About Me
I am a Doctoral Researcher in Computer Science at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg.
My research focuses on AI-enabled software testing, including software testing agents, automated program repair, test evolution, and applications of large language models to software engineering.
I have research experience across software engineering, and applications of artificial intelligence. Before joining the University of Luxembourg, I worked as a Senior AI Research Assistant at Manchester Metropolitan University and as a Data Science Graduate Research Assistant at the University of Leeds.
I have published peer-reviewed research and completed more than 150 reviews for journals and conferences published by IEEE, ACM, Springer Nature, and Elsevier. I also received the UK Global Talent endorsement from Tech Nation.
Research Interests
- Software testing
- Automated program repair
- LLMs for software engineering
- Test evolution and maintenance
- AI Applications
Experience
Doctoral Researcher — University of Luxembourg
SnT, Luxembourg
May 2025 – Present
Conducting research on AI-enabled software testing, software testing agents, and applications of large language models to software engineering. My work focuses on developing and evaluating intelligent techniques for improving software quality and testing effectiveness.
Senior AI Research Assistant — Manchester Metropolitan University
Manchester, United Kingdom
July 2024 – April 2025
Collaborated with a multidisciplinary research team studying electromyography signals and MRI images. Developed analysis code for bioelectrical signals and medical images using MATLAB and Python and supported research into the relationship between muscle structure, function, and chronic pain.
Data Science Graduate Research Assistant — University of Leeds
Leeds, United Kingdom
January 2024 – December 2024
Contributed to a UKRI-funded research project in collaboration with Ocado and Marks & Spencer. Analysed eye-tracking and consumer-shopping data, including product choices, spending behaviour, visual attention, and interactions with product images and prices.
Technical Peer Reviewer
IEEE, ACM, Springer Nature, and Elsevier
June 2022 – Present
Completed more than 150 technical peer reviews for academic journals and conferences. Assessed research quality, methodology, technical correctness, presentation, reproducibility, and compliance with publication standards.
Academic Outreach Ambassador — Manchester Metropolitan University
Manchester, United Kingdom
September 2023 – January 2024
Represented the university and its Department of Computing at outreach events. Presented academic programmes to prospective students and external audiences and supported university open days and engagement activities.
Applied AI Research Assistant — Northeastern University
United States
June 2020 – September 2022
Contributed to applied machine learning and deep learning projects, primarily in computer vision, image processing, object detection, and data analysis. The work resulted in peer-reviewed journal and conference publications.
Teaching Assistant — Jundi-Shapur University of Technology
Iran
September 2020 – November 2021
Supported undergraduate teaching in artificial intelligence, computer vision, and related computing subjects. Explained technical concepts, assisted students with coursework, and supported practical learning activities.
Research Intern — Research and Technology Center
Iran
August 2020 – November 2020
Developed educational websites, contributed to research activities, and analysed online group and messaging data using Python-based tools.
Education
PhD in Computer Science
University of Luxembourg, Luxembourg
May 2025 – Present
- Research area: AI-enabled software testing
- Supervisor: Prof. Mike Papadakis
MSc in Artificial Intelligence
Manchester Metropolitan University, United Kingdom
September 2023 – November 2024
- Grade: Distinction
- GPA equivalent: 4.0/4.0
- Supervisor: Prof. Moi Hoon Yap
- Thesis: Hair Impact Analysis on Melanoma Classification Confidence in the ISIC Image Dataset
MSc in Software Engineering
Arvandan Institute of Higher Education, Iran
September 2022 – September 2023
- GPA: 19.05/20
BSc in Computer Engineering
Jundi-Shapur University of Technology, Iran
September 2017 – November 2021
- GPA last 2Yrs: 3.5/4.0
- Supervisor: Dr. Somaieh Amraee
- Thesis: Analysis of Deep Learning Methods Compared with Machine Learning Models for the Classification of Small Metal Objects
Selected Publications
Handwritten Logic Circuits Analysis Using the YOLO Network and a New Boundary Tracking Algorithm
IEEE Access, 2022
Analytical Study of Two Feature Extraction Methods in Comparison with Deep Learning Methods for Classification of Small Metal Objects
Visual Computing for Industry, Biomedicine, and Art, Springer Nature, 2022
Deep Learning Approaches for Driver Distraction Detection Systems
International Conference on Global Studies in Technology and Engineering Sciences
Computer Vision-Based Hand Gesture Recognition
International Conference on Modern Research in Electrical and Computer Engineering
The Application of Machine Learning in Medical Image Processing
International Conference on Modern Research in Electrical and Computer Engineering
Peer-Review Service
I have reviewed submissions for journals and venues including:
- ACM Transactions on Knowledge Discovery from Data
- ACM Transactions on Multimedia Computing, Communications, and Applications
- Elsevier Engineering Applications of Artificial Intelligence
- Elsevier Image and Vision Computing
- Springer Nature Applied Intelligence
- Springer Nature Multimedia Tools and Applications
- IEEE Transactions on Neural Networks and Learning Systems
- IEEE Access
Selected Projects
Automated Software Testing and Repair Agents
Research on agent-based software testing, automated program repair, test evolution, flaky test repair, and large language models for software engineering.
Handwritten Logic Circuit Analysis
Developed computer-vision methods for analysing handwritten logic circuits. Compared YOLO, Faster R-CNN, RetinaNet, and Detectron2 and developed a boundary-tracking method for interpreting circuit connections.
Small Metal Object Classification
Created and analysed datasets of small metal objects. Applied HOG and LBP feature extraction with k-nearest neighbours, support vector machines, and Naive Bayes, and compared these methods with deep-learning models.
Vehicle Speed Estimation
Developed a system using YOLO object detection, vehicle tracking, and perspective-transformation techniques to estimate vehicle speeds from road video footage.
Medical Image Classification and Segmentation
Worked on projects involving COVID-19 classification from chest X-rays, breast ultrasound image segmentation, brain tumour classification, MRI analysis, and melanoma classification.
Pose Estimation
Implemented human pose-estimation pipelines using MediaPipe and OpenPose to detect and connect body keypoints across video frames.
Face Detection and Facial Expression Analysis
Developed face-detection systems using YOLO and real-time facial-expression analysis using Haar cascades, VGG-Face, and DeepFace-based techniques.
Telegram Data Dashboard
Developed a Streamlit dashboard for storing, searching, and analysing Telegram messages using a structured database.
Technical Skills
- Python
- C/C++
- MATLAB
- Git and GitHub
- LaTeX
- HTML/CSS
- Machine/Deep learning
- Computer vision
- Data analysis
- Software testing
- Automated program repair
Profiles
Contact
You can contact me at m.a.charoosaei@gmail.com.