01. The Business Challenge
At a massive research institution like the University of Illinois, tracking and mapping faculty research is an operational hurdle. With hundreds of distinct majors and thousands of researchers, information was fundamentally siloed.
The Ambiguity of Interdisciplinary Data
While research is increasingly interdisciplinary, the university lacked a unified system capable of interpreting cross-functional interests. Faculty profiles consisted of unstructured, free-form text, making programmatic indexing or cross-departmental collaboration nearly impossible.
LangGraph
Stateful, cyclic workflow
Pydantic
Strict taxonomy validation
Gemini Flash
Optimized API resource usage
02. Pipeline Architecture
To solve this, I engineered an automated, agentic pipeline that accepts natural language inputs and guarantees validated, standardized research classifications.
Description Cleaner
Normalizes raw, unstructured faculty text inputs before passing them into the classification chain.
Tiered Classification
Moves sequentially through a High-Level Field Classifier into a granular Subfield Classifier, triggering a Subfield Proposer for edge cases.
Strict Validation
Output must pass rigorous Pydantic validation to ensure exact alignment with official university taxonomy.
03. Strategic Trade-Offs
Framework: LangGraph vs. Langchain
Opted for LangGraph over standard linear Langchain. This allowed us to build the stateful, cyclic graphs required to implement strict validation gates and iterative workflow loops.
Model Selection: Gemini Flash
Strategically deployed the Gemini Flash model to mitigate the risk of hitting rate limits associated with Pro tiers, effectively balancing computational performance with resource constraints.
Human-in-the-Loop Integration
Designed a "Taxonomy Curator" function to allow for human review of edge-case proposed additions. This managed stakeholder expectations by retaining academic oversight while ensuring long-term systemic accuracy.
04. Outcome & Impact
Institutional Standardization
Provided university administration with a structured methodology to organize faculty research, replacing inconsistent departmental terminology with a shared, scalable classification language.
Cross-Departmental Connectivity
Enabled the university to accurately map individual research profiles, successfully breaking down information silos to facilitate interdisciplinary connections across the campus ecosystem.