Dr. Daniel Wooten
Computational scientist — production machine learning and nuclear reactor simulation
Skills
Programming Languages: Python 3 (10+ years), C/C++/C# (5+ years), Fortran, Java (2+ years), MATLAB, R
Tools: Pandas, Numpy, RegEx, Scikit-learn, Matplotlib, PyTorch, TensorFlow, CUDA, MPI, OpenMP, Git
Reactor physics & simulation: SERPENT 2 (code-modification level), Monte Carlo neutron transport, depletion and fuel cycle analysis, multigroup neutron diffusion, reactor kinetics, RELAP5, constrained and linear optimization
Communication: Public speaking and technical writing; comfortable explaining a model to the people who have to sign off on it.
Experience
Principal Data Scientist: Gen-AI - Capital One Bank - Dec 2024 to Present
- Built Project OWL, an LLM system for automated analysis of customer call transcripts, deployed at scale and valued at $30 million annually
- Designed and deployed an LLM-scale sequential regression model over tabular customer data for credit risk evaluation, increasing accuracy by 4.5% for NPV over $90 million
- Built LLM-Judge, an evaluation harness for automated validation of stochastic model outputs, worth $300k annually — verification and validation of non-deterministic systems in a domain where every decision is auditable to a regulator
- Patent-pending on a novel technique for boosting gradient-boosted machine ensembles with deep sequential model outputs, with first results worth $7.5 million annually
Principal Data Scientist: Anti-Money Laundering - Capital One Bank - Jan 2023 to Dec 2024
- Designed and deployed an LLM-scale sequential model over tabular transaction data for risk-leveling, increasing AUROC by 14% worth more than $1.2 million annually
- Reduced alert volume by more than 15% while increasing risk coverage 11% through new engineered features, cutting investigation cost $800k annually — a precision/recall tradeoff bounded by a regulatory floor
AI/ML Software Engineer - Perceptronics Solutions - Aug 2020 to Jan 2023
- Designed and built Auto-Encoder model for AI-generated-radar detection and classification resulting in 3-year contract renewal
- Created a Bayesian filter based planning tool for coordinating multiple independent actors resulting in 3-year contract renewal
Nuclear & Computational Physics Experience
Full detail on the nuclear work page and the ADER project page.
Graduate Researcher: Reactor Physics & Fuel Cycle Methods - UC Berkeley - Aug 2013 to Dec 2019
- Architected ADER, a ~30,000 line C extension to the SERPENT 2 Monte Carlo reactor physics code, creating a first-of-its-kind fuel cycle depletion capability for circulating, liquid-fueled reactors
- Designed a chemistry-aware linear optimization engine operating on the depletion state, solving fuel composition against physical and chemical constraints rather than assuming it
- Built to production standard: ~15,000 lines of unit and integration tests in C and Python, complete user manual and API documentation, fully version-controlled
- Established applicability ranges for point-reactor kinetics in circulating-fuel systems via time-resolved multigroup neutron diffusion
- Graduate Student Instructor, NE150 Neutron Diffusion Theory
Reactor Physics Intern: Reactor & Nuclear Systems Division - Oak Ridge National Laboratory - Summer 2016
- Evaluated and documented computational modeling options for kinetic response simulation in circulating-fuel reactors; the resulting survey became a peer-reviewed review paper co-authored with ORNL's Jeffrey J. Powers
Reactor Safety Intern: Sodium Fast Reactor - TerraPower LLC - Summer 2015
- Developed an automated Python RELAP5 input generator for the reactor safety team, removing hand-construction of thermal-hydraulic input decks
Reactor Analysis Intern - Tennessee Valley Authority - Summer 2012
- Designed and developed a BWR control blade history monitoring and assessment library, with data scrapers running against live reactor operational data
Education
UC Berkeley - Dec '19
Ph.D. in Nuclear Engineering: Designated Emphasis in Computational and Data Science Engineering
UC Berkeley - May '17
M.S. in Nuclear Engineering
North Carolina State University - May '13
B.S. in Nuclear Engineering, summa cum laude
Publications & Presentations
- Wooten, D., Fratoni, M. “Linear optimization for predicting material compositions in molten salt reactors.” Annals of Nuclear Energy, 2020.
- Wooten, D., Powers, J.J. “A Review of Molten Salt Reactor Kinetics Models.” Nuclear Science and Engineering, 191(3), 2018.
- Wooten, D.D., Fratoni, M. “ADER: Advanced Depletion Extension for Reprocessing — A SERPENT 2 Mod.” 2nd Annual Molten Salt Reactor Workshop, Oak Ridge, TN, 2016.
- Wooten, D.D., Fratoni, M. “Enhanced Fidelity Depletion for Molten Salt Reactors.” PHYSOR 2016, Sun Valley, ID.
- Wooten, D.D., Fratoni, M. “Advanced Depletion Extension for Reprocessing (ADER) for SERPENT 2.” 5th International Serpent User Group Meeting, Knoxville, TN, 2015.
- Byrns, B., et al. “A VHF Driven Coaxial Atmospheric Air Plasma: electrical and optical characterization.” Journal of Physics D: Applied Physics, 45(19), 2012.
Fellowships & Honors
NSSC Fellow, Nuclear Science and Security Consortium (2019)
U.S. Nuclear Regulatory Commission Fellow (2017–2019)
Berkeley Graduate Fellow (2016–2017)
NEUP Fellow, DOE Nuclear Energy University Program (2013–2016)
American Nuclear Society Scholarship (2010–2015)