Gonzalo Benegas
Research Scientist at Open Athena
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolGonzalo Benegas is a research scientist in New York with 12 years of experience applying machine learning to scientific domains and adapting large language models to new problem spaces. He holds a PhD in Computational Biology from UC Berkeley and has a track record bridging academic research—developing methods like GPN-MSA, scQuint, and particle-filter/RJ-MCMC approaches for gene regulation—with production software engineering for scalable web and geospatial systems. At Berkeley he combined deep probabilistic modeling with practical tooling, and his open-source contributions include backend enhancements to urbansim for urban simulation and geospatial APIs. Now at Open Athena, he focuses on AI for science, bringing both rigorous probabilistic thinking and hands-on systems skills to deploy models in domain-specific settings. A less obvious strength is his ability to move between fast-paced product engineering (Autodesk, Synthicity) and long-horizon research, making him effective at turning novel algorithms into usable software.
12 years of coding experience
9 years of employment as a software developer
PhD, Computational Biology, PhD, Computational Biology at University of California, BerkeleyBS+MS, Computer Science, 9.7/10, BS+MS, Computer Science, 9.7/10 at Universidad de Buenos Aires
Stackoverflow
53reputation
565reached
0answers
1question
Github Skills (12)
api-rest10
rest-api10
python10
api-design10
restful-api10
yaml9
bottle9
data-analysis8
webservice8
json7
parallel-processing6
openmp6
Programming languages (7)
Github contributions (5)
UDST/urbansim
Mar 2014 - Aug 2014
Platform for building statistical models of cities and regions
Role in this project:
Back-end Developer
Back-end DeveloperContributions:22 commits in 5 months
Contributions summary:Gonzalo made significant contributions to the backend of the urbansim project. They enabled CORS for cross-origin requests, indicating work on API access and web service functionality. Furthermore, the user added new features to list and write configurations as well as charts data, using Python and related libraries. In addition, the user made some modifications to the data query functionality.
regionsstatisticalstatistical-models
songlab-cal/scquint-analysis
Apr 2021 - Mar 2022
Contributions:68 commits, 53 pushes, 2 branches in 10 months
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