Kelvin Mo

About Kelvin Mo

I am a 24-year-old first-year PhD student in Harvard's Biological and Biomedical Sciences program. My north star is to engineer immune therapies that are as programmable as software by fusing rigorous biology with modern machine learning.

Before Harvard, I split my undergraduate journey between UC San Diego and UC Berkeley while working closely with clinician-scientists at Stanford, Genentech, Novartis, and Intel. Across these teams I built computational systems that translated raw experimental data into strategies for therapeutics and manufacturing.

I care deeply about mentorship. The work only matters if it opens doors for the next generation of scientists who look like the patients we hope to serve.

Systems thinker

Designs full-stack workflows that unite wet-lab, computation, and clinical vantage points.

Builder

Ships production-ready ML pipelines, from single-cell analytics to bioreactor control systems.

Mentor

Leads learning pods and curricula that bring undergraduates into cutting-edge research early.

Story: hacking the academic system

When I arrived at Stanford's Mackall Lab, computational work was outsourced, and precious patient data sat idle. I pitched a new approach: build an in-house, end-to-end single-cell analysis pipeline that clinicians, immunologists, and data scientists could all trust.

I learned wet-lab workflows so I could map every experimental decision to its computational twin. Nights were spent pairing scRNA-seq processing scripts with the clinical metadata our fellows captured in real time.

The result was the first on-treatment single-cell atlas for CAR T therapy in the lab. It uncovered IRF4/IRF8-driven exhaustion programs and chemokine circuits that have since shaped prospective trials.

Current focus

Education

PhD, Biological and Biomedical Sciences
- Harvard University
Sep 2025 - Jun 2030

Doctoral research aimed at programmable cancer immunotherapies and spatial immune modeling.

B.A., Data Science & Molecular and Cell Biology
- University of California, Berkeley
Sep 2021 - Dec 2023

Integrated data science frameworks with advanced molecular biology to prototype translational pipelines.

B.S., Bioinformatics & Computer Science
- University of California, San Diego
Sep 2019 - Jun 2021

Built the computational tooling foundation that powers Kelvin's current lab work.

Experience

Life Science Research Professional
- Stanford University School of Medicine
Mar 2023 - Present
  • Characterized CAR T exhaustion and myeloid biology for the first on-treatment scRNA-seq cohort in LBCL, surfacing biomarkers for new trials.
  • Predicted CD19-CAR response and toxicity using multimodal ML classifiers on pre-infusion immune features, integrating sgGPT-based transformers.
  • Mapped temporal and spatial programs in GD2-CAR therapy for diffuse midline glioma using CosMx, CITE-seq, and proteomic readouts.
  • Built the lab's single source of truth for patient metadata, wet-lab instrumentation, and ML pipelines, enabling real-time translational decisions.
Biotechnology Development Intern
- Genentech
Jun 2022 - Dec 2022
  • Implemented Raman spectroscopy-based feedback control for cell culture bioreactors, enhancing feed control capabilities.
  • Delivered dashboards and automation that reduced manual interventions during pilot biologics runs by 80%.
Data Science Intern
- Novartis
Jun 2021 - Aug 2021
  • Built ranking models on structure-aware embeddings to triage antibody screening campaigns.
  • Deployed decision-support tooling that accelerated hit triage for wet-lab partners.
Data Science Intern
- Intel Labs
Jan 2021 - Oct 2021
  • Built accelerator-aware inference pipelines for large-scale biological simulations and HPC clusters.
  • Published internal whitepapers to senior leadership on GPU/CPU utilization for omics workloads.
Lead Data Analyst
- UC San Diego School of Medicine
Mar 2020 - Jun 2021
  • Constructed tension-area hysteresis analyses and impedance-based manometry tooling for EGJOO patients.
  • Led data ingestion for clinical swallow studies and mentored undergraduates in reproducible analytics.
Research Intern
- Singlera Genomics
Jul 2019 - Sep 2019
  • Shipped early prototypes for cfDNA analytics and assay QC dashboards.
  • Anchored Kelvin's transition from pure wet-lab work into computational biology.

Reach out

Let us build the next generation of immune therapies together.

Email Kelvin LinkedIn GitHub