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Doctor of Philosophy, Biomedical Engineering

University of Virginia, Charlottesville, VA

• Title: Explainable Deep Generative Models, Ancestral Fragments, and Murky Regions of the Protein Structure Universe: Datasets, Models, and Analyses of Fold Space
• Advisors: Philip E. Bourne and Cameron Mura
• Chair: Kristen M. Naegle
• Committee: Jason A. Papin, Aidong Zhang an Stephen Baek

Bachelors of Science, Bioinformatics

University of California, Santa Cruz

• Thesis: Correcting Frameshift Mutations in Transcriptomics Data
• Advisors: Mark Blaxter (Edinburgh), Dietlind Gerloff

Postdoctoral Scholar

University of California, San Francisco

• Bayesian Meta-modeling with deep generative models
• Protein-protein interactions and whole cell modeling
• Explainable AI for protein evolution

PhD Candidate

University of Virginia, Charlottesville, VA

• Developed Prop3D, a python framework to compute atomic, residue and graph level physicochemcal properties for all CATH domains in the cloud and shared using HSDS
• Developed DeepUrfold and DeepUrfold-explain, explainable deep generative models to explore remote relationships between CATH superfamilies at the Urfold level (e.g. discontinous peptide fragments)

Machine Learning Intern

VantAI, New York, NY

Predoctoral Fellow

National Institutes of Health, Bethesda, MD

• Worked with Phil Bourne & Michael Grigg (NIAID)
• Knocked out T. gondii surface proteins with CRISPR/Cas9 to understand function, evolution

Graduate Student Intern

Harvard Medical School, Boston, MA

• Helped develop a python framework for coevolutionary sequence analysis
• Added coevolutionary restraints into Phenix to improve low-resolution X-ray structures

Postbac Fellow

National Center for Biotechnology Information, Bethesda, MD

• Worked under Alexey Shaytan in Anna Panchenko's group
• Wrote HistoneDB 2.0 Django webserver to classify histone sequences by variant with HMMs

Student Assistant

Lawrence Berkeley National Labs, Berkeley, CA

• Worked under Nigel Moriarty in Paul Adam's Lab
• Validated and modelled glycoproteins by ligand fitting and built 2D carbohydrate builder

Undergraduate Researcher

The University of Edinburgh, Edinburgh, UK

• Worked under Martin Jones in Mark Blaxter's Lab for UCSC Senior Thesis
• Wrote HSP-Tiler to fix frameshift mutations in RNAseq data using python, BLAST, HMMs

Amgen Scholar

Washington University in St. Louis, St. Louis, MO

• Worked under Garland Marshall
• Wrote python script to add subsituents to drugs and screened with OpenEye docking

Undergraduate Researcher

University of California, Santa Cruz

• Worked under Dietlind Gerloff
• Predicted structures of Malarial surface proteins with MODELLER and HMMER
• Created a public webserver to share structures

Deep Generative Models of Protein Domain Structures Uncover Distant Relationships- Evidence for an Urfold

NeurIPS-LMRL, Virtual

• Zenodo

Deep Learning of Protein Structural Classes- Any Evidence for an Urfold?

ISMB-3DSig, Virtual

• Zenodo

Determining the functions of the Apicomplexan SRS/6-Cys protein family- A Structural and Evolutionary Understanding of Pathogen Invasion

ISMB-ISCB Student Council Symposium, Prague, CZ

• Zenodo

Classification of Histone Variants

ICSB RSG-DC Student Research Symposium, College Park, MD

Large-scale Biological Data Engineering with HDF5 + the Highly Scalable Data Service

Using HDF5 and HSDS for Open Science Research at Scale Workshop, University of Notre Dame, South Bend, IA (Virtual)

• Zenodo

Deep Generative Models of Protein Domain Structures Can Uncover Distant Relationships- Evidence for an Urfold

GBMES Student Summer Seminar Series, University of Virginia, Charlottesville, VA

Protein Interaction Prediction Using Deep Learning and Protein Structural Data

Systems Biology Journal Club, Dept. of Biomedical Engineering, University of Virginia, Charlottesville, VA

Deep Learning Approaches to Predict Protein-Protein Interactions

ISMB-ISCB Student Council Symposium, Chicago, IL

Deep Learning Approaches to Predict Protein-Protein Binding Sites

Computational Biology Branch Seminar, NCBI/NLM, National Institutes of Health, Bethesda, MD

Determining the Function of the Apicomplexan SRS/6-Cys Protein Family- A Structural and Evolutionary Understanding of Pathogen Invasion

Laboratory of Parasitic Diseases Division Seminar, NIAID, National Institutes of Health, Bethesda, MD