Curriculum Vitae

Thomas Roderick, PhD

tom@flamelit.tech · Canton, GA

Expertise

  • Architecting and implementing scalable, technical AI solutions
  • Strategic analysis and consultation to articulate, roadmap, and achieve data-driven solutions to complex business problems
  • Enhancing or expanding technical capability through targeted, data-driven methods

Professional Experience

Flamelit Consulting, LLC 2021–present
Chief AI/Technology Officer -- Data Science Consultancy

Client industries

  • US Government IT (civilian agencies) -- Lead data scientist/AI architect. Awards: 2021 USCIS Directors Pinnacle Award, 2022 USCIS Associate Directors Management Directorate Award for Exemplary Teamwork, Department Kudos Award (×10)
  • Technology: Software engineering, digital services, industrial IoT
  • Manufacturing and utilities (water, electric)
  • Technology: AI strategy prototyping, consulting, design, and implementation (LLM, predictive modeling, classification, clustering/segmentation)
  • Healthcare IT, AI product
  • Fractional Chief AI Officer engagements (×3)

Major projects

  • Generative AI development and deployment -- document review, data extraction, artifact chat, fraud detection, report generation, GenAI-enhanced data processing
  • Predictive AI / GoFAI -- operational/process AI implementation, risk assessment, micro-segmentation & classification, GIS localization & analytics
  • AI governance -- NIST AI working group participant, defined operational policies and monitoring following SR 11-7 and other AI/ML governance frameworks
College of William & Mary, Raymond A. Mason School of Business 2025–present
Affiliate Faculty
PCCI (Parkland Center for Clinical Innovation) 2019–present
Executive-in-Residence, Data & Applied Science -- Healthcare Non-profit R&D

Major projects

  • Maternal Health Event Surveillance System index model development & implementation
  • Automated discovery algorithms targeting ALS progression stratification by genomic, supplement, and pharmaceutical interactions
  • Community surveillance public health systems for pediatric asthma, diabetes, and hypertension using multi-source data ingestion, AI/ML, ETL, GIS, and dashboarding
  • AI model for potential sepsis detection among non-trauma ER admissions using AutoML, classification, and feature engineering
  • Automated patient segmentation using topological data analysis (embedding), clustering, and classification -- used across major health systems and insurance providers
  • COVID-19 response and capacity modeling using epidemiological models, GIS production, data scraping, and dashboarding; used by major area hospitals and Dallas County public health
  • Strategic analytics product for Managed Care Organizations (Medicaid payers), based on administrative claims and geospatial analysis
  • Emerging risks stratification modeling for geographical and community vulnerability to COVID-19; drove local public health testing site strategy
  • Data warehouse & ETL design for ML operations infrastructure serving 170k+ Medicaid patients
  • Technical developer and judge for internal DS+Tech hackathons (×5)
Riis Technology, LLC 2021
Chief Data Scientist -- Data Science Product R&D
  • Key personnel/PI on SBIR/STTR tech transfer projects (FA864921P1357, FA864921P0621, FA864922P0067, FA864921P1340)
  • Data strategy consulting; grew revenue by 600%
Triquetra Data Services, LLC 2019–2021
Managing Principal
  • Multi-source data pipeline for leading recruiting firm
  • Classification product for construction/CAD specification ontology
  • IoT-derived data solution for manufacturing facility energy management
  • Fractional chief data science advisory for business development and project design
JP Morgan Chase & Co. 2014–2019
Lead Data Scientist -- Retail Finance
  • Lead data scientist for Chase-for-Business strategy & finance (acquisition, retention, deepening for 4M clients across three lines of business); guided a team of 4 data scientists and 25 analysts/data engineers
  • Senior forecast developer and process owner for mortgage sales funnel (branch + digital) covering prospecting, capacity/operations, sales, and finance
  • Primary statistical market forecast modeler for $85B time deposit portfolio (supporting $600B retail deposit book) used for internal forecasting, budgeting, and Federal Reserve scenarios
  • Keynote/inaugural data science speaker at internal symposia and quantitative community launches (Ohio and Texas)
The University of Texas at Austin 2009–2014
Graduate Research & Teaching Assistant
TAC Americas 2008–2009
Engineer/Analyst -- Energy Industry
BYU IDeALabs 2006–2007
Research Associate

