CV
A full PDF version is available above. Highlights below.
Education
- PhD, Physical Chemistry — Colorado State University, 2021–2026 (expected) Advisor: Dr. Seonah Kim. Focus: machine learning for molecular property prediction, graph neural networks, and quantum chemistry.
- BA, Chemistry and Mathematics — University of Colorado Boulder, 2017–2019
Research Experience
Graduate Researcher, Computational Chemistry & Machine Learning — Colorado State University, Dr. Seonah Kim Group · Aug 2021–present
- Designed graph transformer and message-passing architectures for property prediction across atom-, bond-, and molecule-level targets (bond dissociation energies, solubilities, singlet–triplet gaps), achieving state-of-the-art performance on benchmark datasets.
- Developed a protein solubility predictor combining geometric deep learning with persistent homology and topological data analysis to capture global structure missed by conventional GNNs.
- Built a GPU-based exhaustive conformer generator outperforming xTB and CREST by two orders of magnitude on macrocyclic peptides.
- Built production-scale ML pipelines processing millions of DFT/quantum-mechanics simulations with strict provenance and reproducibility guarantees (AiiDA, FireWorks, SLURM).
Research Intern, Computational Chemistry — GlaxoSmithKline, Upper Providence, PA · Summer 2024
- Developed a heterograph link-prediction model on multi-modal biological data for drug–target interaction prediction, with physics-based uncertainty quantification of binding affinities.
- Built a high-performance nearest-neighbors package to quantify grid-based electronic-structure interactions in DNA intercalation, enabling drug–DNA binding analysis at scale.
Software Consultant — Big Compass, Boulder, CO · 2019–2020
- Built a full-stack identity and access management solution for a Fortune 500 client and migrated on-premise databases and ETL pipelines to AWS.
Teaching & Mentoring
- Mentored undergraduate REU researchers (2022, 2025) and junior graduate students.
- Teaching Assistant — General Chemistry Labs (CHEM112, CHEM114), Colorado State University, 2021–2022.
- Teaching Assistant — General Chemistry with Lab, Pomona College, 2014–2015.
Selected Honors & Awards
- C. Michael Elliott Fellowship, Colorado State University, 2024–2025
- Travel Fellowship, Quantum Winter School: Quantum Simulation, IPAM, UCLA, 2026
- Graduate Student Outreach Award, Colorado State University, 2024–2025
- Sustainability Leadership Fellow, CSU School of Global Environmental Sustainability, 2023–2024
- Gary E. Maciel Fund Fellowship, Colorado State University, 2021–2023
- Graduate Teaching Assistant Award, Department of Chemistry, CSU, 2022
- ACS Award for Undergraduate Excellence in Analytical Chemistry, 2019
Service & Professional Activities
- Organizer & Curriculum Developer, Computation Boot Camp, NSF Center for Sustainable Photoredox Catalysis, 2025
- Co-President, Chemistry Graduate Student Organization, Colorado State University, 2023–2024
- Graduate Student Representative, Climate & Culture Working Group, CSU Chemistry, 2024–2025
- Organizer & Lecturer, Linear Algebra for Computational Chemistry and Data Science, CSU, 2024
- Guest Lecturer, CHEM571A Quantum Chemistry, CSU, 2023
Technical Skills
- Machine Learning: Graph neural networks, graph transformers, geometric & equivariant deep learning (E(3)NN), message passing, foundation models, transfer learning, uncertainty quantification, model interpretability.
- Computational Chemistry: Quantum mechanics (DFT), molecular property prediction, drug discovery, molecular dynamics (OpenMM, Amber), cheminformatics (RDKit, Mordred).
- Programming & Frameworks: Python, PyTorch, PyTorch Lightning, PyTorch Geometric, DGL, TensorFlow, E3NN, Ray, NumPy/SciPy/Pandas, Julia, Bash, SQL.
- Data & Infrastructure: AWS, Docker, Singularity, HPC/SLURM, multi-GPU & distributed training, PostgreSQL, MongoDB, AiiDA, FireWorks, Terraform, ETL pipelines.