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Current Students

  1. Younghwan Cho - Feature Selection
  2. Jungwon Hwang - Robotic Manipulation
  3. Rittwika Kansabanik - Video Quality Prediction/Feature Selection
  4. Pei-Tien Lu - Natural Language Processing
  5. Sourita Nag - Deep Learning
  6. Chen Zhao - Feature Selection

Graduated Students

  1. Siquan Zhu, "Class Incremental Object Detection" (pdf). PhD in Statistics, 2025.
  2. Cheng Long, "A Study of Shape Modeling Against Noise" (pdf). PhD in Statistics, 2024. Machine Learning Engineer, Microsoft.
  3. Ke Han, "Semi-Supervised Few-Shot Learning with Probabilistic Principal Component Analyzers" (pdf). PhD in Statistics, 2024. Machine Learning Engineer, Amazon.
  4. Yijia Zhou, "Scalable Clustering: Large Scale Unsupervised Learning of Gaussian Mixture Models with Outliers" (pdf). PhD in Applied Mathematics, 2023. AI Researcher, Huawei, China.
  5. 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.
  6. Boshi Wang, "Scalable Learning with Probabilistic PCA" (pdf). PhD in Statistics, 2023. Senior Image Quality Engineer, GE Healthcare.
  7. Hongyu Mou, "Sparse Dictionary Learning & The Compact Support Neural Network" (pdf), PhD in Statistics, 2022.
  8. Sida Liu, "Efficient Methods for Unsupervised Learning". PhD in Statistics, 2021. Machine Learning Engineer, J.P. Morgan Chase.
  9. Mingyuan Wang, "Online and Offline Feature Screening and Applications" (pdf). PhD in Statistics, 2021. Quantitative Medicine scientist, Critical Path Institute, Tucson, AZ.
  10. Hua Huang, "Robust Machine Learning and the Application to Lane Change Decision Making Prediction" (pdf). PhD in Applied Mathematics, 2021. Machine Learning Scientist, Google.
  11. Orhan Akal, "Deep Learning Based Generalization of Chan-Vese Level Sets Segmentation". PhD in Applied Mathematics, 2020. Senior Machine Learning Scientist, ShotTracker, FL.
  12. Yangzi Guo, "A Study of Feature Interactions and Pruning on Neural Networks" (pdf), PhD in Applied Mathematics, 2020. Senior Machine Learning Research Engineer, Qualcomm.
  13. Donghang Li, "Steerable Convolutional Neural Networks" (pdf), PhD in Statistics, 2020. Biostatistician, Roche, Shanghai, China.
  14. Lizhe Sun, "Online Feature Selection with Annealing and Its Applications" (pdf), PhD in Statistics, 2019. Assistant Professor, Shanxi University of Finance and Economics, China.
  15. Gitesh Dawer, "Neural Rule Ensembles: Encoding Feature Interactions into Neural Networks" (pdf), PhD in Mathematics, 2018. Machine Learning Team, Apple Corporation.
  16. Josue Anaya, "First Steps Towards Image Denoising Under Low-Light Conditions" (pdf). PhD in Statistics, 2017. Predictive Revenue Analyst, Bankers Healthcare Group.
  17. Ajay Gupta, "Modeling Multivariate Data with Parameter-Based Subspaces" (pdf). PhD in Statistics, 2016. Research Scientist at Bank of America, Charlotte, NC.
  18. 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.
  19. Liangjing Ding, "Sparse Motion Analysis" (pdf). PhD in Scientific Computing, 2013.
  20. Nathan Lay, "Artificial Prediction Markets for Classification, Regression and Density Estimation" (pdf). PhD in Scientific Computing, 2013. Research Scientist, National Cancer Institute, MD.