Abdul Rehman Naseer — Data Scientist & AI Researcher
Motivated Data Scientist, AI researcher, and Lab Instructor at GIFT University specializing in computer vision, multimodal learning, anomaly detection, and retrieval-augmented generation (RAG). Co-author of research accepted in leading venues including IEEE TPAMI, ECCV, IEEE Sensors Journal, and DICTA. Experienced in developing PyTorch-based research systems and end-to-end AI applications involving website crawling, hybrid information retrieval, grounded question answering, and interactive user interfaces.
My research interests focus on Machine Learning and Computer Vision, specifically Industrial Anomaly Detection, Multimodal Sensor Fusion, Topological Deep Learning, and Predictive Fault Diagnosis. I secured 1st Position in my academic cohort during my studies.
You can find my publications on my Google Scholar profile.
🔥 News
- 2026.01: 🎉 IEEE TPAMI accepted, (Learning Topology-Aware Representations via Test-Time Adaptation for Anomaly Segmentation).
- 2026.01: 🎉 ECCV 2026 accepted, (Learning Structurally Consistent Representations for Multi-View Radar Semantic Segmentation).
- 2026.01: 🎉 IEEE Sensors Journal accepted, (Hypergraph Contrastive Sensor Fusion for Multimodal Fault Diagnosis in Induction Motors).
- 2025.12: 🎉 DICTA 2025 accepted, (2D-3D Feature Fusion via Cross-Modal Latent Synthesis and Attention-Guided Restoration for Industrial Anomaly Detection).
- 2025.10: 💼 Appointed as Lab Instructor at Department of Computer Science, GIFT University.
📝 Publications
Learning Topology-Aware Representations via Test-Time Adaptation for Anomaly Segmentation
Ali Zia, Usman Ali, Abdul Rehman, Umer Ramzan, Kang Han, Muhammad Faheem, Shahnawaz Qureshi, and Wei Xiang
Learning Structurally Consistent Representations for Multi-View Radar Semantic Segmentation
Ali Zia, Muhammad Umer Ramzan, Abdelwahed Khamis, Usman Ali, and Abdul Rehman
Hypergraph Contrastive Sensor Fusion for Multimodal Fault Diagnosis in Induction Motors
Usman Ali, Ali Zia, Waqas Ali, Umer Ramzan, Abdul Rehman, Muhammad Tayyab Chaudhry, Wei Xiang
Usman Ali, Ali Zia, Abdul Rehman, Umer Ramzan, Zohaib Hassan, Talha Sattar, Jing Wang, Wei Xiang
📬 Manuscripts Under Review
- Anomaly Segmentation: Topology-Aware Optimal Transport for Source-Free Test-Time Adaptation in Anomaly Segmentation
Ali Zia, Usman Ali, Abdelwahed Khamis, Muhammad Umer Ramzan, Abdul Rehman, and Wei Xiang. - Radar Segmentation: TopoRadar: Topology-Aware Multi-View Radar Semantic Segmentation
Ali Zia, Muhammad Umer Ramzan, Usman Ali, Abdul Rehman, and Abdelwahed Khamis. - Object Detection: Residual Object Recovery via Topology-Guided Multimodal Transport for Training-Free Open-Vocabulary Detection
Ali Zia, Usman Ali, Muhammad Umer Ramzan, Abdul Rehman, Shahnawaz Qureshi, and Wei Xiang.
🏫 Experience
- Lab Instructor (2025 – Present)
Department of Computer Science, GIFT University, Gujranwala, Pakistan- Deliver laboratory instruction for Artificial Intelligence, Data Mining, Data Visualization, and Introduction to Data Science.
- Guide students in implementing machine-learning workflows, data-analysis techniques, visualization methods, and programming assignments.
- Support laboratory assessments, debugging activities, and the evaluation of student projects.
- Conduct collaborative research in computer vision, multimodal learning, anomaly detection, and semantic segmentation.
- Contribute to literature reviews, dataset preparation, ablation studies, result analysis, and the preparation of manuscripts.
🛠️ Technical Skills
Programming
Python, R, C++, Java
Machine Learning
PyTorch, TensorFlow, scikit-learn, CNNs, representation learning, multimodal learning
Generative AI
Retrieval-augmented generation (RAG), hybrid retrieval, vector search, keyword search, grounded QA, prompt engineering
Computer Vision
Image classification, anomaly detection, semantic segmentation, feature fusion, attention mechanisms
Data & Tools
NumPy, pandas, Jupyter Notebook, Git, GitHub, LaTeX, Markdown
Research Methods
Test-time adaptation, optimal transport, topological deep learning, unsupervised learning, feature alignment
🎖️ Honors and Awards
- 2022: Secured 1st Position in the BS Data Science program academic cohort during the Spring 2022 semester at GIFT University.
- Oct 2023: Introduction to Data Science in Python, University of Michigan (via Coursera).
- Sept 2023: What Is Data Science?, IBM (via Coursera).
- Aug 2023: Python for Data Science, AI & Development, IBM (via Coursera).
📖 Education
- 2021.12 – 2025.10: Bachelor of Science in Data Science, GIFT University, Gujranwala, Pakistan.
CGPA: 3.53/4.00
Selected Coursework: Deep Learning, Machine Learning, Computer Vision, Data Mining, Big Data Analytics, Data Warehousing, Applications of Data Science.
Undergraduate Thesis: 2D-3D Feature Fusion via Cross-Modal Latent Synthesis and Attention-Guided Restoration for Industrial Anomaly Detection (accepted at DICTA 2025).