Projects & Research Work

This page highlights selected research projects, industrial systems, and open-source contributions spanning Explainable AI, Computer Vision, Anomaly Detection, and Industrial AI.

ADVIS-UniGra: RGB Anomaly Detection for Safe Human–Robot Collaboration

ADVIS-UniGra: RGB Anomaly Detection for Safe Human–Robot Collaboration EU Project 🇪🇺

RGB-based anomaly detection application for safety monitoring in collaborative robotics environments using synthetic industrial data.

Type: Research Application · Status: Published · Year: 2026

Project Page Code

Research Area: Computer Vision, Anomaly Detection, Explainable AI, Human-Robot Collaboration, Industrial Safety, Trustworthy AI

Technologies: Python, PyTorch, OpenCV, VAE-GAN, ROS2, Synthetic Data, Explainable AI, Threshold Calibration

AI on Edge Devices

AI on Edge Devices Research/Edge AI

Lightweight AI deployment on edge devices, including Raspberry Pi-based computer vision systems.

Type: Deployment Project · Status: Completed · Year: 2025

Project Page Code

Research Area: Edge AI, Computer Vision, Embedded AI

Technologies: Python, Raspberry Pi, TensorFlow Lite, OpenCV

Explainable Anomaly Detection

Explainable Anomaly Detection Explainable AI

A case study on building trust in anomaly detection systems using VAE-GAN models and explainable AI.

Type: Research Project · Status: Published · Year: 2024

Project Page Code

Research Area: Explainable AI, Anomaly Detection, Computer Vision

Technologies: Python, PyTorch, VAE-GAN, XAI

LIME Stratified Sampling

LIME Stratified Sampling Explainable AI

An improved LIME sampling strategy for generating more stable and reliable image explanations.

Type: Research Project · Status: Published · Year: 2024

Project Page Code Paper

Research Area: Explainable AI, Computer Vision, Image Explanations

Technologies: Python, LIME, Computer Vision, XAI

Applied and Freelance Research Projects

Applied and Freelance Research Projects Applied AI

Applied research and freelance projects in medical imaging, computer vision, machine learning, and intelligent decision systems.

Type: Applied Research · Status: Completed · Year: 2017–2022

Project Page GitHub Testimonials

Research Area: Medical Imaging, Computer Vision, Machine Learning

Technologies: MATLAB, Python, Deep Learning, Machine Learning