., Silverman, E.,Hersh, C.,Dy, J.,Castaldi, P., Improved prediction of smoking status via isoform-aware RNA-seq deep learning models, PLOS Computational Biology (Impact Factor: 4.779), 2021.

Zhao, T., Bouchard-Côté, A., Analysis of high-dimensional Continuous Time Markov Chains using the Local Bouncy Particle Sampler, Journal of Machine Learning Research (Impact Factor: 5.413), 2021.

Zhu, G.,Zhao, T., Deep-gKnock: nonlinear group-feature selection with deep neural network, Neural Networks (Impact Factor: 9.657), 2021.

Masoomi, A.,Wu, C.,Zhao, T.,Wang, Z.,Castaldi, P.,Dy, J., Instance-wise Feature Grouping, Neural Information Processing Systems (NeurIPS) (20% Acceptance Rate), 2020.

Liu, D.,Xu, N.,Zhao, T.,Song, Y., Identifying the nonlinear correlation between business cycle and monetary policy rule: Evidence from China and the US., Economic Modeling (Impact Factor: 3.875), 2018.

Zhao, T.,Wang, Z.,Cumberworth, .,Gsponer, J.,de Freitas, N.,Bouchard-Côté, A., Bayesian analysis of continuous time Markov chains with application to phylogenetics, Bayesian Analysis (Impact Factor: 2.423), 2016.

Bryant University Faculty Innovation Grants, 2022

Top Reviewer Award for International Conference on Machine Learning (ICML), 2020

Sequential Monte Carlo course and workshop scholarship, 2017

JSM best student presentation awards of section for statistical programmers and analysts (SSPA), 2017

2016 phylogenomics symposium and software school travel awards, 2016

Machine Learning, Deep Learning, Computational Statistics. Bayesian Statistics, Data Visualization.

Bayesian Statistics, Markov Chains Monte Carlo methods, deep learning, lifelong learning, feature selection, and blackbox model interpretation with applications to genetics and computational biology.