About Me

I am a PhD student at Department of Statistics, The Pennsylvania State University. I am fortunate to be advised by Professor Matthew Reimherr. Prior to this, I received my Bachelor degree in Statistics from University of Science and Technology of China.

My research interests are mainly forcing on functional/longitudinal data, statistical transfer learning and differential privacy with kernel methods. Currently, I’m working on accurately and adaptively estimating the discrepancy between different domains in transfer learning and multi-task learning.

Preprints

• Spectral Algorithms with Gaussian Kernels: Robustness and Optimality.
  Haotian Lin and Matthew Reimherr
  (Under Review)

• Smoothness Adaptive Hypothesis Transfer Learning.
  Haotian Lin and Matthew Reimherr
  [arXiv] (Under Review)

• On Hypothesis Transfer Learning in Functional Linear Models.
  Haotian Lin and Matthew Reimherr
  [arXiv] (Under Review)

• Pure Differential Privacy for Functional Summaries via a Laplce-like Process.
  Haotian Lin and Matthew Reimherr
  [arXiv] (Under Revision)

Industrial Experience

• Google - Data Sicentist Intern
  May 2022 - Aug. 2022

Teaching at Penn State

• STAT-440: Computational Statistics (Spring 2023).

• STAT-319: Elementary Mathematical Statistics (Spring 2022).