AbdulManan
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Abdul Manan | CS Undergrad @ NUST

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About Me - Built To Ship!

Computer Science undergrad at NUST (Class of 2027) focused on Machine Learning, Computer Vision, and production AI systems. I turn research ideas into working software — from GPU-accelerated classical ML pipelines to clinical tools and agentic RAG platforms.

I've shipped real outcomes: a nuclei segmentation pipeline hitting 0.8802 Macro-F1 on PanNuke, a live clinical workflow product (Cepharix), computer vision work at Infix Systems, and medical imaging research at MachVIS Lab. My stack centers on Python, FastAPI, AWS, and modern ML tooling — with a bias toward measurable results, clean engineering, and systems that hold up beyond demos.

Open to ML Engineering, Computer Vision, and Applied AI internships or full-time roles where I can own hard problems end-to-end and deliver impact quickly.


Work Experience - Professional Journey!


01
Infix Systems

Computer Vision Intern

• Contributed to early-stage development of a vehicle speed estimation and license plate recognition system.

• Annotated industrial safety data using Labelme.

• Built backend for a Windows virtual camera app, streaming real-time UDP video via FFmpeg as a low-latency system-level source for Zoom, Teams, and Meet.

JUN 2025 – JUL 2025
02
MachVIS Lab

Research Intern — Cephalometric Retrospective

• Learned the complete research workflow, including literature review and identifying research gaps.

• Executed research-driven data workflows including academic paper retrieval, exploratory data analysis, and structured documentation using spreadsheets for literature synthesis.

JUN 2024 – AUG 2024

Projects Showcase - What I've Built!


2025–PRESENT
Fullstack SaaS

FreightFlow — ELD Trucking Platform

Built a production-grade fullstack trucking platform from scratch — featuring FMCSA-compliant ELD log generation, real-time route calculation via OSRM, HOS (Hours of Service) violation detection, interactive map with Leaflet, SVG log sheets, JWT authentication, trip saving, and a fully responsive glassmorphic UI. Deployed on Railway (Django) + Vercel (React) + Supabase (PostgreSQL).

View Live GitHub
2025–PRESENT
Upcoming SaaS

AI Research Analysis Platform

Building an upcoming multi-tenant SaaS platform that helps researchers extract citation-grounded insights from scientific literature — turning dense PDFs into structured, trustworthy evidence for faster literature review.

View Live GitHub
2025
Classical ML

HandCraft-Path: Nuclei Segmentation

Built a GPU-accelerated classical ML pipeline segmenting nuclei on 7,904 PanNuke images using 93 handcrafted features — with memmap streaming, Active Boundary Mining, GPU RFE (12× speedup), and an RF/XGBoost/LightGBM ensemble achieving 0.8802 Macro-F1.

View Live GitHub
2024
RAG System

Scalable Academic Policy QA

Built a RAG system to answer academic policy queries from institutional documents — with ingestion, chunking, embedding, and retrieval pipeline for accurate context, integrated with LLMs to reduce hallucinations and ground responses.

View Live GitHub
2024
Clinical Web App

Cepharix

Built a full clinical workflow prototype covering patient/case management, X-ray upload, AI landmark detection, interactive landmark refinement, and Ricketts cephalometric analysis with report generation — including drag-and-drop landmark editor with undo/redo.

View Live GitHub

Technical Skills - Core Expertise!

Python
C++
C
Java
JavaScript
TypeScript
SQL
React.js
Next.js
Tailwind CSS
HTML
CSS
FastAPI
LangChain
TensorFlow
OpenCV
Qdrant
PostgreSQL
Git
GitHub
Docker
AWS
VS Code
Linux
Jupyter
Vercel

Connect With Me - Across The Web!

Abdul Manan

@mananbyte

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Cepharix

Live Demo

You can explore further by clicking on any of the profile cards above!


Get In Touch - Ask Me Anything!

Ready to collaborate or have a project in mind?
I'm always open to new opportunities and interesting conversations.


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My Resume - On Paper!