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I build production AI systems — RAG chatbots, computer vision pipelines, and full-stack apps that actually ship. Obsessed with elegant code, fast UX, and models that hold up in production.
I sit at the intersection of AI research and shipping software. I love clean code, clean models, and clean interfaces — and the work it takes to make all three coexist.
Bio
I'm a Computer Science student and AI engineer building production-grade systems with deep learning, computer vision, and modern web stacks.
My current obsessions: retrieval-augmented generation, real-time vision pipelines, and shipping AI features that don't feel like demos. I care about latency, evaluation, and user-facing polish — not just notebooks.
Retrieval-augmented systems with vector search, grounded reasoning, and clean conversational UX.
Object detection, tracking, stereo vision, and depth estimation — from prototype to production.
Next.js + Node.js apps with secure auth, real-time UI, and scalable APIs.
High-performance computation with Cilk, multi-threading, and benchmarked scaling.
Transformers, ViTs, GANs — and the glue code that makes them useful.
Glassmorphism, fluid motion, accessible interactions — the front end models deserve.
A modern, opinionated stack covering AI, full-stack web, and developer experience.
Crafting fast, accessible, beautiful UIs.
APIs, services, and server-side logic.
Vision, language, and learning systems.
Relational, document, and vector stores.
Workflow, DevOps, and developer experience.
Freelance work, research, and projects that taught me what shipping actually looks like.
Independent
Building production AI features — RAG chatbots, vector search, and full-stack web apps — for early-stage startups and individual founders.
Independent Research
Stereo vision pipelines, depth estimation, and landmark detection. Explored Vision Transformers and GAN-based augmentation strategies.
Personal & Academic Projects
Shipped voting platforms, CRUD apps, and authenticated web tools. Strong focus on clean APIs and server-rendered UX.
University
Built and benchmarked parallel data structures with OpenCilk. Studied work–span analysis and scalability trade-offs.
Formal study in computer science, with deep focus on AI and web development.
COMSATS University
2022 — 2026
Focused on artificial intelligence and full-stack web development. Strong foundation in algorithms, systems, and applied ML.
Relevant coursework
Auto-fetched repositories, stars, and recent activity from the GitHub API.
A few learning milestones and recognitions along the way.
Deep Learning Specialization
DeepLearning.AI · 2024
Machine Learning
Stanford / Coursera · 2024
Full Stack Web Development
Self-paced · 2023
Computer Vision Nanodegree
Udacity · 2024
Open Source Contributor
2024Active contributor to AI / web open-source projects.
Hackathon Finalist
2024Top 10 finalist in a national AI hackathon.
Top of Class
2023Consistently top performer in CS coursework.
"Shipped a production RAG chatbot in two weeks. The retrieval quality and UX polish were genuinely impressive."
Sarah Chen
Founder · VectorLabs
Long-form posts on AI engineering, computer vision, and frontend craft. Coming soon.
What I learned shipping a production RAG system — retrieval, evaluation, latency, and the pieces no tutorial talks about.
End-to-end notes on building a stereo depth pipeline that actually works outside a lab.
Streaming, optimistic UI, and the design decisions behind interfaces that hide latency.
Open to freelance, full-time, and research collaborations. Drop a message or reach out directly.