• Pico Resort, VT
Hey! I'm Ashad Shaik-Mohamed, a double major at
Rutgers University — New Brunswick, studying ECE and Math. I
enjoy building projects that push me and working on problems that
don't have obvious solutions. I'm interested in full-stack, machine
learning, and infrastructure. Enjoy exploring this portfolio and
feel free to reach out:
ashad.shaikmohamed@rutgers.edu
B.Eng in ECE & Mathematics, Rutgers University
B.Eng in ECE & Mathematics, Rutgers University
Stack
Python
React
Java
JavaScript
TypeScript
Rust
C
Node.js
MONDAY 🔧
Mar 30, 2026
>
Gearing up, designing projects.
Energy
Today
Meditato
May 2025 – Aug. 2025
Teaching Assistant
Sep. 2025 – Dec. 2025
Research Assistant
Sep. 2024 – Present
Meditato - Software Engineering Intern
- Developed a competitive trivia platform where players battle head-to-head in 10-question rounds using ELO-based matchmaking, alongside a learning mode that uses spaced repetition for recreational practice and skill-building
- Built hyperspecific web scrapers using BeautifulSoup and Apify to extract structured trivia data from Sporcle and JetPunk, building a 5,000+ question database and reducing preprocessing time by 35% through deduplication
- Engineered an ELO-based matchmaking system using a dynamic K-factor to stabilize new user ratings and pair players within a ±100 ELO rating window, achieving a 98% match rate with an average match time of ∼5 seconds
Rutgers Blockchain - Secretary
- Organized and led weekly meetings/hands-on technical workshops covering Web3 development, consensus mechanisms, and emerging blockchain protocols, creating a strong learning pipeline for 75+ active club members
- Built sponsor relationships to bring 10+ students to blockchain conferences, bringing home hackathon prizes
Rutgers Dept. of ECE - Research Assistant
- Scraped and indexed metadata from 10,000+ computer engineering papers (IEEE, CVPR) using Requests and BeautifulSoup to build a centralized library of pre-licensed research, reducing department spending by 20%
- Designed a PostgreSQL database schema to organize indexed papers by author, affiliation, and citation data, resolving same-name author conflicts using institution-based disambiguation to ensure accurate search results
- Developed a search engine using Elasticsearch enabling Rutgers ECE researchers to perform fast keyword searches
Valence 🏆
April 2026
GeoSense
April 2026
DraftRoom
March 2026
Go Phish! 🏆
Dec. 2025
DraftRoom
- Built a fantasy basketball analytics platform using React and TypeScript, featuring injury-aware start/sit recommendations and head-to-head team comparisons, deployed via Vercel and GitHub Actions CI/CD
- Designed a proprietary 0–100 player efficiency scoring system using FastAPI to pull live NBA data, Polars to aggregate and weight components (True Shooting%, Defense, Playmaking) and Recharts to visualize results
- Projected future game results using an EWMA, forecasting PTS, AST, REB adjusted for opp. defensive ratings
Go Phish!*
- Built a backend service capable of reliably handling high-volume concurrent events, processing 575+ clicks, 255+ form submissions, and 550+ email opens across simulated phishing campaigns.
- Developed an analytics API querying PostgreSQL to surface campaign performance dashboards, enabling identification of high-risk behavioral patterns across user cohorts.
- Integrated asynchronous request handling to reliably process high-volume user events during simulated attacks.
* HackRU F25 Maverick Winner
GeoSense*
- AI-powered geothermal intelligence platform that generates a fully personalized geothermal feasibility report for any US property in under 15 seconds, for free.
- Analyzes soil, climate, and geological data from USGS and NOAA to recommend the optimal system type, full financial breakdown (including IRA tax credits and state rebates), carbon impact, and nearby certified installers.
- Built with Next.js, Supabase, and Groq's LLaMA model; all financial calculations are hardcoded in TypeScript to ensure accuracy before AI generates the narrative report.
* HackPrinceton
Valence
- Built a decentralized API investment marketplace where API owners deploy APIs, investors purchase API-native tokens, and x402 enables seamless machine-to-machine pay-per-use transactions for AI agents and devs on Solana
- Engineered a TWAP-based dynamic pricing system using Solana Anchor programs that recalculates per-call API costs every 24 hours based on trading volume across Meteora liquidity pools, adjusting prices autonomously
- Implemented automated revenue splitting across owners, investors, and treasury on every API call
SCBC '26: 2nd Place for Best Use of Solana Track