Yen-Chun Liu

Yen-Chun Liu

Statistics PhD student

Duke University

About Me

I am a fourth-year PhD student in statistics at Duke University working with Prof. Simon Mak, co-advised by Prof. Eric Laber and Prof. Alex Volfovsky. My research interests include but not limited to Bayesian optimization, Gaussian processes, and reinforcement learning. Before joining Duke, I worked with Professor Yu-Jen Cheng and Professor Chiung-Yu Huang on a paper about improving estimation of the transformation model by leveraging external heterogeneous information.

Besides studying statistics, I enjoy engaging in outdoor activities and reading. I am also passionate about various social issues including environmental sustainability and social equity.

Interests
  • Bayesian Optimization
  • Gaussian Processes
  • Reinforcement Learning
  • Experimental Design
Education
  • PhD student in Statistical Science, 2022 -

    Duke University, United States

  • MS in Statistics, 2022

    National Tsing Hua University, Taiwan

  • BS in Mathematics, 2020

    National Taiwan University, Taiwan

Recent Publications

(2024). Salvage therapies including retreatment with BCMA-directed approaches after BCMA CAR-T relapses for multiple myeloma. Blood Advances.

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Teaching

 
 
 
 
 
Duke University
Teaching Assistant
Duke University
January 2023 – Present North Carolina
STA 532 Theory of Statistical Inference, STA 561 Probabilistics Machine Learning, STA 332 Statistical Inference
 
 
 
 
 
Undergraduate Summer Statistics Workshop, Duke University
Graduate Mentor
Undergraduate Summer Statistics Workshop, Duke University
May 2023 – May 2023 North Carolina
Mentoring a group of 5 undergraduate students analyzing a Chinese given name dataset.
 
 
 
 
 
National Tsing Hua University
Teaching Assistant
National Tsing Hua University
January 2022 – June 2022 Taiwan
STA 661 Survival Analysis
 
 
 
 
 
National Taiwan University
Teaching Assistant
National Taiwan University
September 2018 – June 2019 Taiwan
MATH 120 Calculus A (I) & (II)

CV

My CV (September, 2025).