Jacob Kimmel
Co-founder & President at NewLimit
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolJacob Kimmel is a biotech founder and computational biologist with 11 years of experience building ML-driven experimental platforms to develop epigenetic reprogramming therapeutics. As Co-founder and President of NewLimit, he translates cell‑scale discoveries into drug programs, drawing on prior leadership as a Principal Investigator at Calico where he ran pooled screening and single‑cell reprogramming platforms. He holds a PhD from UCSF where he developed quantitative imaging and machine‑learning tools (Heteromotility, Lanternfish, scNym) to map stem cell state and aging dynamics, and his work has been supported by NSF, Chan Zuckerberg Biohub, and industry partners. Equally comfortable in code and the lab, he contributes to open-source statistical tooling (notably fixes and tests in statsmodels) and has a track record of shipping robust computational methods for single‑cell genomics and timelapse imaging.
11 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Developmental & Stem Cell Biology, Doctor of Philosophy (Ph.D.) Developmental & Stem Cell Biology at University of California, San Francisco
Stackoverflow
53reputation
14kreached
0answers
2questions
Github Skills (14)
statistics10
regression-models10
hypothesis-testing10
hypothesis-tests10
python10
testing10
data-analysis9
forecasting7
forecast7
regression6
csv6
coordinates6
numpy6
linear-regression6
Programming languages (6)
Github contributions (5)
statsmodels/statsmodels
Jul 2017 - Aug 2017
Statsmodels: statistical modeling and econometrics in Python
Role in this project:
Data Scientist & QA Engineer
Data Scientist & QA EngineerContributions:12 commits, 1 PR, 15 comments in 10 days
Contributions summary:Jacob primarily contributed to the `statsmodels` library by implementing and testing statistical functions. They focused on the Lilliefors test, fixing p-value bounds, adding unit tests for normal and exponential distributions, and addressing errors. The contributions include code modifications and the addition of test cases, indicating a focus on improving the accuracy and reliability of statistical testing functionalities within the library.
forecastingpythonregression-modelsstatsmodelsstatistics
cellgeometry/heteromotility
Nov 2017 - Sep 2018
Quantitative analysis of cell motility behaviors
Contributions:2 releases, 17 commits, 1 PR in 10 months
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