Anirudh Sunil

About Me

I'm a passionate software engineer specializing in AI and security. Currently, I am pursuing a Bachelor of Science in Mathematics and Computer Science at UIUC, graduating Dec. 2026.

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Work Experience

Research Assistant

University of Chicago

Jan. 2026 - May 2026

Improve scientific artifact discoverability and reproducibility for Trovi by discovering, evaluating, and integrating research artifacts
Normalize metadata and write concise summaries to enhance data accessibility and utility
Engage with authors, refine curation tools, and analyze coverage and trends to support the Chameleon project

Data Analyst Intern

National Center for Supercomputing Applications

Aug. 2025 - Dec. 2025

Preprocessed geospatial and socioeconomic feature data for the Amazon in Brazil, enhancing data quality for analysis.
Conducted data modeling, analysis, and predictive assessments to provide insights for decision-making processes.
Created maps and other data visualizations with Python, facilitating better understanding of complex data sets.
Assisted in the development, training, validation, and testing of machine learning algorithms, improving model accuracy.

Software Engineer Intern

Warmly

YC S20

Jun. 2025 - Aug. 2025

Implemented Salesflow email integration with TypeScript to optimize customer outreach by 87%.
Integrated CRM system with React, Postgres, and SQL to simulate sales team interactions with Redis server for authentication, improving data management.

Software Engineer Intern - Cloud Security

Prancer Enterprises

Jun. 2022 - Aug. 2022

Configured AWS S3 buckets to organize layout, improving data access efficiency by 130%.
Reconfigured Kubernetes pods to optimize resource allocation, enhancing the performance of clusters and nodes.
Established secure connections to regulate SQL databases, successfully preventing 10 injection attacks.
Utilized Shift Left Security tools (Burp Suite, OWASP ZAP, DirBuster) to secure websites and reduce vulnerabilities.

Projects

StackSnap

Built an AI-powered interactive debugger that visualizes Python code execution line-by-line. Engineered a custom execution engine using sys.settrace to capture real-time call stack frames and local variable data across multi-file projects. Integrated a context-aware AI assistant using LangChain and the Keywords AI API for intelligent debugging explanations.

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Rankd

Built using Supabase, NextJS, and Tailwind. Used ELO algorithm to calculate rankings for companies and characters for leaderboard display. Currently has 150+ users and more than 500+ games played.

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LLMJudge

Developed a web app with Firebase, TypeScript, and Tailwind CSS that benchmarks prompts and LLM outputs on length and tone. Evaluated Gemini 2.0 Flash output with Perplexity Sonar, R1-1776, and Llama 3 with API calls and optimized. Stored data for prior prompts and scores in CSV and visualized overall evaluation scores with bar chart.

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PoseMind AI: Contextual Yoga Recommender

Developed a contextual Yoga Pose recommender app using Firestore, Vector Search, Langchain, and Gemini to deliver personalized pose suggestions based on user input. Implemented vector search and AI-generated embeddings to enable natural language querying and efficient retrieval of yoga pose recommendations. Designed and deployed a user-friendly web application with AI capabilities, integrating text, images, and audio for an enhanced user experience.

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Medicina.ai

Designed web app with Python and Flask to update heart disease risk using linear regression on user input data. Stores data in SQL database for login data and local user data and continuously updates visual chart to display user risk for diabetes and heart disease. Implemented LLM chatbot feature using Gemini API for real-time communication with user.

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Quantitative Analysis of Protein Structure

Worked with Chad Rienstra Lab to develop an automated tool to compare experimental and simulated SSNMR EmRe protein data with ZNCC scores using Python and Bash scripts.

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