Sanyam Garg
Age:
Madison, WI
I am a passionate UW–Madison junior pursuing a B.Sc. in Computer Science & Data Science. I thrive on solving complex problems and exploring innovative technologies.
Education
University of Wisconsin–Madison
Aug 2023 - May 2027
Degrees
Relevant Coursework
Tools
Programming Languages
Python, Java, C, Dart, SQL, Bash
DevOps & Infrastructure
Docker, Tailscale, Linux, Cloudflared, Git, Conda, Snakemake
Machine Learning & Data Science
PyTorch, NumPy, Pandas, Deep Learning, NLP
Web & Application Development
Flask, Flutter, Firebase, Node.js, REST APIs, WebSocket
Experiences
Century Financial
Dubai, UAE | June 2025 - Aug 2025
AI & Backend Development Intern
- AI Trading Assistant: Engineered the Python backend, integrating OpenAI's API with a RAG system to fetch live user portfolio data and generate personalized financial insights.
- Implemented the Model Context Protocol (MCP) to orchestrate tool calls, enabling the AI to securely manipulate data and store context across sessions while optimizing token usage.
- Real-Time Co-Browsing Engine: Built using Node.js and WebSockets. Utilized DOM mirroring instead of video streaming to drastically reduce bandwidth and latency.
- Developed a client-side masking feature to redact sensitive financial data before network transmission. This solution replaced a third-party tool and saved the firm $3,000+ annually.
Keles Group (UW–Madison)
Madison, WI | May 2025 - Present
Deep Learning Research Assistant
- Developing and evaluating deep learning models (VERMIN framework) in PyTorch to accurately predict DNA methylation from large-scale human/mouse genomic sequences.
- Performed extensive Exploratory Data Analysis on a massive 22-million-row dataset using Pandas in JupyterLab to investigate genetic variation and epigenetic markers.
- Implemented data processing workflows (Snakemake) on an HPC cluster and generated data visualizations to validate pipeline output.
Projects
Private Cloud & Server
Wanted full control over my data and a playground to experiment with infrastructure. Built a hybrid-cloud setup spanning cloud VPS and bare-metal Linux, connected securely with a Tailscale mesh network.
Now running 20+ services in Docker containers—from media automation to development tools. Used Cloudflare Tunnels for public access without exposing my IP. Wrote custom monitoring in Python and automated daily Bash/Cron backups to an off-site location.
Sentinel – Real-Time Threat Monitor
After exposing my server's SSH to the internet, I got curious—who's actually trying to break in? Within minutes, bots worldwide were hammering it with credentials like "root:admin". Built this to watch it happen in real-time.
Created a Python (FastAPI) pipeline that tails system logs over SSH, extracts attacker IPs, resolves their locations, and serves everything through a REST API that the dashboard polls every 1.5 seconds. Deployed with Docker and Cloudflare Tunnels. The map uses Leaflet.js to animate each attack as it happens.
Python Shell
Ever wonder how Bash actually works under the hood? I did. Built my own command-line shell in Python to learn how shells parse commands, spawn processes, and manage I/O.
Implemented core shell features like input/output redirection (<, >) and piping (|) by manually wiring up STDIN/STDOUT between child processes. Also added persistent command history.