Experience

OneThree Biotech

• United States
• Biotechnology Research
• 1 - 100 Employee

• Computational Biologist, ML Engineer

  • Oct 2022 - Present

  At OneThree, I spearheaded the enhancement of the MLOps pipeline, automating k-fold cross-validation, hyperparameter tuning and NeptuneAI logging to the AI API. I also developed a Bayesian algorithm to detect genetic co-dysregulation in cancer cells. At OneThree, I spearheaded the enhancement of the MLOps pipeline, automating k-fold cross-validation, hyperparameter tuning and NeptuneAI logging to the AI API. I also developed a Bayesian algorithm to detect genetic co-dysregulation in cancer cells.


Princeton University
• United States
• Higher Education
• 700 & Above Employee
• PhD Candidate, Researcher

  • Sep 2016 - Present


Princeton University - Center for Statistics and and Machine Learning

• TA - Introduction to Data Science

  • Jan 2021 - May 2021

  Teaching Assistant for the SML 201, the introductory course in data science. Students with little to no coding experience learned how to manipulate and visualize data in R, implement hypothesis tests, run linear regression, and work with the normal, t, and F distributions. It is my passion to teach students statistics and programming in an approachable manner. When teaching students, my goal was to have the students understand the intuition and graphical visualizations behind statistical concepts. This gives students a deeper (and longer-lasting) understanding of concepts than simply memorizing the formulas and technical aspects of the course. https://csml.princeton.edu/undergraduate/sml-201-introduction-data-science Show less



AI4ALL @ Princeton

• Research Instructor

  • Jul 2019 - Jul 2020

  AI4All seeks to foster diversity in the CS community by training early-career students on various concepts in machine learning. For two summers, I designed and led a research module from scratch, teaching students to implement 23andMe-like machine learning algorithms (Random Forests, KNN, SVC, Logistic Regression, Multinomial-Dirichlet Naïve Bayes) to classify genomic and medical data. We challenged students to consider the underlying algorithms, their performance, and biases in the data. I also lead two lectures on multinomial classification and statistics for the ~30 students in the camp. It's my personal belief that any concept can be taught to any audience with enough time and creativity (the proper rhetoric). https://ai4all.princeton.edu/ Show less



Research Computing - PICSciE at Princeton University

• University Administrative Fellow

  • Sep 2019 - May 2020

  Intern for the Princeton Institute for Computational Science and Engineering (PICSciE) Staff of Princeton Research Computing. This department provides computational training to researchers of all levels (graduate students, senior researchers, professors), offering courses like Intro to Cloud Computing and HPC clusters, hosting consulting sessions for researchers with technical questions, and building websites/databases for research projects. My project as a Fellow was to contact department chairs and students across the university to understand better the needs of researchers that PICSciE could fulfill. Show less



F.J. Arsuaga Topological Molecular Biology Lab

• Junior Specialist (Researcher)

  • Jan 2015 - Sep 2016

  Research under Professor Arsuaga, Dept. of Mathematics, Dept. of Molecular and Cellular Biology. Here, I explored statistical approaches for modeling Hi-C data, evaluating the spatial relationships among chromosome clusters in breast cancer. The three-dimensional architecture of the genome plays a pivotal role in regulating gene transcription and repair. Within the context of cancer, the spatial conformation of genomes is altered, leading to pathway-level changes that ultimately manifest as tumorigenic phenotypes. As a part of this fully computational lab, I worked alongside molecular biologists, mathematicians, and software engineers. Show less



Professor S. Atsumi Metabolic Engineering Lab

• Research Assistant

  • Oct 2013 - Sep 2014

  Research under Professor Shota Atsumi, Professor in the Dept. of ChemistryCloning of E. coli and yeast to inhibit the expression of gluconate transporter protein for biofuel production. While ethanol is naturally produced by many microorganisms through a simple cellular pathway, butanediol possesses chemical properties that closely resemble those of gasoline commonly used in our day-to-day lives. In this project, our focus was on engineering E. coli to synthesize this combustible molecule by cloning key enzymes into the cellular circuitry and repressing alternative metabolic pathways that use the same metabolites. Show less