Euxhen Hasanaj

Research Scientist at GenBio AI

Palo Alto, California, United States
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Summary

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Senior
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Top School
Euxhen Hasanaj is a research scientist at GenBio AI with a PhD in Machine Learning from Carnegie Mellon and eight years of experience applying ML to biotechnology and drug design. He develops multiscale foundation models to predict single-cell perturbation responses and has a track record of translating research into practical tools—examples include SenSet, a 106-gene senescence signature, and Truffle, an algorithm for integrating clinical transcriptomic time series accepted to ISMB 2024. His work spans graph learning, generative models, and biological foundation models with prior internships at Genesis Therapeutics and Sanofi focused on de novo drug design and patient stratification. Based in Palo Alto, he blends deep academic training with production ML experience across healthcare and computer vision, and often targets aging and perturbation-response biology—areas where modeling choices can reveal unexpected biological subtypes.
code8 years of coding experience
job2 years of employment as a software developer
bookBachelor of Arts - BA, Mathematics and Computer Science, Bachelor of Arts - BA, Mathematics and Computer Science at American University in Bulgaria
bookDoctor of Philosophy - PhD, Machine Learning, Doctor of Philosophy - PhD, Machine Learning at Carnegie Mellon University
bookStudy Abroad, International Student Exchange Program (ISEP), Study Abroad, International Student Exchange Program (ISEP) at University of Iowa
languagesEnglish, Italian, Albanian, French
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Github Skills (49)

python10
dimensionality-reduction10
spatial-transcriptomics10
gene-expression10
rna-seq10
bioinformatics10
data-visualization10
genomics10
genomics-visualization10
clustering10
gnn9
biology9
codex9
temporal-data9
graph-embedding9

Programming languages (3)

C++ShellPython

Github contributions (5)

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euxhenh/grinch

Jul 2022 - Sep 2022

A library for differential expression and gene set enrichment analysis based on hydra and pydantic.
Contributions:53 commits, 115 PRs, 107 pushes in 1 month
pydanticclusteringdifferential-expression-analysisgene-set-enrichmentmarker-genes
euxhenh/multiset-multicover

Dec 2021 - Oct 2022

A package for performing multiset multicover using the greedy cover algorithm.
Contributions:6 releases, 39 commits, 2 PRs in 9 months
multisetcpppython
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