Research

Three active faculty collaborations. Different fields, one thread: making complex systems work for real people.

0 Active collaborations
0 Enrollment records analyzed
0 Years of historical data
0 Model accuracy

ML Yield Prediction Model

with Dean Oya Tukel, Martin Tuchman School of Management

Universities guess at enrollment yield more than they admit. We're replacing the guess with a model. It forecasts which admitted students will actually enroll, trained on 12,000+ records spanning 15 years of historical data. Current performance: 72% accuracy, 70% precision.

  • My role: data cleaning, feature engineering, model training, evaluation
  • Status: in progress — [SUMMER SYMPOSIUM SHOWCASE? Confirm]
  • Methods: [FEATURE ENGINEERING DETAILS, MODEL SELECTION — needs Rishab's input]
Pythonscikit-learnpandasPredictive Modeling

AI Accessibility for Neurodivergent Users

with Prof. Andrew Klobucar, NJIT Humanities

Mainstream AI interfaces assume a neurotypical user. This research asks what changes when you stop assuming that. We study how students with ADHD, anxiety, and autism actually use AI tools, and we prototype interfaces designed for them from the start. This work feeds directly into AdaptIQ.

  • My role: design research, user interviews, prototyping
  • Status: in progress
  • Research question: [EXACT FRAMING — needs Rishab's input]
HCIAccessibilityClaude APIPrototyping

NFT Marketplace Research

with Prof. Jim Shi

Decentralized marketplaces promise open access but their mechanics are poorly understood. This project examines how NFT marketplaces actually behave: [CONTRACT DESIGN / UX / TOKENOMICS — which aspect, needs Rishab's input].

  • My role: [SPECIFIC CONTRIBUTIONS — needs Rishab's input]
  • Status: in progress
BlockchainDeFiMarket Design