HOSAM ZOLFNOON
ML Engineer &
Applied AI Developer
based in Europe
Machine Learning Engineer with expertise in computer vision, real-time systems, LLMs, and cloud-native tools. I build practical, intelligent solutions, from facial expression recognition to educational apps, focused on clear design and real-world impact.
“ML solutions should be clear, scalable, and designed for impact, not just performance.”
Expertise
I design and develop intelligent systems that merge real-time performance with practical impact. My focus is on machine learning solutions that enhance human interaction, automate insights, and operate reliably in real-world conditions.
Machine Learning & AI
Designing models that go beyond accuracy—prioritizing usability, interpretability, and deployment. From facial expression recognition to physiological signal analysis, I transform data into meaningful insights for clinicians and end-users.
Real-Time Systems
Building low-latency applications with WebRTC, WebSocket, and optimized pipelines. I specialize in making AI run seamlessly in real time, whether through emotion detection in browsers or contactless health monitoring across devices.
Full-Stack Deployment
Delivering end-to-end solutions from backend APIs to containerized infrastructures. Using Docker, Kubernetes, and modern MLOps, I create scalable platforms that are easy to deploy, maintain, and adapt to evolving requirements.
Portfolio
Welcome to my portfolio—a collection of projects where I apply machine learning, real-time systems, and thoughtful engineering to address real-world challenges. My work spans domains like telehealth, education, and emotion-aware interfaces, always guided by usability, ethics, and technical precision.
From electronic health records for low-resource clinics to facial expression recognition in remote therapy, contactless heart rate monitoring, and interactive AI learning tools, each project reflects a commitment to building intelligent systems that are both effective and human-centered. I invite you to explore the work, the thinking behind it, and the impact each solution aims to create.
Machine Learning · 2024/2022
1 of 4 Case Studies
EHR – AI-Enabled Electronic Health Records Platform
A modular EHR system for charity health institutes with a MySQL + Flask backend and Streamlit frontend. AI modules (Scikit-learn, TensorFlow, Hugging Face) flag vital anomalies, extract identity and health indicators, and auto-generate reports (Docx → PDF → Email). With offline-sync and multilingual support, it improves efficiency in clinics and outreach programs.
Machine Learning · 2024/2022
2 of 4 Case Studies
FER – Facial Expression Recognition for Teletherapy
FER is a real-time machine learning system that aids online therapy by detecting patient emotions through facial landmarks and TensorFlow models. It uses WebRTC for live video, includes consent-based privacy measures, and integrates smoothly into virtual mental health sessions.
Machine Learning · 2024/2022
3 of 4 Case Studies
BPM – Contactless Heart Rate Monitoring for Elder Care
BPM is a real-time, contact-free system that estimates heart rate by analyzing facial landmark movements in live video. Designed for retirement homes, it replaces wearables with passive monitoring, detects cardiac anomalies, and streams BPM data via WebSocket in under a second to provide timely alerts to caregivers.
Machine Learning 2025/2023
4 of 4 Case Studies
HPO – Interactive AI Learning Portal
HPO is a browser-based platform that helps students learn deep learning through hands-on experimentation. Users can upload datasets, configure neural networks, and see how hyperparameters affect results in real time. Built with TensorFlow, Docker, and Kubernetes, it supports responsive training even in low-resource settings, making ML education more accessible and practical.
Learning Through Building: My Machine Learning Journey
As a Machine Learning Engineer, I create educational and practical AI systems that simplify complex concepts. My projects focus on real-time applications and hands-on learning. This blog shares insights, tools, and lessons to help others apply machine learning with clarity and confidence.
Here you’ll find technical walkthroughs, coding strategies, and deployment tips for real-world AI. Whether you’re new to neural networks or refining your models, this space offers practical guidance. Join me in exploring the challenges and creativity behind building impactful machine learning solutions.
Let’s Connect
Are you working on a project that bridges machine learning, real-time systems, or digital health?
Whether you’re building something innovative, looking for a technical collaborator, or just want to exchange ideas, I’d love to hear from you.
Feel free to reach out for a chat about projects, collaborations, or research.
Email me at: contact@hosamzolfonoon.pt
Let’s build technology that truly makes a difference.
