Curriculum Vitae

Ashir Borah

PhD candidate · UCSF / Arc Institute · functional genomics, virology, and AI-enabled research systems

ashiraseesh@gmail.com · Google Scholar · ORCID · GitHub · LinkedIn

Download CV (PDF) 1-page résumé

Summary

PhD candidate in the Biological and Medical Informatics program at UCSF, jointly mentored by Luke Gilbert and Brian Hie at the Arc Institute. Research at the intersection of functional genomics, virology, and computational biology — combining CRISPR-based screening, assay development, and high-dimensional data analysis to study gene regulation, host–virus interactions, and disease mechanisms.

In parallel, building AI-enabled research systems — LLM-based councils, research agents, APIs, and multi-agent workflows for literature synthesis, hypothesis generation, experimental planning, and scientific reasoning.

Before UCSF, nearly three years at the Broad Institute on the Cancer Dependency Map, using statistical modeling and machine learning on genome-scale perturbation data to discover and validate cancer targets. B.S. Mathematics & Computer Science from Dickinson College, Magna Cum Laude, Phi Beta Kappa.

Education & positions

  1. Arc Institute

    Jun 2023 — Present
    PhD Researcher · Palo Alto, CA
    • Designing experimental and computational methods for functional genomics and virology.
    • Building CRISPR-based screening and perturbation systems to study gene regulation, host–virus biology, and disease mechanisms.
    • Developing assay platforms and analysis workflows for high-dimensional genomic datasets.
    • Building AI-enabled scientific tooling — LLM councils, APIs, and multi-agent workflows for literature synthesis, hypothesis generation, and experimental planning.

  2. University of California, San Francisco

    Sep 2022 — Present
    PhD Candidate · Biological and Medical Informatics · San Francisco, CA
    M.S., Biological and Medical Informatics · awarded June 2024 (en route to PhD) · advisor: Luke Gilbert
    • PhD research in functional genomics, virology, and computational biology, in collaboration with the Arc Institute.
    • Developing computational and experimental approaches for studying gene regulation, perturbation biology, and disease mechanisms.
    • Analyzing large-scale biological datasets with statistical, machine learning, and high-dimensional methods.
    • Led an R bootcamp for postdocs and clinicians — 100+ trainees.

  3. Broad Institute of MIT and Harvard

    Jul 2019 — Apr 2022
    Computational Associate I & II · Cancer Data Science · Dependency Map Project · Cambridge, MA
    • Validated candidate cancer targets identified through genome-scale CRISPR knockout screens.
    • Applied machine learning and statistical methods to identify vulnerabilities in cancer cell lines, with a focus on GI cancers.
    • Prioritized candidate dependencies for downstream therapeutic investigation.
    • Contributed to an open-source ML platform modeling genetic-knockout dependency profiles across >100,000 genomic features.

  4. Uliza

    Sep — Dec 2017
    Machine Learning Developer
    • Built ML-driven systems to support crowdsourced workflow automation.
    • Set up core technical infrastructure — server management, database optimization, and disaster recovery.

  5. Dickinson College

    2015 — 2019
    B.S. Mathematics & Computer Science · Magna Cum Laude · Phi Beta Kappa · Carlisle, PA
    • Student research project on secure CoAP-DTLS systems for resource-constrained devices.
    • Best Poster, All-College Science Symposium (2019).
    • Teaching assistant for Introduction to Java and Data Structures; tutoring and residential leadership roles.

