👋 Hi, I’m Nolan — a dual Computer Science and Hispanic Linguistics major at UNC-Chapel Hill. My work lives at the intersection of language and logic: I'm passionate about building AI systems that don’t just generate fluent text, but reason with meaning. My current projects explore how structured knowledge representations and sociolinguistic insight can enhance large language models and make them more interpretable, semantically grounded, and truly intelligent.
- Institution: University of North Carolina at Chapel Hill
- Program: Honors Carolina | B.S. in Computer Science & Hispanic Linguistics
- Current Research:
- Emotion-Driven Code-Switching in Sentiment Analysis (Honors Thesis): Investigating how sociolinguistic and pragmatic factors affect code-switching behavior and how this information can improve sentiment detection in bilingual NLP systems.
- Structured Reasoning for LLMs: Developing hybrid systems that integrate knowledge graphs (Wikidata, Neo4j) and symbolic inference layers with probabilistic language models — aiming to bridge surface form and deep structure in AI understanding.
- Languages:
- AI & NLP: LLMs/SLMs, symbolic reasoning, sentiment analysis, code-switching, model fine-tuning,
, PyTorch, TensorFlow
- Knowledge Representation: Ontology engineering (Wikidata, Neo4j), triplestore databases, higher-order logic (HOL), semantic parsing
- Systems & Infrastructure: Linux, Singularity,
, HPC workflows (Slurm),
(Lambda, EC2, S3), CI/CD (GitHub Actions, GitLab CI)
- Frameworks & Tools:
,
,
, Material UI, Redis,
,
, WebSockets
- Data Engineering:
,
, robust pipeline development, reproducibility, and QA automation for large-scale datasets
Research Programmer
Neural Dynamics of Control Laboratory (FIU) | Remote
Under the supervision of Dr. George Buzzell
- Designed and deployed a scalable data validation system for neuroscience research (hallMonitor 2.0)
- Ensured reproducibility and integrity in HPC workflows (>13TB EEG datasets)
- Built quality assurance layers to enforce data integrity and adherence to lab schema standards
💡 Check out our lab code on GitHub!
I’m passionate about rethinking how AI systems interact with knowledge — decoupling language from logic, then deliberately reconnecting them through structured symbolic reasoning and semantically-aware architectures. Whether through code, ontology, or linguistic analysis, I love designing systems that make machine reasoning more transparent and aligned with human meaning.
I'm always open to collaboration, research ideas, or just thoughtful conversations about language and intelligence.
📬 [email protected] | 💼 LinkedIn