Dr. Zobeir Raisi | Deep Learning | Excellence in Research Award

Dr. Zobeir Raisi | Deep Learning | Excellence in Research Award 

Dr. Zobeir Raisi | Deep Learning | Chabahar Maritime University | Iran

Dr. Zobeir Raisi is a male expert in computer vision, machine learning, and deep learning, specializing in object detection, recognition, tracking, segmentation, 3D human pose estimation, and camera calibration, combining advanced theoretical knowledge with practical and applied research experience. He holds a Ph.D. in Systems Design Engineering from the University of Waterloo, Canada, and both M.E. and B.E. degrees in Electrical Engineering from the University of Sistan & Balouchestan, Iran, reflecting a strong academic foundation and interdisciplinary technical proficiency. Dr. Zobeir Raisi’s professional experience encompasses postdoctoral research focused on automating sports analytics using smartphone cameras, supervising master’s students in camera calibration projects with industry collaboration, and conducting Ph.D.-level research on transformer-based deep learning frameworks for arbitrary-shaped text detection and recognition in complex visual environments. He has contributed as a research assistant in computer vision and machine learning applications for automated assembly and anomaly detection systems, as well as serving as a lecturer and assistant professor at Chabahar Maritime University, teaching courses spanning digital image processing, digital systems, electrical circuits, computer architecture, microcontrollers, and electromagnetics, while mentoring undergraduate and graduate students and managing journal editorial processes.

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Featured Publications


Machine Learning Algorithms for Signal and Image Processing


– John Wiley & Sons, 2022 · 100+ Citations

Transformer-Based Text Detection in the Wild


– IEEE/CVF CVPR, 2021 · 74 Citations

2D Positional Embedding-Based Transformer for Scene Text Recognition


– Journal of Computational Vision and Imaging Systems, 2020 · 32 Citations

Dr. Cristian Dan Pavel | Deep Learning | Best Research Article Award

Dr. Cristian Dan Pavel | Deep Learning | Best Research Article Award 

Dr. Cristian Dan Pavel | Deep Learning | University of Medicine and Pharmacy Grigore T. Popa | Romania

Dr. Cristian Dan Pavel is an accomplished Gastroenterology Specialist and an emerging clinical researcher with a strong academic and professional background in digestive medicine and biomedical sciences. Currently serving at the Dimitrie Castroian Municipal Hospital in Huși, Romania, he brings extensive expertise in hepatology, gastrointestinal imaging, and endoscopic diagnostics. Dr. Cristian Dan Pavel is pursuing his Ph.D. in Histology at the “Grigore T. Popa” University of Medicine and Pharmacy, Iași, where his research focuses on the morphological and biochemical mechanisms underlying gastrointestinal and hepatic disorders. His doctoral work, under the supervision of Prof. Dr. Carmen Zamfir, integrates histological imaging and oxidative stress modeling, bridging fundamental pathology with clinical application. He holds an M.Sc. in Gastroenterology from the University of South Wales, UK, where his thesis explored the risk of hepatocellular carcinoma in patients with chronic hepatitis C treated with direct-acting antivirals. His academic training also includes a postgraduate course in gastroenterology and a Medical Doctor (MD) degree from the same Romanian institution. Professionally, Dr. Cristian Dan Pavel’s clinical journey spans roles as Resident Doctor in Gastroenterology at “Sf. Spiridon” County Clinical Emergency Hospital, Iași, and as a Specialist in Gastroenterology at Dimitrie Castroian Municipal Hospital, where he provides advanced endoscopic diagnostics and evidence-based patient management. His research interests lie in hepatology, antiviral therapy outcomes, oxidative stress in intestinal pathology, and biomedical imaging, often intersecting clinical medicine with computational and experimental analysis. Dr. Pavel has developed advanced research skills in gastrointestinal endoscopy, optical coherence tomography (OCT), histological data interpretation, and systematic review methodology, with publications indexed in Scopus and IEEE-linked medical journals. He has been an active participant and presenter at multiple national and international gastroenterology congresses, reflecting his commitment to scientific exchange and collaboration.

Professional Profiles: ORCID | Scopus 

Featured Publications 

  1. Pavel, C. D. (2024). Facial Anthropometric Assessment: Importance in Ophthalmology and Orthodontics. Citations: 33.

  2. Pavel, C. D. (2024). Variabilities in Retinal Hemodynamics Across the Menstrual Cycle in Healthy Women Identified Using Optical Coherence Tomography Angiography. Citations: 41.

  3. Pavel, C. D. (2023). Hybrid Deep Learning Models for Analyzing Histological Images of the Zebrafish Intestine Under Oxidative Stress. Citations: 29.

  4. Pavel, C. D. (2023). The Relevance of Experimental Models in Assessing the Impact of Oxidative Stress on Intestinal Pathology. Citations: 36.

  5. Pavel, C. D. (2022). Evaluating Fundoscopy as a Screening Tool for Optic Nerve Atrophy in Multiple Sclerosis: An Optical Coherence Tomography (OCT) Comparative Study. Citations: 42.

  6. Pavel, C. D. (2021). Vision and Life Quality: A Comparative Study on Students from Medical Universities. Citations: 27.

  7. Pavel, C. D. (2020). Computer Vision Syndrome: An Ophthalmic Pathology of the Modern Era. Citations: 39.