Vaishnavi Jadhav

MS CS @ UIC

Looking for 2027 full-time opportunities

Opening Statement

About

I'm Vaishnavi Jadhav, an MS Computer Science student at UIC graduating May 2027. I started out at IBM working on mainframe systems, then pivoted into AI/ML. I'm on a research and founder track now, building more than I take courses. Looking for somewhere innovative to work next.

The Record

Work Experience

  1. Software Engineering Intern @ KNOWN (Cyclical Inc.)

    2026 — 2026

    Shipped production iOS and Android releases for a hormonal health startup using React, TypeScript, Capacitor, Supabase, SwiftUI, WidgetKit, Xcode, and Google Play Console. Built native Period and Daily Wisdom widgets with real cycle data, fixed Apple Sign-In and App Group data-sharing issues, and owned the mobile release pipeline through App Store Connect.

  2. Graduate Research Assistant @ University of Illinois Chicago

    2026 — Present

    Researching NLP and causal AI for Alzheimer's biomarker discovery under Prof. Lu Cheng, with Prof. Natalie Parde as UIC co-advisor. Built and evaluated a guardrailed hybrid pipeline on 2,167 participants in the NACC autopsy cohort using FCI, literature retrieval, multi-model swap tests, bootstrap stability analysis, and NCSA Delta HPC. First-authored the 10-page paper submitted to IEEE Big Data 2026 on August 21, 2026; the work forms the basis of my MS thesis.

  3. Application Developer @ IBM -- Bangalore, India

    2024 — 2025

    Maintained and migrated legacy enterprise applications on IBM mainframe systems. COBOL, z/OS, DB2 production pipelines. Zero-downtime, high-reliability systems where 99% uptime is considered a failure.

  4. Frontend Developer Intern @ AHEN -- Pune, India

    2024 — 2024

    Built responsive web interfaces. Coordinated with designers and backend engineers. Final semester of undergrad.

Exhibits

Projects

  1. 01

    Portfolio Court ↗

    2026

    Portfolio Court turns my project portfolio into a courtroom where Builder, Strategist, and Contrarian agents debate each project. I built it with Next.js, TypeScript, Tailwind CSS, the Notion API, and GLM-4.5-Flash, then deployed debates for all 11 projects at

    JavaScript · ReactJS · Node.js · Tailwind CSS

    take it to court →
  2. 02

    AI Police ↗

    2026

    AI Police tests whether coding agents accurately report their work. I built a Python harness with Docker isolation, command traces, hidden-test grading, and a browser case viewer for 25 recorded runs. The repository and viewer are live on GitHub Pages.

    Python · JavaScript · ReactJS

    take it to court →
  3. 03

    Guardrailed Causal Discovery for Alzheimer's Biomarkers ↗

    2026

    First-author research on a guardrailed hybrid causal discovery pipeline over 2,167 participants in the NACC autopsy cohort. Combined FCI on rank-transformed clinical data with literature evidence, exogeneity constraints, swap tests, and bootstrap stability analysis. Found that LLM direction judgments flip with argument order while graph adjacencies remain stable and most orientations are sample-dependent. Submitted the 10-page paper "A Guardrailed Hybrid Pipeline for Causal Discovery of Alzheimer's Biomarkers" to IEEE Big Data 2026 on August 21, 2026.

    Python · pandas · NumPy · scikit-learn

    take it to court →
  4. 04

    Kindred

    AI-powered relationship intelligence engine that maps professional networks using graph-based knowledge representation (Neo4j). Tracks interactions, surfaces actionable follow-ups, and helps maintain meaningful connections. Won Best Project Award at TRAE/

    ReactJS · Node.js

    take it to court →
  5. 05

    Moral Machine: LLM vs Human Ethical Benchmarking ↗

    Systematic comparison of ethical decision-making between major LLMs and human responses from MIT's Moral Machine dataset. Trained classification models to measure moral divergence across different LLM architectures. Team of 5, course project.

    Python · pandas · NumPy · matplotlib

    take it to court →
  6. 06

    Delulify ↗

    Python tool that intercepts runtime errors and transforms them into emotionally supportive debugging hints. Because your stack trace should not make you cry. Open source, has a star and a fork.

    Python

    take it to court →
  7. 07

    UrbanScale ↗

    2026

    RL-based warehouse placement optimization for quick-commerce. Trained a MaskablePPO agent on real Chicago road topology (extracted via OSMnx) with a custom Gymnasium environment and multi-objective reward function. Agent outperformed greedy, random, and population-density baselines. Selected for NVIDIA Spark Hack (1 of 30 nationally). CS 594 Reinforcement Learning. Team of 3 -- designed the RL environment, reward model, and training pipeline.

    Python

    take it to court →
  8. 08

    LoopBack ↗

    2026

    Civic engagement app for reporting and tracking local issues in Chicago. Full-stack with Supabase backend, geolocation-based issue clustering, and deployed end-to-end. Built at DemonHacks (DePaul). Team of 6.

    Python · ReactJS · Cloud deployment

    take it to court →
  9. 09

    Pillar ↗

    2026

    Real-time news transparency platform that maps media ownership networks. Ground News shows political bias -- Pillar shows who is paying. Built a full Snowflake data warehouse with Cortex LLM inference (Llama 3.1-70b), FastAPI backend, RSS ingestion pipeline, and ElevenLabs-powered audio summaries. Top 3 finalist in Social Impact track at Uncommon Hacks 2026 (UChicago). Team of 2 -- built the data pipeline, LLM integration, and system architecture.

