Every day the genome grows more accessible: biochemically, computationally, and medically. I build tools to one day make genetically targeted medicine accessible for everyone. To get there I am pursuing an MD-PhD, because going from sequence to symptom takes expertise in both.

I started as a computer engineer building machine learning systems for health and biomedical research. Now, as a Research Specialist in the Stern Lab at HHMI and the Stowers Institute, I study population genetics, model evolution with deep learning, and assemble and annotate high-quality genomes. The Stern Lab's comprehensive approach allows me to bridge science from the field and microscope, through sequencers, and into AI.

My MPH focused on psychiatric epidemiology, with research on gender, autism, and ADHD. For four years I helped teach a graduate public-health course that paired epidemiology students with autistic adults as collaborators, emphasizing accessibility, participatory research, and dignity of care.

An MD-PhD will bring these together: research at the bench, teaching in the lab, and care in the clinic. Patients deserve the latest science and a clear explanation of it, and making narrowly tailored, advanced medicine accessible to broad populations is what makes the long journey worth it.

Genetics & genomics Machine learning Immunology Computational biology Epidemiology Health equity
Experience

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2025 – present

Research Specialist

HHMI / Stowers Institute, Stern Lab
Evolutionary genetics, computational biology, and comparative genomics. Supervisor: Dr. David L. Stern.
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2024 – 2026

Instructional Assistant & Guest Lecturer

George Washington University, Milken Institute SPH
Autism: A Public Health Perspective. Community-based participatory research and annual lectures.
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2018 – 2025

Senior Machine Learning Engineer & Health Researcher

The MITRE Corporation
Deep learning, biotechnology, and health-systems research.
2015 – 2018

Earlier engineering roles · Deloitte, Citigroup, Capital One, ARRIS Group

Education

2023

M.P.H., Public Health

The George Washington University
Women and gender minority health; psychiatric epidemiology.
2024 – 2026

Premedical Coursework

Northern Virginia Community College
Biology, Organic Chemistry, Biochemistry, Cell Biology.
2018

B.S., Computer Engineering

Georgia Institute of Technology
Digital signal processing; healthcare data security.

Selected Publications

Selected Presentations

  • Development, Regulatory Genomics & AI
    Stowers Institute for Medical Research, Kansas City, MO. April 2026.
  • ASPIRE RIKEN Meeting
    Cold Spring Harbor Laboratory, Cold Spring Harbor, NY. December 2025.
  • Annual guest lectures on autism epidemiology, gender, and pharmacology
    The George Washington University. Spring 2024 – 2026.

Clinical & Service

2020 – 2026

Volunteer, Virginia Medical Reserve Corps

President's Volunteer Service Award, Silver
Vaccine clinics and patient counseling, contact tracing, sanitation, and resource distribution to at-need communities.
2022 – 2024

Wilderness First Responder (NOLS)

Backcountry medical response
Primary medical resource for a climbing team; responded to more than a dozen front- and backcountry emergencies.
2019 – 2025

USA Climbing Level 2 Certified Coach

Sportrock Climbing Centers, Alexandria, VA
Coached youth and adult athletes, including national-level competitors; training, nutrition, and injury care.
2024 – 2026

Global Affairs and Religion Network

The George Washington University
Active member of the research group and journal club.

Languages

EnglishNative
Mandarin ChineseIntermediate
JapaneseIntermediate
HindiConversational

Selected Skills

Programming
Python Java C++ SQL Scala R STATA Bash
AI & Machine Learning
PyTorch TensorFlow Keras scikit-learn Ray / RLlib MLflow Hugging Face
Bioinformatics
Nextflow hifiasm BWA samtools NCBI (BLAST, SRA) Bioconda PacBio pbtk
Cloud, DevOps & Data
AWS Azure Docker Kubernetes Terraform PySpark Neo4j Parquet
Download full CV (PDF)
Contact

Best reached by email. I am always glad to talk about genomics, public health, or physician-scientist training.

Email me
GitHub ORCID Google Scholar LinkedIn
Personal

Outside the lab — a few of the things I love.

Long distance running
Long distance running
Mountaineering
Mountaineering
Dancing
Dancing
Enjoying my kilts
Enjoying my kilts
Taking climbers to new places
Taking climbers to new places
Learning to hot air balloon
Learning to hot air balloon
Actually climbing myself
Actually climbing myself
Naturalist
Naturalist

Evolutionary & population genetics

Stern Lab, HHMI and the Stowers Institute.

