lang.zeng@pitt.edu

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Hi there! I am Lang Zeng, a Ph.D. Candidate in the Department of Biostatistics at the University of Pittsburgh, advised by Professor Ying Ding. My research centers on deep learning and its statistical foundations in predictive modeling using multi-modal biomedical data for better disease prediction and management.

I am on the 2025-2026 job market.

Research Interest

  • Deep Learning and Non-/Semi-parametric Theory: Develop deep learning-based non-/semi-parametric models with high-dimensional covariates and establish theoretical foundations for survival analysis and rank-based statistical learning.
  • Statistical Modeling for Risk Prediction with Multi-modal Biomedical Data: Develop predictive models for individualized disease progression by integrating imaging, genetics, and electronic health record (EHR) data. Applications include age-related eye diseases, Alzheimer’s disease, and event forecasting in oncology clinical trials.
  • Collaborative Biomedical Applications: Address pressing biomedical questions through collaborations, including identifying proteomic signatures in Alzheimer’s disease and lung disease, and advancing statistical solutions for challenges such as cell type clustering and doublet detection in single-cell sequencing data.

Education

  • Ph.D. in Biostatistics, University of Pittsburgh, 2021–2026 (June, Expected)
  • M.S. in Biostatistics, University of Michigan, 2018–2020
  • B.Sc. (Minor) in Mathematics and Applied Mathematics, Peking University, 2015–2018
  • B.Med. in Preventive Medicine, Peking University, 2013–2018