Hao Zhu
Postdoctoral Fellow at Harvard Medical School
Boston, Massachusetts, United States
Summary
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Rockstar🎓
Top SchoolHao Zhu is a postdoctoral fellow and AI-for-science researcher in Boston with 11 years of experience building scalable, production-ready ML systems and biomedical computational methods. He holds a PhD from Tufts where he developed RegDiffusion, a fast denoising diffusion model and robust causal network inference tools for genomics, and now continues this work at Harvard Medical School and Beth Israel Deaconess. Hao has applied his research in industry at Amazon, building low-latency vector search and RAG pipelines for music applications, and earlier led data science and cloud efforts at Hebrew SeniorLife. An active R open-source maintainer, he contributed notable features to widely used packages such as kableExtra (advanced table styling and image support) and skimr (inline histograms and expanded summaries). He bridges deep research and production engineering—prototyping novel algorithms that are engineered for speed and practical deployment in biomedical and commercial settings. Colleagues know him for combining rigorous statistical thinking with pragmatic software craftsmanship across open-source and clinical research projects.
11 years of coding experience
11 years of employment as a software developer
Master of Arts (M.A.) Clinical Investigation, Master of Arts (M.A.) Clinical Investigation at Boston University School of MedicineDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Tufts UniversityBachelor's degree Chemical Engineering, Bachelor's degree Chemical Engineering at University of Illinois Urbana-ChampaignHigh School
Stackoverflow
7,676reputation
741kreached
107answers
7questions
latex
top-5%
shiny
top-5%
r
top-1%
knitr
top-1%
pdf
top-5%
Github Skills (22)
r-package10
r10
format-table10
formatting10
knitr10
latex10
html10
rmarkdown10
data-analysis10
testing9
shiny9
pdf9
bookdown8
dplyr8
tidyr8
Programming languages (13)
Github contributions (5)
haozhu233/kableExtra
Nov 2015 - May 2022
Construct Complex Table with knitr::kable() + pipe.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 releases, 2 reviews, 603 commits in 6 years 7 months
Contributions summary:Hao contributed to the kableExtra package by implementing new features to enhance table formatting capabilities. Their contributions included the addition of add_footnote and related styling options for HTML and LaTeX tables. The user's work focused on integrating complex functionality, such as multi-row headers and custom styling options like alignment, text color, and background color, into the package. Further, the user introduced support for adding image in the table output.
pipelatexknitrrmarkdownkable
ropensci/skimr
May 2017 - Jun 2017
A frictionless, pipeable approach to dealing with summary statistics
Role in this project:Data Scientist
Data ScientistContributions:17 commits, 7 PRs, 14 pushes in 13 days
Contributions summary:Hao primarily contributed to the development and enhancement of summary statistics functionality within the `skimr` package. They implemented the `inline_hist` function to generate inline histograms for numeric variables. Additionally, the user expanded the package by adding and modifying summary functions for various data types, like logical and character vectors, and integrated these functions into the core skim_v function. The user's work also involved adding test cases and improving the printing of the skim results.
r-packagestatisticsunconf17data-scienceapproach
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