A selection of projects spanning knowledge engineering, production ML systems, open-source tools, and applied research.
Current Focus: Knowledge Engineering & Semantic AI
Knowledge Graph & Ontology Systems @ FactSet
Designing and building enterprise-scale knowledge graphs and ontology-driven data architectures for financial data. This work involves defining taxonomies and semantic models that structure how entities, relationships, and concepts are represented across FactSet’s data ecosystem — enabling downstream applications from search to analytics to generative AI.
Graph Neural Networks for Entity Resolution
Applying GNN architectures to entity resolution and link prediction problems in large-scale financial knowledge graphs. Leveraging graph structure and node embeddings to disambiguate entities, surface implicit relationships, and improve data quality at scale.
Semantic Infrastructure & Knowledge MCPs
Building semantic middleware that connects knowledge graph infrastructure with LLM-powered workflows — enabling AI systems to reason over structured domain knowledge rather than relying on unstructured text retrieval alone. This includes ontology-aware retrieval, graph-enhanced RAG, and tooling that exposes structured knowledge to AI agents.
Production ML Systems
Data Solutions AI @ FactSet (2022-Present)
VP of Data Solutions AI at FactSet (S&P 500), leading teams building knowledge graphs, semantic AI systems, and ML infrastructure for financial data clients. Focus areas include entity resolution, ontology design, document understanding, and generative AI integration across FactSet’s product suite.
NLP for Defense @ SparkCognition Gov Systems (2020-2022)
Built production NLP and information retrieval pipelines for Air Force Research Labs. Enabled engineers to surface relevant technical documents at scale from massive unstructured corpora using advanced ML/NLP techniques.
Open Source & Research Tools
PsyCL Dataset
Psychological Characteristics of Leaders — a dataset of at-a-distance derived cognitive and personality values from analysis of over 54 million spoken words by political leaders. Published in Foreign Policy Analysis (2022).
sswebdata
Python package for importing open-access security studies web data (conflict events, state characteristics, social phenomena) into pandas DataFrames. Simplifies access to commonly used datasets in security and conflict research.
POS4764 - GIS for Political Analysis
Self-contained Jupyter notebook curriculum covering Python-based GIS analysis applied to terrorism, conflict, and voting behavior. Designed as a full semester course with progressive complexity.
Dissertation Research
Food, Familiarity, and Forecasting: Modeling Coups with Computational Methods
Applied ensemble ML methods and spatial/environmental features to forecast global coups d’etat. Combined food security indicators, climate data, and civil-military relations features to build predictive models that outperformed traditional approaches.
Applied Research
Fisheries Conflict Modeling
ML pipeline analyzing climate-fisheries-conflict linkages in East Africa and the South China Sea. Examining how environmental change drives resource competition and political instability. Published across Journal of Peace Research and Marine Policy.
Coastal Resilience & Disaster Readiness
NLP/ML research at UCF’s National Center for Integrated Coastal Research, surfacing information about community readiness at fine-grained spatial resolutions to natural disasters and climatic shocks.
Commons Synthesis Project
Applied NLP and ML to synthesize knowledge on community-based natural resource management from academic literature. Published in International Journal of the Commons.