My research interests lie at the intersection of Artificial Intelligence (AI), Computer Vision, and Biomedical Imaging, with a particular focus on leveraging deep learning and explainable AI techniques for real-world applications. My current work explores advanced ensemble learning and interpretability methods to enhance the reliability of AI systems in medical diagnostics, such as HER2 scoring in breast cancer.

Additionally, I am interested in affective computing, particularly in implicit emotion recognition through visual and physiological signals, combining EEG and imaging data. I am also expanding my scope to neurodegenerative disease analysis, especially in the context of ALS, where imaging modalities are employed for early and precise detection. My broader interests include generative AI, diffusion models, and the application of these technologies in creative media and personalized healthcare.

I am an innovative and dedicated computer engineer with over 15 years of academic and research experience in Artificial Intelligence, Computer Vision, and Biomedical Imaging. With a strong foundation in technical problem-solving and a passion for cutting-edge technologies, I have contributed to impactful projects ranging from point cloud processing and satellite image compression to cancer detection and augmented reality in education.

Currently serving as a Research Fellow at TU Dublin, I bring a global perspective to my work, having held research and teaching positions in Pakistan, Italy, and Germany. My professional journey is marked by interdisciplinary collaboration, high-impact publications, and leadership roles in academic quality enhancement and postgraduate advisement. I thrive in dynamic, research-driven environments where I can mentor students, innovate with emerging technologies, and contribute meaningfully to societal well-being through intelligent systems.

I have over 15 years of teaching experience, primarily at the University of Engineering & Technology (UET) Peshawar, where I served as a Lecturer in the Department of Computer Systems Engineering. During this time, I taught a variety of undergraduate and postgraduate courses, advised student batches, and supervised numerous final-year and graduate research projects.

In addition to teaching, I held several academic roles including Postgraduate Advisor, member of the Board of Studies, Industrial Advisory Board, Undergraduate Research Review Committee, and the Quality Enhancement Cell. I was also part of the SAR and IT/Data Management committees. My teaching approach is shaped by practical, hands-on learning, and I always aim to bridge the gap between theoretical concepts and real-world applications. My goal has been not only to educate but also to mentor and guide students toward academic and professional success.

My research work has resulted in numerous publications across reputable journals and international conferences. I have published extensively in the areas of image processing, computer vision, AI in healthcare, and point cloud denoising. My doctoral research at Politecnico di Torino led to key publications in IEEE Access and the Journal of Visual Communication and Image Representation, focusing on joint geometry and color denoising of 3D point clouds.

More recently, my work has extended to AI applications in medical diagnostics, including breast cancer and skin cancer detection using deep learning, as well as projects involving explainable AI and ensemble learning. I’ve also contributed book chapters on augmented reality in education and AIoT-based telehealth systems. In total, I have authored over 20 journal articles, book chapters, and conference papers, many of which are indexed in Scopus and IEEE Xplore.

Experienced computer engineer and academic with a strong background in AI, computer vision, and biomedical imaging. Currently a Research Fellow at TU Dublin, with over 15 years of teaching and research experience, including a long tenure at UET Peshawar.