
Syed Muhammad Hassaan
AI Engineer.
Social links
Overview
GitHub contributions
Experience
Global Health
CurrentLead Software Engineer
- Employment Period
- 12.2025—
- Duration
- 1y
Dublin, Ireland (Remote)
I lead engineering on a telehealth platform that connects patients with licensed clinicians in six countries.
- Rebuilt the platform for 60+ clinicians, 210 services, 1,200+ patients and 1,400+ appointments
- Shipped multilingual journeys across Ireland, Portugal, Spain, Czechia, Romania and Brazil
- Cut the same-day GP booking journey from 5 steps to 3
- Automated bookings, clinician assignment and documents: 86.5% of bookings need no admin touch
- Ran 4,500+ automation executions in 90 days at a 0.4% failure rate
- Implemented PHI controls, encryption, consent and role-based access under GDPR and LGPD
- TypeScript
- PostgreSQL
- Payments
- Automation
- GDPR/LGPD
Endifaa
Full-Stack Developer
- Employment Period
- 10.2025—06.2026
- Duration
- 9m
Saudi Arabia (Remote)
Built and maintained the Endifaa sports-academy platform.
- Multi-portal architecture for users, academies and admins, with role-based access
- Billing: subscriptions, invoices, cart, checkout and payment logic
- Bilingual English/Arabic with RTL and LTR support
- Production readiness with Docker, secure API configuration and PostgreSQL
- React
- TypeScript
- RTK Query
- Django/DRF
- PostgreSQL
- Docker
Part-time & founding roles
Jordy
CurrentCo-Founder
- Employment Period
- 03.2026—
- Duration
- 9m
Dubai, UAE (Hybrid)
Co-building an AI outbound sales platform that finds prospects, researches them, and runs personalised campaigns.
- React
- TypeScript
- LLMs
- Automation
- Analytics
Aertonic
CurrentFounding Engineer
- Employment Period
- 11.2025—
- Duration
- 1y 1m
Dubai, UAE (Remote)
Building the core product from the ground up and shaping its architecture as an early team member.
- TypeScript
- AI
- Product Engineering
Zao Fi
CurrentFounding Engineer
- Employment Period
- 2025—
Karachi, Pakistan (Startup)
A stock AI that I build with friends. It watches what whales, insiders and Congress are buying, and turns it into one 0–100 conviction score with the reasons in plain English.
- AI
- Market Data
- Explainable Scores
Clients(12 countries)
Live sites(12)
Websites for clients
Open source(3)
lumen (opens in a new tab)
Brxerq/lumen
Something happens on your computer, the devices around you react. An AI coding agent finishes, a build fails or a deploy lands, and your RGB keyboard flashes, your smart lights pulse, your screen edge glows, or you get a notification and a sound. A status tab at the top of the screen shows every open Claude or Codex tab with its activity, context use and usage limits. You set it up in a visual WHEN/THEN rule builder, and it runs on Windows, macOS and Linux with no accounts, no cloud and no telemetry.
- Python
claude-cockpit (opens in a new tab)
Brxerq/claude-cockpit
Instruments and controls for Claude Code. Live progress bars come from Claude’s own todo list at zero extra tokens, and a router runs quick, normal and hard prompts on the model and effort you pick. A cache meter counts down to the moment the prompt cache expires and can keep it warm. Near the compaction point, Claude chooses to compact the conversation or to write a handoff for a new session.
- TypeScript
Super-Market Shelves Detection (opens in a new tab)
Brxerq/Super-Market_Shelves_Detection_Object-Detection
The training code, annotated datasets and models behind the shelf-monitoring demo: it finds empty and misaligned spaces on supermarket shelves with SSD MobileNet V2 and transfer learning. Nine models were tested, three SSD MobileNet V2 variants on three datasets (empty, misaligned and both). SSD MobileNet V2 FPNLite 640x640 scored best on empty shelves.
- Jupyter Notebook
AI demos(6)
Shelf monitoring (opens in a new tab)
Hugging Face Space · Retail computer vision
Real-time out-of-stock and misalignment detection for supermarket shelves: SSD MobileNet V2 FPNLite with transfer learning and focal loss, trained on 1,000 annotated shelf images. The demo runs three TensorFlow Lite models (both classes, empty only, misalignment only) on CPU with LiteRT. Upload a shelf photo or a video, and it draws a box on each problem and counts them per class.
- TensorFlow
- SSD MobileNet V2
- Gradio
Face attendance + anti-spoofing (opens in a new tab)
Hugging Face Space · Multi-layer liveness check
A liveness check for student attendance: the webcam must show a live person before attendance is marked. It counts 3 slow blinks with dlib face landmarks, checks for one shown hand with MediaPipe, and runs an LBP texture check on the face. YOLOv4 blocks attendance when a phone is in view, such as a photo or video replayed on a phone. The web app saves no images.
- OpenCV
- Dlib
- YOLOv4
- MediaPipe
anti_spoofing (opens in a new tab)
Hugging Face Model · MIT licence
The real-time face recognition and anti-spoofing system behind the attendance demo. OpenCV, dlib and MediaPipe detect faces, analyse eye blinks and check liveness through texture analysis and gesture detection. YOLOv4 detects smartphones during attendance capture. Made for attendance in educational and professional environments.
- OpenCV
- Dlib
- MediaPipe
- YOLOv4
Stack
- Python
- TypeScript
- C++
- Dart
- TensorFlow
- PyTorch
- OpenCV
- OpenAI API
- LLMs / NLP
- React
- Next.js
- Django / DRF
- Flutter
- PostgreSQL
- MySQL
- FastAPI
- RabbitMQ
- Docker
- AWS
- Vercel
- Railway
- Git
- Claude
- Codex
- Antigravity
- T3 Code
Education
Certifications
Getting Started with AI on Jetson Nano
NVIDIA · 08.2025
Building RAG Agents with LLMs
NVIDIA · 08.2025
Fundamentals of Digital Marketing
Google Digital Garage · 07.2022
Cisco Certified Network Associate (CCNA)
Cisco · 11.2021
Testimonials(5)
I have worked closely with Syed on our multi-market healthcare platform, providing product and business guidance throughout the project. Syed took full ownership of the technical development, delivering the complete patient booking journey, Stripe payment integration, and dedicated portals for administrators, patients, and doctors. What stood out most was the care he gave to healthcare-specific requirements, including patient data encryption, consent workflows, and GDPR and LGPD compliance. He is dependable, thoughtful, and capable of managing complex projects from start to finish. I would highly recommend him to anyone looking for a skilled and responsible software engineer.
Contact
Karachi, Pakistan · UTC+5