Publications & Presentations

Publications & Patents

  • Roderick, T., Tremblay, M., Kohli, R., Castellanos, A. (2026). TerrainGrade: An Artifact for Flood Susceptibility Mapping. [Working paper submitted to DESRIST 2026].
  • Roderick, T., Tremblay, M., Kohli, R., Castellanos, A., Pengetnze, Y. (2025). When Vulnerability Drives Action: Designing Forward Looking Frameworks for Disaster Preparedness. [Forthcoming, Information Systems Research].
  • Tremblay, M., Castellanos, A., Kohli, R., Espinosa, E., Roderick, T. (2025). Integrating Mental Health and Juvenile Justice Outcomes: A Case Study of Model-Agnostic Interpretable Machine Learning. [Forthcoming, INFORMS Journal on Computing].
  • Pengetnze, Y., Oaks, T., Tamer, Y., Roderick, T., Allen, J., Lignon, H., Rather, L., Termulo, C., Huang, P., & Miff, S. (2024). Pediatric Asthma Surveillance System (PASS): Community-Facing Disease Monitoring for Health Equity. NEJM Catalyst Innovations in Care Delivery, 5(8).
  • Tamer, Y., Karam, A., Roderick, T., & Miff, S. (2022). Know-Thy-Patient: A Novel Approach and Method for Patient Segmentation/Clustering Using ML. NEJM Catalyst Innovations in Care Delivery, 3(4).
  • Barker, P., Hartley, D., Beck, A. F., Oliver, G. H., Sampath, B., Roderick, T., & Miff, S. (2021). Rethinking Herd Immunity: Managing the Covid-19 Pandemic in a Dynamic Biological and Behavioral Environment. NEJM Catalyst Innovations in Care Delivery, 2(5).
  • Roderick, T., Pengetnze, Y., Miff, S., Tremblay, M., & Kohli, R. (2021). Building a Vulnerability Index of Biological and Socioeconomic Risk Factors to Combat COVID-19 Spread. The Next Wave of Sociotechnical Design, 22.
  • Oliver, G. R., Miff, S., Roderick, T., Parkland Center for Clinical Innovation. (2023). System and Method for More Accurate Estimation of Vaccine Efficacy by Taking Into Account the Rate of Herd Immunity. U.S. Patent Application 17/939,921.
  • Arora, A., Sundaram, V., Zimmerman, L., Roderick, T., et al., Parkland Center for Clinical Innovation. (2021). Community Vulnerability Index Dashboard. U.S. Patent Application 17/191,648.

Selected Presentations

  • USCIS BIMS 2026 -- AI Governance in Practice
  • USCIS BIMS 2025 -- Data Management and Development
  • USCIS BIMS 2024 -- GenAI: What Comes Next
  • USCIS BIMS 2023 -- Practical Applications of Emerging AI Technology for Technologists
  • USCIS BDSO 2022 -- Business Product Owner's Guide to Data Science
  • USCIS AI/ML Consortium 2021 -- Operational, Locational Improvements for COVID-19 Closure Recovery
  • UT San Antonio Workshop for ISR SI: Unleashing the Power of IT for Strategic Management of Disasters (2021)
  • Design Science Research in Information Systems and Technology, DESRIST 2021
  • Institute for Healthcare Improvement: COVID-19 Vulnerability Index (2020)
  • SafeGraph Data Consortium: COVID-19 Vulnerability Index (2020)
  • UT Dallas PostDoc Society: Transitioning from PhD to Industry as a Data Scientist (2020)
  • JPMorgan Chase Data Science Symposium: Building a Performant Cross-Business Data Science System (2017)
  • Lawrence Berkeley National Laboratory: Optimal Electric Transmission Pricing (2014)
  • Parkland Center for Clinical Innovation: Coding for Data Science Careers (2021–2024)

Education

PhD
Economics -- The University of Texas at Austin 2009–2014 · Dissertation: Essays on Regulatory Impact in Electricity and Internet Markets
MS
Economics -- The University of Texas at Austin 2009–2011
BS
Mathematics & Economics -- Brigham Young University, Provo 2001–2007

Skills

AI & Software AI-assisted coding, LLM integration & hosting, AI governance, AI Ops, model benchmarking
Data Science Segmentation/clustering, forecasting, model validation, predictive modeling, feature engineering, PCA, optimization, cross-validation, classification, AWS (Redshift, Lambda, boto3, SageMaker), GenAI (OpenAI, Claude, Llama)
Business Database/digital marketing, finance (P&A, P&L, forecasting), strategy, CRM (Odoo, HubSpot), project management
Economics Econometrics, computational economics, industrial organization, price elasticity, regulatory impact, game theory
Programming Python, SAS (Base Certified), SQL (MySQL, Teradata, Oracle, Hive, SQL Server, Databricks/Spark), PySpark, Matlab, bash, Tableau, QGIS, LaTeX, Java

Certifications

  • Multi AI Agent Systems CrewAI · Feb 2025 Credential
  • AWS Cloud Practitioner Amazon Web Services · Sep 2022–Sep 2028 Credential
  • Causal Inference Coursera · Aug 2019 Credential
  • Machine Learning Researcher DataCamp · Aug 2019
  • Analytics Solution Delivery DataCamp · Apr 2019
  • Data Analyst / Data Scientist DataCamp · Apr 2019
  • Certified Base Programmer (SAS 9) SAS · Dec 2015 Credential