Engineering, Research & Operations.
Chronological overview of my work in electric-vehicle battery manufacturing, data engineering, computational drug discovery, and materials research, alongside my current role in Business Operations & Strategy at our family-owned enterprise.
Roles & Key Contributions
2020 – PresentBusiness Operations & Strategy
Operations · Strategic Planning · AgricultureSupporting day-to-day business operations, partner coordination, and strategic initiatives at my family's agricultural enterprise.
- Operations & Coordination: Assist with operational management, commercial coordination, and strategic planning across my family's agricultural business.
- Field Trial Evaluation: Support field demonstration plot trials to evaluate organic fertilizer strategies and track crop productivity.
- Data & Reporting Exploration: Explore practical approaches for baseline soil and satellite analysis as well as clear reporting for business and institutional partners.
Methods & Tools: Business Operations · Strategic Planning · Field Trial Analysis · Python & SQL
Sr. Data Engineer (P3) & Data Engineer (P2)
EV Battery Manufacturing · 4680 Cell & Factory TelemetryBuilt battery formation screening libraries (FAST), real-time multi-gigafactory telemetry dashboards (RAPID), Generation 4/5 battery simulation models, and 4680 cell API recipe synchronization workflows.
- FAST Screening Library (P3): Developed the FAST (Formation Analytics Screening Toolbox) library used by data scientists to evaluate new development recipes during battery formation and reach deterministic pass/fail trial conclusions.
- RAPID Live Factory Dashboard (P3): Developed and maintained the RAPID internal dashboard for Berlin and Austin Gigafactory sites, enabling process engineers to inspect real-time telemetry and make live production-line adjustments.
- EoL Defect Detection & Vendor Scoring (P3): Developed automated early defect detection during End of Line (EoL) testing and established vendor scoring parameters for business analytics teams.
- Milmont AWS Streams, Gen 4/5 ML Models & 4680 API Sync (P2): Implemented temperature, pH, and electrical current data streams for the Milmont facility into AWS; developed proprietary Generation 4 & 5 ML models simulating Model Y and Model 3 batteries across vendors; and engineered API call-and-sync recipe systems supporting 4680 battery cell development.
Methods & Tools: Python · SQL · AWS · FAST Toolbox · RAPID Dashboard · Gen 4/5 ML Simulation · REST APIs
Data Science Intern
Computational Drug Discovery · Molecular Machine LearningCurated drug discovery datasets and trained transfer-learning and active-learning models in Python to screen molecular candidates for wet-lab testing.
- Molecular Property Prediction: Used Python to curate drug discovery datasets and build machine learning models to predict molecular properties.
- Transfer & Active Learning: Applied transfer learning and active learning techniques to make effective use of sparse chemical datasets.
- Wet-Lab Candidate Screening: Screened large databases of molecules to identify promising candidates to advance into wet-lab testing.
Methods & Tools: Python · TensorFlow · Keras · NumPy · Pandas · Transfer Learning · Active Learning
Process Development Engineer, Formation
EV Battery Cell Formation · SEI DiagnosticsDeveloped proprietary battery cell formation recipes for R1S, R2, and R3 vehicle programs and predictive Solid Electrolyte Interphase (SEI) anomaly detection protocols.
- R1S, R2 & R3 Formation Recipes: Developed proprietary formation recipes for R1S, R2, and R3 models with improved charging compatibility on Tesla’s Supercharger network.
- Predictive SEI Anomaly Detection: Developed diagnostic protocols to detect Solid Electrolyte Interphase (SEI) formation anomalies during precharge steps.
- Production & Development Recipe Standardization: Deployed 6 recipes (4 development recipes and 2 production recipes) that served as the standard baseline from December 2021 to December 2022.
Methods & Tools: Battery Cell Formation · SEI Precharge Diagnostics · Electrochemical Testing · Python / MATLAB
Research Assistant — Battery Engineering
Electrochemical Energy Storage & Materials CharacterizationConducted coin-cell assembly, cathode active material synthesis, materials characterization (XRD, FTIR, NMR), and battery cell recycling research.
- Coin-Cell Assembly & Cycling: Assembled coin cells in argon glove boxes and ran electrochemical testing on automated battery cyclers.
- Cathode Synthesis & Characterization: Synthesized cathode active materials and performed physical characterization using XRD, FTIR, NMR, vacuum ovens, and ROTAP shakers.
- Direct Recycling Teardown: Harvested and tore down spent cells (cathode, separator, and electrolytes) for battery recycling studies and authored experiment reports.
Methods & Tools: Coin Cell Assembly · Battery Cyclers · XRD · FTIR · NMR · Glove Box Operations · ROTAP Shaker
Education
More on My Background →| Graduation | University | Degree & Concentration |
|---|---|---|
| June 2023 | University of California, Berkeley Berkeley, CA | Master of Engineering (M.Eng.) in Materials Science and Engineering Concentration in Data Science · Major GPA: 3.92 |
| June 2021 | University of California, San Diego San Diego, CA | Bachelor of Science (B.S.) in Chemical Engineering Minor in Computer Science |