04The surveyor

Route history

MS Computer Science at University of Illinois Chicago. Building tools where scale and responsibility share the same codebase. Currently based in Chicago. The short version: I like systems that are measurably correct and demonstrably fair. Résumé (PDF) ↗

Looking for now

Graduating May 2026 and open to full-time software engineering and applied ML / research roles — ideally where responsible AI, data systems, or geospatial work meet. Based in Chicago, open to relocation.

The throughline — fairness

I didn't come to fairness through theory — I took one course, pulled the thread, and couldn't put it down. Each project since has moved one layer closer to the systems that quietly decide things about people: first learning to measure bias, then to explain models, then to build the tools that catch them, and now to stress-test AI where the stakes are legal and civic.

    01

    Measure

    Fall 2025

    CS 516 · Responsible Data Science & Algorithmic Fairness, UIC

    Toxicity in LLMs — a replication study

    Replicated DExperts decoding-time detoxification on GPT-2 against RealToxicityPrompts, then broke it on adversarial ToxiGen. The lesson that hooked me: a method can score ~100% on explicit toxicity yet crack on implicit hate (98.5%) — and at a ~10× latency cost. You can’t fix what you can’t measure honestly.

    Read the study ↗
    02

    Explain

    Spring 2026

    Socially Responsible AI, UIC

    Galaxy Morphology XAI

    Benchmarked four post-hoc explainers (Grad-CAM, LIME, Integrated Gradients, GradientSHAP) across four CNN architectures on galaxy imagery, scored by faithfulness metrics. The finding: no explainer wins universally — rankings flip with architecture and dataset. Trust in a model has to be earned per-context, not assumed.

    View project ↗
    03

    Build

    Spring 2026 · MS Project

    Master's project, UIC

    FairLint DL

    Turned the research into a tool engineers actually touch: a deep-learning fairness debugger shipped as a VS Code extension, scanning models for demographic disparities in-editor via a two-phase gradient-ascent counterfactual search. Auditing time dropped 40% versus script-based workflows. Fairness belongs in the loop, not the postmortem.

    View project ↗
    04

    Investigate

    2026 · now

    Northwestern GAIN — Agentic AI Investigative Journalism Challenge

    FairGuard

    Reusable Agent Skills for investigative journalism, built with Claude Code and run over 1M+ federal lobbying records and congressional press releases. The anchor finding: the Artemis Group — founded by a former NASA Administrator — directs 39% of its filings at NASA with four former officials on staff, plus a ranked map of comparable revolving doors across 23 agencies.

    View project ↗
    05

    Benchmark

    2026 · now

    Advised by Prof. Saeid Tizpaz-Niari, UIC

    TaxMR — robustness for tax LLMs

    Low-income taxpayers increasingly ask AI for tax help, where a wrong or unstable answer costs a real refund. TaxMR uses metamorphic testing — swap a name, add an irrelevant sentence, reword the question, push back — and checks the answer doesn’t move. The thesis: neurosymbolic grounding, where only typed inputs reach an executor, is the most robust, because a name physically can’t change the result.

The pattern I keep chasing: AI is making more and more decisions about people who can’t see inside it. I want to keep building the instruments that hold it accountable — whether that’s an editor extension, an investigative agent, or a robustness benchmark.

Experience — 8 waypoints

Jun 2026Present

Chicago, IL

Machine Learning (Research) Engineer

RISC Lab · UIC

Metamorphic robustness benchmarking of tax-question-answering LLMs (TaxMR) in the Responsible, Informative, and Secure Computing Lab.

  • Building TaxMR: 130 CPA-labeled VITA tax questions expanded to 2,080 metamorphic cases across four relations (demographic name swaps, irrelevant context, paraphrase, sycophantic pushback).
  • Comparing robustness across base, RAG (IRS Pub 4491), and neurosymbolic (PAL) regimes on ~7 models; conditional violation rate with cluster-bootstrap CIs and exact McNemar tests.
  • Advised by Prof. Saeid Tizpaz-Niari; Phase 1 pipeline validated end-to-end on Qwen 2.5 7B.

Aug 2025Present

Chicago, IL

Graduate Research Assistant

The Urban Transportation Center · UIC

Full-stack freight analytics toolkit and geospatial pipelines for 285+ Chicago-region municipalities.

