Haixu Ma @ UNC-Chapel Hill

Welcome to my homepage! My name is Haixu Ma (马海旭). I am a Ph.D. candidate in Statistics from Department of Statistics and Operations Research at University of North Carolina at Chapel Hill. I am fortunate to be advised by Professor Yufeng Liu and Professor Donglin Zeng. I obtained my B.S in Statistics from School of Mathematical Sciences, Nankai University. My PhD research interests mainly focus on Statistical Machine Learning, Personalized Recommendation/Decision Making, Causal Inference, and Reinforcement Learning. Thanks to my recent internship experience at Adobe, I have gained exposure and stepped into research topics about Large Language Models in Generative AI. Linkedin | Twitter | Github | Google Scholar Contact: haixuma at live dot unc dot edu

Recent News

• 04.2024: Glad to share our paper Disentangling Sex-Dependent Effects of APOE on Diverse Trajectories of Cognitive Decline in Alzheimer's Disease has been accepted by Neuroimage. Our work leverages change point detection to elucidate the complex temporal dynamics of cognitive decline in Alzheimer's Disease.

• 08.2023: Join Amazon as an Applied Scientist Intern. Excited to explore Action URL detection for better Personalized Ranking.

• 07.2023: Will present our JMLR paper at Journal to Conference Track in ICML 2023. Check our Video and Poster. See you in Hawaii!

• 05.2023: Come back to Adobe as a Machine Learning Engineering Intern. Excited to explore projects about estimating heterogeneous treatment effects using Large Lauguage Models with Generative AI.

• 05.2023: Passed the preliminary exams. Finally got advanced to a Ph.D. candidate.

• 12.2022: Will present our paper Learning Individualized Treatment Rules with Many Treatments: A Supervised Clustering Approach Using Adaptive Fusion at NeurIPS 2022. Check our Video and Poster.

• 08.2022: Will present our paper Learning Optimal Group-structured Individualized Treatment Rules with Many Treatments at JSM 2022.

• 05.2022: Join Adobe as a Machine Learning Engineering Intern. Excited about the intern projects using Causal Machine Learning methods for personalized recommendation.

• 01.2022: Happy to join Advanced Computational Medicine Laboratory as a Research Assistant supervised by Professor Guorong Wu. Excited to explore multi-stage progression of Neuro-degeneration in Alzheimer’s Disease using High-dimensional Change Point Detection.

• 07.2018: Happy to join Collaborative Center for Statistics in Science at Yale University as a Research Intern supervised by Professor Heping Zhang.

Honors and Rewards

• Best Student Paper Award in Biopharmaceutical Section, American Statistical Association, 2022
  Paper: Ma, H., Zeng, D., and Liu, Y. (2023). Learning Optimal Group-structured Individualized Treatment Rules with Many Treatments. Journal of Machine Learning Research, 24(102), 1-48
  Also presented at Journal to Conference Track in ICML 2023, see our Video and Poster

• Trainee Highlight Award (THA) Honorable Mention, 9th Annual Brain Initiative Meeting, 2023
  

• Malcolm Ross Leadbetter Graduate Student Excellence Award for Outstanding Performance in Ph.D. Research, Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, 2023
  

• Cambanis-Hoeffding-Nicholson Award for Outstanding Performance in Ph.D. Qualifying Exams and Academic Studies, Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, 2020
  

• Raj Chandra Bose Graduate Student Travel Award, Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, 2022
  

Services

• Journal Reviewer: Journal of the American Statistical Association (JASA), Annals of Applied Statistics (AOAS), Journal of Multivariate Analysis

• Conference Reviewer: ICML 2023&2024, AISTATS 2023&2024, KDD 2023, NeurIPS 2023&2024, LoG 2023, ICLR 2024

• Program Chair: SDM 2024