Samuel Friedman

Samuel Friedman

Computational Biologist | NYC

About Me

My journey started in statistical human genetics at Rutgers University. Seeing the transformative potential of machine learning in healthcare and genomics led me to defer MD-PhD acceptances to pursue an MS and, now, career in machine learning –– a decision that has opened up exciting opportunities at the intersection of AI and biological research.

Technical Skills

Languages and Frameworks

PythonRCC++JavaJavaScriptSQLReactFlask

ML and Data

PyTorchCUDASklearnSparkPostgreSQLSQLiteMongoDB

Computational Biology

ScanpyHTSeqPyRangesSeuratBEDToolsBowtie2STAR

DevOps

AWSGCPGitDockerNextflowShell scriptingLinux Server Management

Professional Experience

New York Genome Center

New York, NY

Computational Biologist

Jun 2024 - Present

  • Improving CRISPR: Fine-tuned ESM protein language model, developed XGBoost and CNN classifier models, incorporated proteomics data, and utilized AlphaFold3 at scale to identify motifs that improve CRISPR editing rates
  • Finding sites to target with CRISPR for improved understanding of complex diseases: Utilized Enformer, SQLite, LangChain, and RShiny, and developed a Python package that facilitates CRISPR cas9 guide library development from GWAS fine-mapped loci of complex diseases (three papers -– on Autoimmune, Cardiovascular, and Psychiatric Traits -- in progress; all similar in concept to original STING-seq paper)
  • Created comprehensive RNA-targeting cas13 guide library using TIGER model inference and alignment for off-target effects with Bowtie2
  • Contributed to alignment and preprocessing pipeline of MultiPerturb-seq, a novel pooled CRISPR screen method allowing for dual capture of ATAC and single-cell RNA-seq, along with sgRNA
    Published in Nat. Biotechnol. (2024)

Regeneron Pharmaceuticals, Regeneron Genetics Center

Tarrytown, NY

Genome Informatics & Data Engineering Co-op

Jun 2023 - Dec 2023

  • Developed full-stack web-app with React, Flask, Spark, and AWS
  • Designed a Python pipeline for processing transcriptomic data

Rutgers University, Department of Genetics

Piscataway, NJ

Research Assistant

Jun 2021 - May 2022

  • Created mappings between genetic and phenotypic datasets using Python and R for NIMH Repository
  • Ran statistical analysis to match genetic profiles and eliminate 15% redundancy in biosample identifiers

Projects

Education

Columbia University, School of Engineering

New York, NY

Master of Science in Computer Science, Machine Learning track

Sep 2022 - May 2024

  • Courses: Algorithms, Systems Programming, OS, AI, ML, Deep Learning in Genomics, NLP, Databases
  • Leadership: President & Co-Founder of Columbia Artificial Intelligence Society for Graduate Engineers

Rutgers University, Honors Program

New Brunswick, NJ

Bachelor of Arts in Genetics, summa cum laude

Sep 2017 - May 2021