  • Engineered a Next.js + FastAPI freight toolkit visualizing crash metrics and traffic volumes across 285+ municipalities, deployed on UIC RHEL9 with Docker and Nginx.
  • Architected Python pipelines processing 8.5M+ origin–destination pairs (300GB+) with chunked, atomic operations; containerized OpenTripPlanner to route across 2,926 zones.
  • Built an OpenStreetMap Overpass extraction pipeline classifying 10,000+ US railyard polygons into intermodal, classification, and spur categories.

May 2025Aug 2025

Chicago, IL · Remote

Open Source Software Engineer

Google Summer of Code · OpenStreetMap

OpenLR-compatible temporary road closure database, API, and map UI for the OSM ecosystem.

  • Built a temporary road closures database and RESTful API with PostgreSQL/PostGIS and FastAPI for real-time closure reporting in OSM navigation apps.
  • Implemented OpenLR location referencing for cross-platform encoding across OSM-based navigation systems.
  • Shipped a Next.js + Leaflet web app for community closure submissions; deployed on a dedicated OSM server with Docker, Nginx, auto-renewing SSL, and GitHub Actions CI/CD.

Feb 2025May 2025

Chicago, IL

Research Assistant

University of Illinois Chicago

Graph models of the Chicago road network for optimal congestion-zone analysis.

  • Constructed a road network graph of Chicago with OSMnx and NetworkX, filtering to primary/secondary roads for computational efficiency.
  • Engineered bounded cycle-detection algorithms to identify congestion zones and optimal camera placements within 3–5 miles of the city centroid.

Dec 2023Jul 2024

New York, NY · Remote

Software Engineer

SimPPL

Led a 5-person team; LLM hate-speech research and social network visualization tooling.

  • Led a team of 5 building a project discovery platform for fellows and team leads across the organization.
  • Co-authored a report with Prof. Deb Donig and the ADL on the impact of LLMs on hate-speech propagation in online forums.
  • Built a coordination network graph visualizer used across YouTube, Truth Social, and BlueSky data.

Dec 2023May 2024

Boston, MA · Remote

Software & AI Engineer

Boston University

Virtual marketplace experiments on fake advertising and consumer behavior.

  • Led a virtual marketplace experiment on Empirica.ly and React.js where producers choose between honest and deceptive ads while consumers select products.
  • Worked with Prof. Marshall W. Van Alstyne and Dr. Swapneel Mehta in the Digital Information Research Lab.

Mar 2023Nov 2023

Remote

Software Engineer

SimPPL

Network analysis of YouTube video ecosystems via the YouTube Data API.

  • Analyzed YouTube videos, comments, and channels; visualized video–user–comment relationships as network graphs.
  • Shipped product pages for the company site, deployed on Vercel and Netlify with backend API testing and documentation.

Jun 2021Jul 2021

Mumbai, IN

Machine Learning Intern

Kaizen Future Tech

Stacked CNN/ResNet ensembles for natural disaster classification; Arduino IoT systems.

  • Built CNN and ResNet image classifiers for natural disaster detection reaching 95% accuracy.
  • Developed a stacked ensemble with XGBoost as meta-classifier to improve generalization.

Education

Aug 2024May 2026

University of Illinois Chicago

MS, Computer Science

GPA 3.7 / 4.0

  • NLP
  • Data Science
  • Algorithmic Fairness
  • Responsible AI

20212024

University of Mumbai · TSEC

BE, Information Technology

GPA 9.32 / 10

  • DSA
  • Machine Learning
  • Computer Networks
  • Data Mining
  • Image Processing

Instruments

Languages

  • Python
  • TypeScript
  • JavaScript
  • SQL
  • C/C++
  • GLSL

ML & Data

  • PyTorch
  • scikit-learn
  • PySpark
  • Pandas
  • NumPy
  • LangChain / LangGraph
  • Captum
  • OpenCV
  • Transformers

Web & APIs

  • Next.js
  • React
  • FastAPI
  • Node.js
  • Tailwind CSS
  • GSAP
  • Three.js
  • Leaflet / MapLibre

Geospatial

  • PostGIS
  • OSMnx
  • NetworkX
  • GeoPandas
  • Shapely
  • Valhalla
  • OpenLR
  • ArcGIS Pro

Infra

  • PostgreSQL
  • MongoDB
  • Neo4j
  • Redis
  • Docker
  • Nginx
  • GitHub Actions
  • Linux