Developing red gallGall cross-sectionsHyphae inside a gall
Developing red gall
The approach

What parasitic systems reveal

Stern Lab · HHMI / Stowers

In the Stern Lab, I research parasitic relationships, where one species reaches across a biological boundary to control how another grows. These interactions are strikingly aggressive: parasites hijack their host's development, manipulate its immune system, and direct its tissues with precision. I study how that machinery works, and how it has evolved.

To find those mechanisms, I have learned to use population and comparative genetics across many related species. Comparing their genomes shows which regions are conserved and which have been rewritten. This illuminates the specific proteins that enable this relationship and trace them as these lineages diverge. The lab favors rapidly evolving systems because change accumulates fast enough to follow clearly. I take part in every stage of that work, from collecting samples in the field to the final analysis.

In the end, these are the same problems the human body has to solve. Immune evasion, developmental control, and the genetic conflict between host and parasite all have direct parallels in human disease, from infection to allergy to autoimmunity. Mechanisms that are nearly impossible to isolate in people are often discovered in these alternative systems. That is the goal of my work: using evolution's clearest experiments to one day understand the biology behind human disease.

Exploring phylogenetic relationshipsHi-C contact map
Exploring phylogenetic relationships
The methods

From genomes to models

Stern Lab · HHMI / Stowers

Answering these questions takes genomes, many of them, with high quality sequences and across the tree of life. In the Stern Lab I learned to assemble and annotate new reference genomes and set them in their evolutionary context, comparing hundreds of species at once. Reading conservation and divergence across that comparison is how candidate genes and proteins first come into view. A pattern only becomes convincing once you can watch it repeat across lineages.

Getting there is a genuine engineering problem. Raw sequencing data has to be assembled, decontaminated, scaffolded to chromosome scale, and annotated before any of it can be compared. Together with Dr. Stern, I built and run petabyte-scale pipelines that turn trillions of reads into finished, trustworthy genomes. My engineering background helped me make that process reproducible, so the biology we discover is accurate and real.

Finally, I build deep-learning models that discover new biology within those genomes. My models capture relationships and adaptations that conventional comparisons would miss: thousands, and potentially millions of proteins that have been overlooked. My models predict how proteins relate and evolve, and then surface new candidates worth chasing at the bench. It is where the computation finally points back at biology, and, I hope one day, at medicine.

Autism, gender & diagnosis

George Washington University, Milken Institute SPH
ASD and ADHD diagnosis by income and sex
ASD and ADHD diagnosis by income and sex
Public health

Who gets diagnosed

George Washington University, Milken Institute SPH

In the Milken Institute School of Public Health, my research in psychiatric epidemiology focused on studying how autism and ADHD are actually diagnosed across a population. Those diagnoses are far from neutral: who receives one, and when, turns heavily on sex, gender, and family income, and working with nationwide datasets I traced those disparities and the tension between the biological and social stories told to explain them.

Correlates of autism diagnosis
Correlates of autism diagnosis
Dignity of Care

Making science accessible

George Washington University, Milken Institute SPH

I worked, taught, and learned alongside nonspeaking autistic adults. They were research partners, communicating through assistive devices and reshaping the questions I thought to ask. Together, we taught graduate students, using autistic voices as inspiration, my research methods as implementation, and students' creativity for the application, eventually handing the findings back to the autistic community that needed them. This is the other half of how I understand medicine: genetics can explain a mechanism, but epidemiology and lived experience explain who a condition reaches and how it is met.

Children's mental health

The MITRE Corporation
A Vision for Mental Health Systems of Care for Young People
Health systems

From federal to personal

The MITRE Corporation

In my later years at MITRE, I worked on machine learning and epidemiology for public health. Under Liz Oppenheim, I conducted an evaluation of the federal programs meant to support children's mental health: we gathered all federal programs targeting children's mental health into a single analytic framework and modeled which of their goals were actually sensitive to funding. We were after a hard, practical question — where the money helps, and where it doesn't. The work became part of a published report I co-authored and presented to a council of healthcare executives. You can find the report here.

Chesapeake Bay chlorophyll · Sentinel-2 via Google Earth Engine
Chesapeake Bay chlorophyll · Sentinel-2 via Google Earth Engine
Engineering

Biotechnology and geospatial intelligence

The MITRE Corporation

For the first half of my time at MITRE I was building machine learning for biotechnology, biomedical and geospatial data. I designed deep-learning systems for satellite imagery, processing both raster and spectral images for ecosystem and human health. I built databases and AI compatible systems to make messy laboratory and flow-cytometry data searchable. Other projects reached further afield, from multi-agent reinforcement learning to multi-government deployments. This time at MITRE is what brought the engineer out in me, turning ideas into useable systems.

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