Problem
Noisy multi-objective samples make the Pareto frontier uncertain, especially when the decision space is sampled indirectly through a black-box objective.
Project Write-Ups
Technical work, compressed for a deeper scan.
Each write-up is structured around the problem, approach, results, and lessons learned. Public code and formal papers will be linked here as they become available.
Operations Research
Pareto Confidence Bands
Approach
Fit Gaussian process surrogate models, generated posterior frontier simulations, and formulated a PuLP/CBC MILP with contiguity constraints.
Result
Built an automated Monte Carlo pipeline targeting confidence bands that cover at least 95% of simulated Pareto frontiers.
Lesson
The modeling challenge is not just finding a frontier; it is communicating uncertainty in a way that preserves decision usefulness.
NLP Infrastructure
SpokenCRS Dataset API
Problem
Conversational recommendation datasets such as ReDial and Inspired use heterogeneous formats that slow down benchmark setup.
Approach
Created CRSDataFrame and TurnWrapper abstractions with a unified turn-level schema for utterances, entities, ratings, and metadata.
Result
Reduced dataset onboarding time by an estimated 80-90% and enabled plug-and-play compatibility across 3+ CRS model architectures.
Lesson
Good research infrastructure removes silent data engineering work so model comparisons become cleaner and faster.
Market Sentiment
Reddit to Equity Direction
Problem
Social finance text is noisy, ticker-dependent, and difficult to align cleanly with price movement targets.
Approach
Scraped 7 finance subreddits with PRAW, classified sentiment using FinBERT, merged with yFinance data, and built sklearn preprocessing.
Result
Benchmarked 5 classifiers with GridSearchCV for TSLA, AAPL, and AMZN next-day direction labels.
Lesson
Signal quality depends heavily on timing, ticker ambiguity, and labeling choices before model selection matters.
HackMIT
Blind Karaoke
Problem
Create a fast, playful karaoke experience where the singer cannot see the lyrics and the app scores what they remember.
Approach
Built a Flask and Next.js prototype using Spotify playback, Whisper transcription, and lyric comparison logic.
Result
Developed during HackMIT, a 24-hour hackathon with about 1,000 selected students internationally.
Lesson
Real-time audio projects reward simple architecture, fast feedback loops, and clear scoring constraints.