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Résumé — last updated 2026-07-30

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Vihaan Sarin

Full-Stack Software Engineer

+1 608-282-5559vihaansarin@gmail.comMadison, Wisconsin@dexd7in/vihaan-sarin

Education

University of Wisconsin–Madison

Bachelor of Science, Computer Science & Data Science — GPA: 3.74

Madison, WI · Sep 2022 – May 2026

Delhi Public School, Dwarka

New Delhi, India · 2018 – 2022

Technical Skills

Languages: Python, Java, JavaScript, TypeScript, SQL, C++, C, Bash, R, HTML, CSS

Frameworks & Tools: React.js, React Native, Node.js, Express, Flask, FastAPI, Apache Spark, JUnit, JavaFX, Docker, Git, GCP, BigQuery, VS Code, PyCharm, IntelliJ, Eclipse, WSL

Databases & Libraries: PostgreSQL, MongoDB, Cassandra, pandas, NumPy, SDV, Bootstrap, dplyr, Tidyverse, ggplot2

Systems & Platforms: Unix/Linux, HDFS, Distributed Systems, POSIX Threads, Concurrency, Systems Programming, REST APIs, CI/CD Pipelines

Concepts & Coursework: Algorithms, Data Structures, Operating Systems, Database Management, Object-Oriented Design, Machine Learning, Data Architecture, Data Modeling, Data Visualization, Big Data Systems

Experience

Software Engineer Intern (Data & AI)

May 2025 – Nov 2025

Innover Digital · Remote / Atlanta, GA

  • Designed a full-stack React + FastAPI platform for synthetic data generation, including an LLM-based generation mode (OpenAI SDK, guardrails, preset templates) producing schema-validated sample rows.
  • Integrated five SDV models (CTGAN, TVAE, GaussianCopula, CopulaGAN, HMASynthesizer) and a PII masking engine (spaCy NER + Faker) for secure, constraint-preserving relational synthesis.
  • Built tabbed previews, post-generation dashboards, and export pipelines, cutting dataset-exploration setup time 30%.
  • Optimized metadata inference and constraint-handling pipelines, cutting runtime 25–40%. Internship extended three months on the strength of it.

Web Development Intern

Jul 2024 – Aug 2024

Thales · Noida, India

  • Built a full-stack animal adoption platform (HTML, CSS, JavaScript) with interactive filtering and secure adoption workflows across responsive, cross-device layouts.
  • Architected modular components and optimized client-side rendering with efficient DOM updates, cutting page load times 25%.
  • Integrated and validated backend routes for data exchange, applying Thales' engineering standards for secure, fault-tolerant deployment.

Projects

Synthetic Data Platform — React, FastAPI, Python, SDV, OpenAI SDK, spaCy

2025

  • A full-stack platform for generating synthetic relational data at scale — five SDV models, an LLM generation mode, and PII masking built in from the start.
  • 25–40% pipeline runtime cut — Metadata inference and constraint-handling pipelines, measured across benchmark runs.
  • 30% faster dataset-exploration setup — Tabbed previews, post-generation dashboards, and export pipelines.
  • 3 months internship extended — Extended on the strength of the metadata inference work.

Aura Farmer — React Native, Supabase

2025

  • A React Native + Supabase social app exploring engagement without public likes or follower counts — an "aura points" system instead. Finished top 3 of 15 teams in Voodoo’s Studio incubator.
  • 3 / 15 incubator finalist — Top 3 of 15 teams, Voodoo's Studio incubator.
  • 40% fewer redundant API calls — Supabase query optimization.
  • 2.0s → 1.5s faster profile fetch time — Same optimization pass, measured in testing.

MiniSpark — C, POSIX threads

2025

  • A parallel data-processing framework written from scratch in C — Resilient Distributed Datasets, a DAG scheduler over a POSIX thread pool, and lineage-based recovery — built to understand what Spark actually does underneath the API.
  • 4× throughput on multicore — DAG scheduler over a POSIX thread pool, datasets up to 10GB.
  • <5% overhead recovering lost partitions — RDD lineage recomputation.
  • 20% less memory fragmentation — Custom allocators, thread-safe queues and mutexes.

WSH — C, POSIX

2025

  • A POSIX-style shell written in C, interactive and batch modes — fork/exec, 128-argument parsing, environment variables, built-ins, piping, and background jobs, covering 80%+ of daily Bash use.
  • 80%+ of daily Bash functionality covered — fork/exec, piping, background jobs, built-ins.
  • Zero memory leaks under Valgrind — 500+ commands tested, including nested pipelines.
  • Within 5% of Bash execution speed — On standard workloads.