Kartik Gangwar

I build systems that turn complex workflows into reliable products.

Computer Science and Data Science at UW–Madison. I work on backend systems, mobile products, data pipelines, and machine-learning applications.

Recently Shipped — Studi
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Featured Work

Building products that solve real problems through reliable systems.

Live on the App Store

Studi

Study coordination for UW–Madison students

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Helps UW–Madison students discover study sessions, coordinate with classmates, and connect through real-time messaging.

What I Built

Production mobile app and backend spanning authentication, study sessions, friend discovery, real-time messaging, push notifications, analytics, and moderation.

Key Systems

→Built real-time coordination workflows with Firebase and Firestore
→Built class-aware study-session discovery and friend discovery workflows
→Shipped v1.0 with 690+ automated tests, including 270+ emulator security tests
→Integrated PostHog analytics for funnel tracking and user engagement monitoring
React NativeTypeScriptFirebaseFirestorePostHog
Studi app home screen showing Hi Kartik, Your next session card for HISTORY 101 Review for 5th quiz, and Your classes list with COMP SCI 400, MATH 320, and HISTORY 101
Live mobile product · 2,000+ downloads

FiPet

A gamified financial-literacy app combining learning quests, pet progression, customization, and real-time social features.

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Engineering Focus

→Hardened native iOS SwiftUI/Firebase architecture for a production app with 2,000+ downloads
→Expanded native iOS regression coverage from 164 to 521 tests (+218%) across authentication, Firebase contracts, onboarding recovery, and asynchronous state handling
→Diagnosed and fixed Swift Task/AsyncStream lifecycle bugs retaining battle view models and Firestore listeners
→Added environment safeguards across 4 native build configurations spanning authentication, account deletion, social features, and real-time battles
SwiftSwiftUIiOSFirebaseFirestore
FiPet app home screen showing Level 2 orange fox pet, XP progress, daily streak tracker, and financial literacy quests

AI Market Sentiment Dashboard

Completed • Team project

Real-time AI pipeline: Yahoo/RSS ingestion, evidence validation, exact/semantic deduplication, canonical story reconciliation, embedding-based theme clustering with deterministic identities, versioned SQLite persistence (25 tables, 16 indexes, 64 integrity triggers).

AI Market Sentiment Dashboard with sentiment analysis, probability mix, NVDA price history, and market headlines
→Architected versioned SQLite schema with 25 tables, 16 indexes, and 64 integrity triggers for data consistency
→Built exact/semantic deduplication pipeline with canonical story reconciliation and embedding-based theme clustering
→Shipped with 3,500+ passing automated tests covering ingestion, validation, storage, and API contracts
FastAPIReactPythonSQLiteNLP

TrueNeed

Hackathon • 24 hours

Mutual-aid platform connecting users who post help requests and offers. Firebase Auth handles sign-in, Firestore powers user-scoped match inbox and live feed updates.

→Built Firebase Authentication with auth-dependent navigation
→Designed user-scoped match inbox with live Firestore feeds
→Prototyped match-acceptance workflow across 4 Firestore collections
→Implemented timestamped handoff records with missing-reference checks
React NativeFirebaseFirestoreTypeScript

Experience

Building production systems and shipping reliable software.

Software Engineering Project Manager

AI@UW

March 2026 – Present

→Lead a 5-person engineering team building a financial-news intelligence platform across ingestion, NLP, prediction, backend, and frontend systems
→Integrated independently developed Python/FastAPI, NLP, prediction, and React components into an end-to-end system with typed API contracts, validation boundaries, provider fallbacks, and deterministic data workflows
→Implemented REST APIs and a 15-minute provider cache with stale-data fallback, reducing 10 repeated requests to 1 external provider call in controlled testing

Impact

Led architecture and integration across a 5-person engineering team building a financial-news intelligence platform

FastAPIReactPythonSQLite

Lead Software Engineer (CTO)

FiPet

October 2025 – Present

→Expanded native iOS regression coverage from 164 to 521 tests (+218%), validating Firebase contracts, authentication flows, onboarding recovery, account integrity, and asynchronous state handling
→Diagnosed and fixed Swift Task/AsyncStream lifecycle bugs that retained battle view models and Firestore listeners, introducing explicit task ownership and cancellation
→Hardened SwiftUI/Firebase architecture for a production iOS app with 2,000+ downloads, adding environment safeguards across 4 native build configurations spanning authentication, account deletion, social features, and real-time battles

Impact

Improved native iOS reliability for a production app with 2,000+ downloads through regression testing, concurrency debugging, and environment safeguards

SwiftSwiftUIiOSFirebaseFirestore

Technology Strategy Intern

iStart Valley

June 2023 – September 2023

→Analyzed the technical and market feasibility of a VR mental-health product, including potential AI/ML approaches
→Translated technical findings into product and business recommendations
→Presented recommendations in iStart Valley global business competition, advancing to the Global Semifinals

Impact

Global Semifinalist — iStart Valley Business Pitch Competition

VRAI SolutionsProduct Strategy

Software Engineering Instructor

STEMShala Enrichment Center

June 2023 – August 2025

→Designed and taught project-based Python and JavaScript curriculum for 40+ students
→Achieved a 90% project completion rate across student programming projects
→Mentored students through software and robotics projects, debugging, and problem-solving

Impact

Taught software development to 40+ students with a 90% project completion rate

PythonJavaScriptRobotics

About

Building systems that work reliably at scale.

I'm a Computer Science and Data Science student at UW–Madison focused on building reliable software systems. I work across backend development, native iOS, data pipelines, and machine-learning infrastructure, with a particular interest in what happens after a prototype works: architecture, testing, security, integration, and production reliability.

My recent work includes native iOS engineering for FiPet, a production app with 2,000+ downloads; shipping Studi v1.0 to the App Store with 690+ automated tests; and leading a five-person AI@UW engineering team building a financial-news intelligence platform.

I enjoy working on systems where reliability matters — from debugging Swift concurrency and real-time Firebase state to designing durable data pipelines and backend APIs.

Technical Profile

Tools and technologies I work with to build reliable systems.

Languages

PythonJavaC/C++SwiftJavaScriptTypeScriptSQL

Frameworks & Platforms

ReactReact NativeSwiftUIFastAPINode.jsFirebaseFirestoreSQLiteREST APIs

Developer Tools

LinuxGitGitHubGitHub ActionsDockerAWSAzureClaude CodeCodex

AI/ML & Data

PyTorchHugging Face Transformerssentence-transformersHDBSCANscikit-learnNumPyPandas

Get in Touch

Open to discussing projects, collaborations, or opportunities.

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© 2026 Kartik Gangwar. Built with Next.js and Tailwind CSS.