Current Students
- Younghwan Cho - Feature Selection
- Ke Han - Large Scale Semisupervised Learning
- Jungwon Hwang - Robotic Manipulation
- Rittwika Kansabanik - Video Quality Prediction/Feature Selection
- Cheng Long - Shape Denoising
- Pei-Tien Lu - Natural Language Processing
- Sayantika Nag - Object Segmentation
- Sourita Nag - Deep Learning
- Chen Zhao - Feature Selection
- Siquan Zhu - Object Detection
Graduated Students
- Ke Han, "Semi-Supervised Few-Shot Learning with Probabilistic Principal Component Analyzers"
(pdf). PhD in Statistics, 2024
- Yijia Zhou, "Scalable Clustering: Large Scale Unsupervised Learning of Gaussian Mixture Models with Outliers"
(pdf). PhD in Applied Mathematics, 2023. AI Researcher, Huawei, China
- Rashad Aziz, "Sparse Methods for Latent Class Analysis, Principal Component Analysis and Regression with Missing Data"
(pdf). PhD in Statistics, 2023. Data Scientist, Capus Reimagined, FSU.
- Boshi Wang, "Scalable Learning with Probabilistic PCA" (pdf).
PhD in Statistics, 2023. Senior Image Quality Engineer, GE Healthcare.
- Hongyu Mou, "Sparse Dictionary Learning & The Compact Support Neural Network"
(pdf), PhD in Statistics, 2022.
- Sida Liu, "Efficient Methods for Unsupervised Learning". PhD in Statistics, 2021.
Machine Learning Engineer, J.P. Morgan Chase.
- Mingyuan Wang, "Online and Offline Feature Screening and Applications"
(pdf). PhD in Statistics, 2021.
Quantitative Medicine scientist, Critical Path Institute, Tucson, AZ.
- Hua Huang, "Robust Machine Learning and the Application to Lane Change Decision Making Prediction"
(pdf). PhD in Applied Mathematics, 2021. ML Scientist, Google.
- Orhan Akal, "Deep Learning Based Generalization of Chan-Vese Level Sets Segmentation".
PhD in Applied Mathematics, 2020. Machine Learning Scientist, Overjet, MA.
- Yangzi Guo, "A Study of Feature Interactions and Pruning on Neural Networks"
(pdf),
PhD in Applied Mathematics, 2020. Senior ML Research Engineer, Qualcomm.
- Donghang Li, "Steerable Convolutional Neural Networks"
(pdf), PhD in Statistics, 2020.
Biostatistician, Roche, Shanghai, China.
- Lizhe Sun, "Online Feature Selection with Annealing and Its Applications"
(pdf), PhD in Statistics, 2019.
Assistant Professor, Shanxi University of Finance and Economics, China.
- Gitesh Dawer, "Neural Rule Ensembles: Encoding Feature Interactions into Neural Networks"
(pdf), PhD in Mathematics, 2018.
Machine Learning Team, Apple Corporation.
- Josue Anaya, "First Steps Towards Image Denoising Under Low-Light Conditions"
(pdf). PhD in Statistics, 2017.
Predictive Revenue Analyst, Bankers Healthcare Group.
- Ajay Gupta, "Modeling Multivariate Data with Parameter-Based Subspaces"
(pdf). PhD in Statistics, 2016. Research Scientist at Bank of America, Charlotte, NC.
- Gary Gramajo, "Parameter Sensitive Feature Selection for Learning on Large Datasets"
(pdf). PhD in Statistics, 2015. New Ventures Analyst, Chick-Fil-A Corp, Atlanta GA.
- Liangjing Ding, "Sparse Motion Analysis"
(pdf). PhD in Scientific Computing, 2013.
- Nathan Lay, "Artificial Prediction Markets for Classification, Regression and Density Estimation"
(pdf). PhD in Scientific Computing, 2013.
Research Scientist, National Cancer Institute, MD.