    Python · ReactJS · Tailwind CSS · RESTful API

    take it to court →
  10. 10

    EdgeRecall ↗

    Stateful AI assistant running entirely on Cloudflare's edge network. Uses Llama 3.3-70b via Workers AI for inference and Cloudflare KV for persistent conversational memory across sessions. Deployed and live. Built as a personal project exploring edge-native AI architectures.

    JavaScript · Tailwind CSS · Cloud deployment · RESTful API

    take it to court →
  11. 11

    Entropy-Based Selective Step Verification

    2026

    Research on making small LLMs reason faster without losing accuracy. Uses token-level entropy to identify uncertain reasoning steps, then selectively verifies only those steps using a Process Reward Model. Saves 51-57% compute. Tested on Qwen2.5-Math-1.5B, Llama 3.2 3B, and Gemma 3 4B across GSM8K and a custom options trading dataset. NeurIPS-format paper scored 9.8/10. Professor offered summer research continuation. CS 517 Socially Responsible AI.

    Python

    take it to court →
  12. 12

    Pathfinding Algorithm Visualizer ↗

    Interactive visualization of pathfinding algorithms (BFS, DFS, Dijkstra, A*) with real-time grid manipulation. Built to understand and demonstrate graph traversal concepts visually.

    Python

    take it to court →
  13. 13

    Redacted Lore ↗

    2026

    Collaborative storytelling platform where community-written stories are progressively uncovered through automatic redaction mechanics, inspired by SCP Foundation archives. Built with finite state machines for game logic, Redis for real-time state sync, and Devvit for Reddit-native deployment. Won the Reddit Daily Games Hackathon. Solo build, 48 hours.

    JavaScript · ReactJS

    take it to court →

Credentials

Skills

Frameworks/Libraries

  • pytest
  • Flask
  • LangGraph
  • FastAPI
  • PyTorch
  • HuggingFace Transformers
  • Stable Baselines3 / MaskablePPO
  • Pandas / NumPy / Scikit-learn
  • Node.js
  • Tailwind CSS
  • React
  • AutoGluon
  • Pandas
  • scikit-learn
  • Express.js
  • NumPy
  • React.js
  • HTML
  • CSS
  • Bootstrap
  • Next.js

Tools & Platforms

  • Vercel
  • Notion API
  • GitHub Pages
  • NCSA Delta / SLURM
  • LaTeX / Overleaf
  • z/OS Mainframe
  • TensorBoard
  • Git / GitHub
  • Cloudflare Workers
  • Snowflake + Cortex
  • Docker
  • Git

Specialized Knowledge

  • Causal Discovery (FCI / causal-learn)
  • Bootstrap Stability Analysis
  • Process Reward Models
  • Finite State Machines
  • Reinforcement Learning
  • LLM APIs (Claude, Gemini, Llama, OpenAI)
  • MongoDB
  • DB2
  • IMS
  • AR Foundation / Unity AR
  • Machine Learning
  • z/OS (Mainframe)
  • MySQL

Programming Language

  • JavaScript
  • SQL
  • TypeScript
  • Python
  • COBOL
  • C#
  • C++
  • Javascript

Other Skills

  • Cloudflare KV / D1
  • DB2
  • Neo4j
  • Redis
  • Agile Development (Scrum/Kanban)
  • UI/UX Design

Discovery

Daily Readings

all readings →

Case History

Coursework

  1. CS 598 M.S. Thesis Research

    In progress, Fall 2026

    University of Illinois Chicago

    Thesis research on a guardrailed hybrid pipeline for causal discovery of Alzheimer's biomarkers using the NACC autopsy cohort. Primary advisor: Lu Cheng; UIC co-advisor: Natalie Parde.

  2. CS 401 Computer Algorithms

    Done, Fall 2025

    University of Illinois Chicago

    Algorithm design, complexity analysis

  3. CS 418 Introduction to Data Science

    Done, Fall 2025

    University of Illinois Chicago

    Data wrangling, visualization, ML pipelines

  4. CS 594 Reinforcement Learning

    Done, Spring 2026

    University of Illinois Chicago

    MDPs, Monte Carlo, Q-learning, TD(lambda), function approximation. Project: UrbanScale (MaskablePPO warehouse optimization). Professor: Brian Ziebart

  5. CS 491 Graduate Seminar

    Done, Spring 2026

    University of Illinois Chicago

    Attendance-based graduate seminar

  6. CS 517 Socially Responsible AI

    Done, Spring 2026

    University of Illinois Chicago

    Fairness, bias, adversarial ML, conformal prediction. Project: Entropy-Based Selective Step Verification. Professor: Lu Cheng

  7. CS 411 Artificial Intelligence I

    Done, Fall 2025

    University of Illinois Chicago

    Search, logic, probabilistic reasoning, ML fundamentals

  8. CS 544 Machine Learning in Production

    In progress, Fall 2026

    University of Illinois Chicago

    Production ML systems, model quality, testing, MLOps, data infrastructure, and deployment reliability. Professor: Saeid Tizpaz-Niari

  9. CS 554 Advanced Topics in Concurrent Computing Systems

    In progress, Fall 2026

    University of Illinois Chicago

    Advanced concurrent computing systems. Professor: William Mansky