Muhammad Aqeel
Postdoctoral Research Fellow
Department of Engineering for Innovation Medicine · University of Verona, Italy
Anomaly detection·Unsupervised learning·Vision-language models·Generative models
Download CVMy research is centered on anomaly detection for industrial inspection, with a focus on unsupervised and zero-shot settings where labeled defect data is unavailable. Over time my work has expanded toward generative models and vision–language approaches, motivated by the need to handle data scarcity and improve generalization across unseen defect categories.
Recently I have also been exploring video understanding and multimodal summarization, though anomaly detection remains my primary focus. I completed my PhD at the University of Verona under Francesco Setti and Marco Cristani, and earned my Master's at Beijing University of Posts and Telecommunications under Xiaohong Liu.
News
Selected publications
Anomaly-Aware Vision-Language Adapters for Zero-Shot Anomaly Detection
ICIP 2026
Multimodal Abstractive Summarization of Instructional Videos with Vision-Language Models
ICPR 2026
Robust Anomaly Detection in Industrial Environments via Meta-Learning
ICCV 2025 Workshops (Oral)·PDF
Semantic Parsing for Aspect-Based Sentiment Analysis
IEEE Access 2025·PDF
Publications
See also Google Scholar for citation metrics.
2026
Anomaly-Aware Vision-Language Adapters for Zero-Shot Anomaly Detection
Multimodal Abstractive Summarization of Instructional Videos with Vision-Language Models
2025
Semantic Parsing for Aspect-Based Sentiment Analysis
A Contrastive Learning-Guided Confident Meta-learning for Zero Shot Anomaly Detection
Robust Anomaly Detection in Industrial Environments via Meta-Learning
Diffusion-Based Data Augmentation for Medical Image Segmentation
RoadFusion: Latent Diffusion Model for Pavement Defect Detection
ExDD: Explicit Dual Distribution Learning for Surface Defect Detection via Diffusion Synthesis
Latent Space Synergy: Text-Guided Data Augmentation for Direct Diffusion Biomedical Segmentation
Self-Supervised Iterative Refinement for Anomaly Detection in Industrial Quality Control
2024
Meta Learning-Driven Iterative Refinement for Robust Anomaly Detection in Industrial Inspection
Self-supervised Learning for Robust Surface Defect Detection
News
A timeline of recent updates, paper acceptances, talks, and milestones.
2026
2025
2024
2022
2019 – 2021
Grants
Funded research projects and scholarships.
PNRR PhD Scholarship
Italian Ministry of University and Research, via University of Verona
Role: PhD Fellow · National Recovery and Resilience Plan funding for doctoral research on industrial anomaly detection.
Mobility Research Grant
University of Ljubljana, Slovenia
Role: Visiting Researcher · Six-month research stay collaborating with Prof. Danijel Skočaj's group on zero-shot anomaly detection.
Chinese Government Scholarship (CSC)
China Scholarship Council, via Beijing University of Posts and Telecommunications
Role: Scholarship Recipient · Supported MSc research on natural language processing.
Career
Education
Ph.D. in Computer SciencePhD
Supervisors: Prof. Francesco Setti & Prof. Marco Cristani · Anomaly detection for industrial manufacturing
M.Sc. in Computer ScienceMSc
Beijing University of Posts and Telecommunications, China
Supervisor: Prof. Xiaohong Liu · Natural language processing and sentiment analysis
B.Sc. in Computer ScienceBSc
Experience
Postdoctoral Research FellowPostdoc
University of Verona, Italy
Visiting ResearcherVisiting
University of Ljubljana, Slovenia
Teaching AssistantTeaching
University of Verona, Italy
Computer Vision and Machine Learning, Department of Engineering for Innovation Medicine
Research AssistantResearch
Huazhong University of Science and Technology, Wuhan, China
Industry RolesIndustry
Pakistan
Software Quality Assurance Engineer at UIIT, Arid Agriculture University · Earlier, Software Developer at eConceptions (Pvt) Ltd.