Publications

1,125 citations · h-index 10 · i10-index 10 View on Scholar →

Peer-reviewed

  1. mTORC1 activity suppresses ferroptosis through a SCARB1-dependent HDL–tocopherol uptake pathway
    T.A. O'Loughlin, J.S. Stiles, P. Acharya, A. Arab, L. Goudy, R. Dai, A.A. Borah, et al.
    Molecular Cell2026
  2. Integrative analysis of mRNA stability regulation uncovers a metastasis-suppressive program in breast cancer
    H. Karner, T.C. Mittmann, V.W. Chen, A.A. Borah, A. Langen, H. Yousefi, L. Fish, et al.
    Science Advances2026
  3. Human Papillomavirus does not fully inactivate p53 cellular activity in HNSCC
    J. Gencel-Augusto, H. Li, L.C. Woerner, N. Tian, A.A. Borah, J.N. Myers, P. Ha, et al.
    Head & Neck2026
  4. SKI complex loss renders 9p21.3-deleted or MSI-H cancers dependent on PELO
    P.C. Borck, I. Boyle, K. Jankovic, N. Bick, K. Foster, A.C. Lau, L.I. Parker-Burns, …, A.A. Borah, et al.
    Nature2025Cited by 22
  5. Integrated epigenetic and genetic programming of primary human T cells
    L. Goudy, A. Ha, A.A. Borah, J.M. Umhoefer, L. Chow, C. Tran, A. Winters, et al.
    Nature Biotechnology2025Cited by 17
  6. A systematic search for RNA structural switches across the human transcriptome
    M. Khoroshkin, D. Asarnow, S. Zhou, A. Navickas, A. Winters, J. Goudreau, …, A.A. Borah, et al.
    Nature Methods2024Cited by 18
  7. In vivo Perturb-seq of cancer and microenvironment cells dissects oncologic drivers and radiotherapy responses in glioblastoma
    S.J. Liu, C. Zou, J. Pak, A. Morse, D. Pang, T. Casey-Clyde, A.A. Borah, D. Wu, et al.
    Genome Biology2024Cited by 18
  8. Lineage-specific canonical and non-canonical activity of EZH2 in advanced prostate cancer subtypes
    V.B. Venkadakrishnan, A.G. Presser, R. Singh, M.A. Booker, N.A. Traphagen, …, A.A. Borah, et al.
    Nature Communications2024Cited by 66
  9. A ubiquitination cascade regulating the integrated stress response and survival in carcinomas
    L.D. Cervia, T. Shibue, A.A. Borah, B. Gaeta, L. He, L. Leung, N. Li, et al.
    Cancer Discovery2023Cited by 66
  10. Partial gene suppression improves identification of cancer vulnerabilities when CRISPR-Cas9 knockout is pan-lethal
    J.M. Krill-Burger, J.M. Dempster, A.A. Borah, B.R. Paolella, D.E. Root, T.R. Golub, et al.
    Genome Biology2023Cited by 39
  11. Sparse dictionary learning recovers pleiotropy from human cell fitness screens
    J. Pan, J.J. Kwon, J.A. Talamas, A.A. Borah, F. Vazquez, J.S. Boehm, et al.
    Cell Systems2022Cited by 43
  12. Microenvironment drives cell state, plasticity, and drug response in pancreatic cancer
    S. Raghavan, P.S. Winter, A.W. Navia, H.L. Williams, A. DenAdel, K.E. Lowder, …, A.A. Borah, et al.
    Cell2021Cited by 611
  13. Repeat expansions confer WRN dependence in microsatellite-unstable cancers
    N. van Wietmarschen, S. Sridharan, W.J. Nathan, A. Tubbs, E.M. Chan, …, A.A. Borah, et al.
    Nature2020Cited by 204

Preprint

  1. Systematic identification of chromatin organizers as tuners of intratumoral heterogeneity
    B.J. Woo, S. Sobti, J.M. Suh, H. Yousefi, K. Garcia, S. Zhou, A.A. Borah, et al.
    bioRxiv2026

Full list, including conference abstracts, on Google Scholar →

Selected honors

  • Spot Award (×2), Broad Institute · 2020, 2021
  • Phi Beta Kappa Honor Society · 2019
  • Best Poster, All-College Science Symposium · 2019
  • Richard Howland Memorial Scholarship · sole CS recipient · 2018
  • Pi Mu Epsilon (Mathematics) & Upsilon Pi Epsilon (CS) · 2018
  • Jane Hill Prize in Computer Science · 2016
  • Torchbearer Award, Bhumi · 6 of 8,000 volunteers · 2015

Teaching & mentoring

  1. Instructor — R Bootcamp for Biomedical Research

    2022 — 2024
    University of California, San Francisco
    • Brought the Broad Institute R bootcamp curriculum to UCSF and taught it for three consecutive years to postdocs, clinicians, and graduate students.
    • Adapted the original cancer-data-science curriculum for a broader biomedical audience — 250+ trainees across three offerings.

  2. Research mentor — UCSF PhD rotation students

    2023 — Present
    Gilbert Lab · UCSF / Arc Institute
    • Mentored two UCSF PhD rotation students (Bioinformatics and Tetrad programs) through introductory functional-genomics projects.
    • Provided experimental and computational guidance and supported scientific writing, analysis, and presentation skills.

  3. Course creator & TA — Cancer Program R Bootcamp

    2019, 2021
    Broad Institute of MIT and Harvard
    • Designed and implemented the original curriculum teaching R for cancer data science to postdocs and graduate students.
    • Trained ~100 participants across two offerings; received a Spot Award for voluntarily developing the course.

  4. Teaching assistant — Mathematics & Computer Science

    2016 — 2019
    Dickinson College
    • Courses: Introduction to Programming I & II, Data Structures.
    • Facilitated lab sections, debugged student code, and graded assignments.

Service

  • Ad-hoc peer reviewer · Nature Biotechnology
  • Co-chair, CodeRATS · Broad Institute · 2020–2021 — community for early-career computational researchers
  • Volunteering Coordinator (North India) · Bhumi · 2014–2015 — managed 100+ volunteers, 2,700 hours

Skills & methods

Functional genomics

CRISPR screens (knockout, interference, activation), Perturb-seq, scRNA-seq, viral vector design, mammalian cell culture, cloning.

Single-cell analysis

Scanpy, Seurat, Cell Ranger, scVI, rapids-singlecell (GPU-accelerated), MAGeCK.

Programming & ML

Python, R, PyTorch, JAX. Statistical modeling, dimensionality reduction, foundation models for DNA / RNA / protein.

AI tooling

LLM-based agents, multi-agent workflows, retrieval-augmented systems, LangChain, DSPy, scientific APIs, prompt engineering.

Languages

English (native) · Hindi (professional) · Assamese (conversational)