I’m a PhD candidate at The University of Texas at Austin, working at the intersection of machine learning, computational biology, and bioinformatics. My research blends code and biology to design predictive models for peptides, analyze complex datasets, and accelerate drug discovery. I build tools, uncover patterns in biological systems, and turn messy data into meaningful insights. With a foot in both the computational and life sciences worlds, I aim to push the boundaries of biotech, pharma, and fundamental research.
Skills
Programming & Data Analysis: Expert in Python, R, and Shell scripting with hands-on experience in HPC environments, virtual screening pipelines, and full-stack data science workflows.
Software & Tools: Power user of PyTorch, PyTorch Lightning, Pandas, NumPy, ggplot2, git, SLURM, LaTeX, and more — efficient across both research and production settings.
Research Methods: Applied machine learning and deep learning with a focus on transformers, statistical modeling, HMMs, and scalable bioinformatics pipelines. Strong emphasis on interpretability and impactful data visualization.
Languages: Fluent in English, conversational in Spanish — comfortable collaborating across linguistic and cultural lines.
Education
PhD in Biochemistry, The University of Texas at Austin (2022 – Present)
Graduate Certificate in Computational Life Sciences, Arizona State University (2020 – 2021)
Bachelor of Science in Biochemistry, Arizona State University (2019 – 2020)
Bachelor of Arts in English (Creative Writing), Arizona State University, Barrett Honors College (2009 – 2013)
Publications
Antibacterial Microcins are Ubiquitous and Functionally Diverse Across Bacterial Communities - Nature Communications (In Review)
Graduate Research Assistant, UT Austin (2022 – Present) - Conducting research on machine learning models for peptide encoding, natural antibiotic discovery, and bioinformatics applications.
Co-Founder, BioML Society, UT Austin (2023 – Present) - Organized industry and academic talks, led a protein engineering hackathon, and taught computational biology lectures.
Research Technician, Arizona State University (2020 – 2021) - Analyzed large protein sequence datasets and supported lab research in bacterial defense systems.
Guest Lectures & Posters
Guest Speaker: AI LIVE - UT Austin’s Year of AI Showcase, Fall 2024, Austin, TX. Topic: Interactive Workshop: AI & Eradicating Food Insecurity
Guest Lecture: UT Austin Graduate STEM Professional Development Course, Fall 2024, Austin, TX. Topic: Harnessing Language Models for Chemical Analysis and Therapeutic Discovery
Invited Speaker: UT Austin’s Core Facilities Conference, Summer 2024. Representing the Biomedical Research Computing Facility. Topic: Bioinformatics Approaches to Natural Peptide Antibiotic Discovery
Poster Presentation: Molecular Machine Learning Conference (MoML), Summer 2024, Quebec, Canada, hosted by Mila. Title: SMILES-based Modeling for Predicting Membrane Penetration of Cyclic Peptides
Invited Speaker: UT Austin’s Biophysics Hang-Out, Spring 2024. Topic: Development of Computational Methods for Discovery and Selection of Therapeutic Peptides
Guest Lecture: UT Austin Graduate Computational Biology Course, Spring 2024. Topic: Teaching Language Models to Speak Biology
Poster Presentation: Interdisciplinary Life Sciences Graduate Program Annual Retreat, Fall 2023. Title: Chemical Language Model for Identification of Novel Drug Analogues. Best Poster Award.
Certifications, Awards & Honors
Phi Kappa Phi Honor Society, 2023
Best Poster Award, UT ILS Retreat, 2023
CITI Program: Conflicts of Interest Certification
CITI Program: Biomedical Responsible Conduct of Research Certification
