About
Bioinformatics researcher with expertise in applying machine learning to complex biological challenges. Holds an MS in Bioinformatics from Johns Hopkins University with specialization in machine learning, computational and structural biology, and drug design. Published researcher at top-tier machine learning conferences, with hands-on experience spanning therapeutic antibody design to protein expression analysis in cancer research. Combines deep technical expertise in machine learning, computational biology, and data science with proven science communication skills, enabling effective cross-disciplinary collaboration and translation of complex research into practical applications.
Education
Johns Hopkins University | 4.0 GPA
MS, Bioinformatics
Research: “Bridging Quantum and Classical Computing in Drug Design”
Honors: Patrick Cummings Research Award for exceptional research in the field of biotechnology
Key Coursework:
Middlebury College | 3.91 GPA
BA, Religion, Philosophy, and Political Science
Honors: summa cum laude, Theodore S. Woolsey Prize (department award), Phi Beta Kappa Honor Society, thesis with highest honors
Technical Skills
Machine Learning
Programming
Bio & Cheminformatics
Data & Operations
Data Visualization
Quantum Computing
Projects
Bridging Quantum and Classical Computing in Drug Design: Architecture Principles for Improved Molecule Generation
Published at ICML 2025 - Generative Biology Workshop
Developed a hybrid quantum-classical machine learning architecture for drug discovery that achieved a 2.27-fold improvement in candidate quality while using 60% fewer parameters than classical baselines
De novo Antibody Generation with RFdiffusion
Developed a complete computational antibody design pipeline using diffusion models to generate novel therapeutic antibodies from scratch, created an accessible Google Colab notebook for public use, and authored an educational tutorial demonstrating the end-to-end process from target selection to structural validation
Protein Expression Analysis in Esophageal Cancer
Built a full-stack tool to analyze protein expression patterns in esophageal cancer, integrating SQL databases, Python analysis, and interactive visualizations to identify potential therapeutic targets
Algorithmic Approaches to mRNA Pseudoknot Prediction
Evaluated computational approaches for RNA structure prediction, achieving 11% faster prediction of pseudoknot motifs through combination of machine learning algorithms
Algorithmic Foundations of Quantum Machine Learning
Authored a comprehensive theoretical analysis examining the mathematical differences between classical neural networks and parameterized quantum circuits, focusing on how quantum entanglement enables novel representational capacities and correlation structures beyond classical machine learning paradigms
Experience
Teaching Assistant in Advanced Applied Machine Learning at Johns Hopkins University
August 2025 - Present
Support graduate-level instruction in advanced machine learning techniques and applications
Assist students with complex ML implementations and research methodologies
Communications Lead at Glacier National Park Conservancy
July 2022 - Present
Develop and execute strategy to help scientists communicate their research to the public
Automate processes to scale communications while increasing personalization and relevance
Visual Information Specialist at Glacier National Park
April 2020 - June 2022
Produce and host Headwaters podcast, which hit #1 in the Nature category on Apple Podcasts
Design education wayside signs to exhibit along park roads
Naturalist Park Ranger at Glacier National Park
May 2017 - April 2020
Delivered more than 200 public educational programs, attended by over 8,500 park visitors
Publications
Bridging Quantum and Classical Computing in Drug Design: Architecture Principles for Improved Molecule Generation
July 2025
ICML 2025 - Generative Biology Workshop
Accepted
A Conversation on Fern Taxonomy with Susan Fawcett
June 2022
Kelseya: Newsletter for the Montana Native Plant Society
A discussion with Susan Fawcett, a PhD Research Botanist at the University and Jepson Herbaria at UC Berkeley, specializing in fern evolution, on her work with Thelypteridaceae and fern taxonomy
What Does the Future Hold for Glacier's Alpine Plants?
December 2021
Kelseya: Newsletter for the Montana Native Plant Society
In the lead article for the Winter 2021 edition of Kelseya, I examine new plant morphology data to hypothesize about the future of this ecosystem
Conference Presentations
Bridging Quantum and Classical Computing in Drug Design: Architecture Principles for Improved Molecule Generation
July 2025
ICML 2025 - Generative Biology Workshop | Vancouver, Canada
Presentation on hybrid quantum-classical machine learning architectures for drug discovery
Custom Dynamic Content with Data API Integration
February 2025
Public Lands Alliance Conference | Las Vegas, NV
Getting science to bigger audiences using cron, REST APIs, public resources to create a compelling, automated newsletter
Integrating RENXT with Automated Email Marketing
June 2024
bbdevdays
Demonstrating a custom JS Chrome extension to give fundraisers control over automated email constituents receive through an email platform API
Telling the Whitebark Pine Story: A Media Perspective
September 2022
Whitebark Pine Science and Management Conference | Dillon, MT
Panelist at a session on using the media to tell the story of the whitebark pine and connecting with the public with science
Podcasts: The Best Thing Your Park Isn't Doing
December 2021
National Association for Interpretation Conference | Palm Springs, CA
Telling the story of the Headwaters podcast and how it revolutionized our public outreach efforts and brought national park science and history beyond the park boundaries
Awards
Patrick Cummings Research Award
May 2025
Johns Hopkins University
The Patrick Cummings Research Award recognizes students for exceptional research in the field of biotechnology during their graduate studies. Given for my independent research, "Bridging Quantum and Classical Computing in Drug Design."
Intermountain Group Freeman Tilden Award
January 2022
National Park Service
The Freeman Tilden Awards are the highest interpretation awards presented to a National Park Service individual or team to recognize outstanding contributions to the profession of interpretation. Given for work on season 2 of the Headwaters podcast, covering the plight and recovery efforts for the whitebark pine, an ecologically important tree threatened with extinction.
Volunteer
Board Member, Montana Native Plant Society
2022 - Present
Serve on the Conservation Committee
Book speakers and facilitate conversations for the MNPS Presents speaker series
Lead educational plant walks for the public
Volunteer Judge at County Science Fair
2022 - Present
Give students feedback on their work and the scientific method
Citizen Botanist
2022 - Present
Document rare plant communities in technical mountainous terrain
Conduct post ESA-delisting monitoring for Howellia aquatilis