RABAH MOUISSAT

Programmed FANUC welding robots, transitioning from simulation in RoboGuide to live production environments. Performed maintenance and troubleshooting to ensure optimal robot performance and minimize downtime. Developed a Hikrobot camera–based computer vision system for orientation detection at 90° and 145° in ведро (bucket), operating in real time on a conveyor line. Integrated vision system with PLC for synchronized control and automated decision-making.

Russian startup

Working with children and refugees from Palestine, Afghanistan, Syria, Iraq, Yemen, and Russia at the Russian Red Cross.

I developed an video analysis system for detecting defects in tiles, bricks, and panels on the production line. The system identified cracks, chips, color mismatches, and geometric distortions. I installed high-quality cameras on the conveyor, implemented real-time image processing with YOLOv8, ResNet, and generated reports showing defect types, timestamps, and defect percentages. The system achieved 95% accuracy and processed images in ≤ 0.5 sec per frame. I built an NLP-based system to classify and respond to customer queries via chat, email, and phone. It categorized requests (delivery, defects, returns, consultations), provided automated responses, and recognized user intent. I used BERT, T5, developed the system in Russian, and integrated it with AmoCRM to escalate complex cases. I created a recommendation engine for an online store, analyzing purchase history, product views, and demographics. It provided cross-sell and up-sell suggestions and displayed recommendation widgets on the homepage and shopping cart. I implemented Collaborative Filtering, Neural Collaborative Filtering with TensorFlow Recommenders and stored data in PostgreSQL. I developed a 3-month demand forecasting model using Facebook Prophet, LSTM (PyTorch). It analyzed sales, seasonality, promotions, and competitors, adjusting for anomalies like discount-driven demand spikes. Forecasts were visualized as demand graphs for each warehouse. I built a GPT-4-based system that generated 200–400 character product descriptions with SEO optimization. I also used DALL·E for image generation. Technical Stack : Backend: Python (FastAPI, Flask) Frontend: React.js Deployment: Docker + Kubernetes Hosting: Yandex.Cloud / AWS Database: PostgreSQL Web Scraping Using BeautifulSoup, Requests, and Selenium

Working on FANUC ,Kuka robotics and computer vision for robotic tasks.

Experienced Nursing Assistant skilled in radiology, MRI, and scanner operations, with hands-on expertise in emergency care and surgical assistance. Proficient in multitasking in high-pressure environments, providing compassionate patient care, and supporting medical teams in diverse clinical settings.

Skilled in automation systems design, PLC programming, Python scripting, industrial networking, and SCADA systems. Proficient in troubleshooting, process optimization, and collaborative problem-solving.

Experienced in identifying and preventing website defacement, vulnerability testing, and penetration testing. Skilled in web application security tools, risk assessment, and incident response. Proficient in OWASP standards and ethical hacking techniques.

"Create engaging videos exploring ethical hacking, the mechanics of spamming, and comprehensive tutorials on utilizing Kali Linux."