Uri Laserson
Algo Developer at Hudson River Trading
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolUri Laserson is an algorithm developer based in New York with 14 years of experience and a PhD from MIT. He co-founded and served as CTO of Patch Bio, leading R&D that combined high-throughput sequencing with machine learning to design synthetic regulatory elements, raising $11.5M and engineering a successful acquisition by Ginkgo. His background spans academia and industry—from assistant professor to Senior Director of AI Research—bringing both scientific rigor and product leadership. An active open-source contributor, he has made systems-level contributions to projects like numba, ibis, impyla and ADAM (work on data types, CFFI/LLVM integration, DB clients and genomics formats), reflecting deep backend and low-level engineering skills. At Hudson River Trading he now applies that rare blend of wet‑lab genomics, ML modeling, and low-level systems engineering to build high-performance production algorithms and data pipelines.
15 years of coding experience
22 years of employment as a software developer
PhD, PhD at Massachusetts Institute of TechnologyBA, BA at New York University
Hebrew
Stackoverflow
2,411reputation
2.2mreached
8answers
33questions
Github Skills (48)
apache210
spark10
python10
machine-learning10
apache10
java10
scala210
numpy10
scala10
javas10
compiler-compiler10
sql10
parquet10
bioinformatics10
compression10
Programming languages (15)
Github contributions (5)
cloudera/impyla
May 2013 - Feb 2016
Python DB API 2.0 client for Impala and Hive (HiveServer2 protocol)
Role in this project:
Back-end Developer
Back-end DeveloperContributions:256 commits, 54 PRs, 90 pushes in 2 years 9 months
Contributions summary:Uri's contributions primarily involve implementing features and fixing bugs in the Python client for the Impala distributed query engine. They added support for new features like parameterizable queries and improved the existing API functionality for handling data types such as TIMESTAMP and DECIMAL. The user also refactored the code for modularity and enhanced the internal logging systems for improved debugging and monitoring.
apipythonhiveserver2python-dbpresto
sryza/aas
Nov 2014 - Feb 2017
Role in this project:Data Scientist
Data ScientistContributions:23 commits, 9 pushes, 6 comments in 2 years 3 months
Contributions summary:Uri contributed to genomics data analysis and predictive modeling. They implemented code for transcription factor (TF) prediction, including loading and processing genomics data (phylop, gencode, DNase, ChIP-seq). The user designed and utilized a motif scoring function and integrated the results into a model generating features such as phylop scores, and distances to transcription start sites. The changes also include the addition of a 1000 Genome analysis framework.
analyticso-reillyspark
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