Alexander Lachmann
Manager Statistical Genetics
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolAlexander Lachmann is a statistical genetics and biomedical informatics leader with a Ph.D. from Columbia University and over a decade of research and engineering experience translating gene expression and regulatory networks into scalable, cloud-native analysis platforms. He has led development of comprehensive knowledge-bases for transcription factor binding and kinase-substrate interactions and reverse-engineered cell context–specific regulatory networks to drive biological discovery. At Mount Sinai he built cloud-based infrastructures enabling large-scale physiological and genetic analyses, and now leads statistical genetics efforts at Regeneron. Equally comfortable in wet-lab biology and software engineering, he combines deep domain expertise with production-level tooling to connect complex datasets to actionable hypotheses. His background in computer science (RWTH Aachen) and early work on pattern discovery with Xerox-informed algorithms hints at a long-standing focus on extracting structure from noisy biological data.
8 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Biomedical Informatics, Doctor of Philosophy (Ph.D.), Biomedical Informatics at Columbia University in the City of New YorkDiplom, Computer Science, Diplom, Computer Science at RWTH Aachen University
English, German, Dutch
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (30)
loess10
seq10
rna-seq10
python-bindings10
jupyter9
catalog9
bioinformatics9
jupyter-notebook9
genomics9
python8
interpolation8
systems-biology7
prediction6
pipeline5
notebook4
Programming languages (9)
Github contributions (5)
MaayanLab/archs4r
Nov 2021 - Mar 2025
Contributions:1 release, 55 pushes, 1 branch in 3 years 4 months
MaayanLab/blitzgsea
Sep 2021 - Jan 2023
Fast Gene Set Enrichment Analysis (GSEA) implementation of the prerank algorithm. Use Loess interpolation of bimodal ES distribution for accurate p-value estimation.
Contributions:1 release, 5 reviews, 232 commits in 1 year 4 months
python-bindingsestimationinterpolationbioinformaticsaccurate
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