About Me

Hey, thanks for stopping by my portfolio!
I'm Mian Abdullah, a junior at DePauw University pursuing a Bachelor's in Computer Science & Philosophy.
I'm a first-generation learner originally from Lahore, Pakistan. I've completed 4+ internships in strategy & AI, full-stack, and ML (including BCforward, Legislative Intelligence, iD Tech), taught 312+ students coding and robotics, co-founded Plutores (Web3 mortgage tech) and Mubtada, and built 30+ projects from GPT-powered apps to ML and mobile. On campus, I've held leadership in 6+ clubs and served as Vice President of DePauw Robotics.
Outside the tech world, you'll often find me on the soccer field, at a table tennis match, or engaging in spirited debate—especially on topics that bridge computer science, logic, and finance.
I believe in creating spaces where collaboration, curiosity, and innovation thrive. Would love to connect, exchange ideas, and explore potential collaborations.
Experience

Strategy & AI Intern
BCforward - Indianapolis, IN, USA
Dec 2025 - Present

Software Development Engineering Instructor
iD Tech - Texas, USA
May 2025 - Aug 2025

Machine Learning Intern
Legislative Intelligence - Noblesville, IN, USA
Feb 2025 - May 2025

SDE Teacher & Lab Assistant
DePauw University - Greencastle, IN, USA
Aug 2024 - Dec 2025

Apprentice
Tenzer Technology Center - Greencastle, IN, USA
Aug 2023 - Aug 2024

President, Co-Founder
Mubtada - Pakistan
Jun 2022 - May 2024

SDE Intern
Websitech Community Prvt. Limited - Remote
May 2022 - Aug 2022
My Projects
GTG App
Cross-platform iOS/Android app using Expo and React Native, serving 2,000+ campus users with Firebase authentication and real-time data sync achieving ~150ms response time.
View ProjectPortfolio Optimizer
Full-stack Markowitz-based stock/ETF recommendation system with interactive Plotly UI, achieving 15% lower volatility and 95% reduction in API calls through smart caching.
View ProjectDistributed Anomaly Detection
ML-powered cybersecurity system for IoT networks using novel charge-assignment algorithms, reducing false positive rates by 26% and improving detection accuracy by 40%.
View ProjectFace Recognition ML
Real-time face recognition system using Siamese Neural Networks with one-shot learning capability, trained on 176K+ images with 38.9M parameter architecture.
View Project