• 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
- Built web scraping and data ingestion pipeline processing 5,000+ trivia questions from online sources and Kaggle datasets, implementing deduplication via RapidFuzz (80% similarity threshold) and data validation.
- Trained logistic regression and gradient-boosted models achieving 78% accuracy in difficulty prediction, enabling real-time question adaptation based on user performance patterns.
- Implemented input validation and parameterized queries to prevent SQL injection, filtering malformed data and handling edge cases in JSON parsing.
Rutgers University - Teaching Assistant
- Designed and delivered weekly recitation sessions for 25+ students, creating supplementary problem sets that reinforced core algorithmic concepts and improved average quiz scores.
- Supported 100+ students across office hours by diagnosing recurring misconceptions and tailoring explanations to different learning styles, reducing repeat debugging questions over the semester.
Rutgers Dept. of ECE - Research Assistant
- Scraped and indexed metadata from 7,500+ computer engineering papers (IEEE, CVPR) using Requests and BeautifulSoup, extracting structured data on authors, affiliations, topics, and citations.
- Designed a PostgreSQL relational schema with junction tables to support many-to-many author–paper relationships, incorporating affiliation-based author disambiguation to resolve name collisions.
- Developed FastAPI search engine with asynchronous request handling, achieving sub 1-second keyword retrieval across indexed abstracts and metadata.
Valence 🏆
April 2026
GeoSense
April 2026
DraftRoom
March 2026
Go Phish! 🏆
Dec. 2025
DraftRoom
- Engineered a proprietary 0–100 DraftRoom Score combining True Shooting %, opponent-adjusted scoring, defensive impact, and playmaking efficiency — replacing traditional box score evaluation for fantasy draft decisions.
- Built a FastAPI backend on live NBA.com data with an exponentially weighted trajectory model, per-opponent defensive rating adjustments, and a concurrent 30-player pipeline with 2-hour TTL caching.
- Deployed a production full-stack app on Vercel and Render with GitHub CI/CD, featuring real-time debounced search, animated DR Score history charts, and injury-aware start/sit recommendations.
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
- A decentralized API investment marketplace where API owners deploy their APIs, investors buy API-specific tokens to fund their growth, and the market dynamically prices each API based on token trading activity.
- Uses x402 for seamless machine-to-machine payments, enabling AI agents and developers to call APIs and pay per-use automatically with no subscriptions or billing dashboards.
- Creates a virtuous cycle where investor funding scales API infrastructure, usage generates revenue shared with token holders, and market demand continuously adjusts pricing via a 24-hour TWAP formula on Solana.
SCBC '26: 2nd Place for Best Use of Solana Track