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Education
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2016-2024
Ph.D., Chemical Engineering
California Institute of Technology
Pasadena, CA- Thesis (Defended 6/20/24): Global Analysis of Protein Synthesis and Degradation in Escherichia coli
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2011-2016
B.S., Chemical Engineering
University of Florida
- Minor: Biomolecular Engineering
Experience
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2016-Present
Postdoctoral Scholar, Chemical Engineering
Ph.D. Candidate, Chemical EngineeringCalifornia Institute of Technology, Pasadena, CA
- Discovered global regulatory roles of protein degradation by combining chemoproteomic analysis, linear modeling, text mining, and machine learning to identify 186 novel protease substrate candidates in Escherichia coli.
- Developed a predictive machine learning model for in vivo protein stability in E. coli, achieving 87.5% accuracy in the experimental validation of 8 substrates.
- Engineered and deployed an open-source interactive application for filtering, normalization, differential expression analysis, and pathway enrichment analysis of mass spectrometry–based proteomics data. (repository) (publication)
- Identified DNA repair factors recruited to colibactin-induced DNA interstrand cross-links in Xenopus egg extracts via differential expression analysis and time-series clustering of chromatin mass spectrometry data. (preprint)
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2022
Bioinformatics Co-op
EMD Serono, Department of Translational Medicine and Global Clinical Development, Remote
- Developed Shiny application for visualizing cell type—specific transcript abundance, identifying differentially expressed genes, and conducting gene set enrichment analysis in clinical samples across autoimmune disease states.
- Established pipeline and Shiny application for the real-time analysis of text mining data from PubMed to identify genes, pathways, and diseases of therapeutic interest through information-theoretic and statistical approaches.
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2015
NSF REU Fellow
Harvard Medical School, Wellman Center for Photomedicine, Massachusetts General Hospital, Boston MA
- Investigated the effects of photocrosslinking on ex vivo tissue biomechanics via cyclic uniaxial tensile testing.
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2014
NSF REU Fellow
Johns Hopkins University School of Medicine, Department of Radiation Oncology, Baltimore, MD
- Evaluated the anti-tumor immune response generated by magnetic nanoparticle hyperthermia and ionizing radiation treatments in a mouse model for cancer.
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2012-2015
Undergraduate Research Assistant
University of Florida, Department of Chemistry, Gainesville, FL
- Developed an amphiphilic and pH-responsive copolymer for site-specific drug delivery in plants by functionalizing polysuccinimide with hydrophilic molecules.
Open Source Projects
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2022-Present
tidyproteomics-interactive
- A Shiny application for interactively working with tidyproteomics, an R package for processing protein- and peptide-level data and conducting statistical analysis.
Honors and Awards
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2018
- Center for Environmental Microbial Interactions (CEMI) Pilot Grant, California Institute of Technology
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2016
- CEMI Fellow, California Institute of Technology
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2016
- NSF Graduate Research Fellowship, California Institute of Technology
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2015
- Yao Su Student Research Prize, HST Summer Institute
- NSF REU Fellowship, Harvard-MIT Division of Health Sciences and Technology (HST)
- Collins Engineering Scholarship, University of Florida
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2014
- NSF REU Fellowship, Johns Hopkins University Institute for NanoBioTechnology (INBT)
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2013
- University Scholars Program, University of Florida
Skills and Coursework
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Bioinformatics and statistics
- Mass spectrometry-based proteomics analysis
- RNA-seq analysis
- Text mining
- Machine learning
- Cloud computing
- Shiny application development
- Linear modeling
- Regulatory network analysis
- Gene set enrichment
- Bayesian inference
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Programming languages
- Python
- R
- SQL
- Bash
- JavaScript
- CSS
- HTML
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Machine learning
- Scikit-learn
- PyTorch
- XGBoost
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Data analysis and visualization
- Pandas
- NumPy
- Matplotlib
- Seaborn
- Jupyter Notebook
- Shiny
- Bioconductor
- tidyverse
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Cloud and development tools
- Docker
- AWS
- Git
- Visual Studio Code
- RStudio
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Software suites
- GeneData Profiler
- Proteomics analysis suites (MaxQuant, Proteome Discoverer)
- Clarivate CBDD
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Relevant coursework
- CS/CNS/EE 155: Machine Learning & Data Mining
- CS/CNS/EE 156a: Learning Systems
- Bi/BE 103: Data Analysis in the Biological Sciences
- Bi/BE/CS 183: Introduction to Computational Biology and Bioinformatics
- ChE/BE 163: Biomolecular Engineering
- BE 150: Design Principles of Genetic Circuits
- APh 161: Physical Biology of the Cell