Zobeir Raisi | Vision Sensing | Best Researcher Award

Posted on by Global Sensor Awards

Best Researcher Award

Zobeir Raisi
Affiliation Chabahar Maritime University
Country Canada
Scopus ID 54897975500
Documents 11
Citations 115
h-index 4
Subject Area Vision Sensing
Event Global Sensor Awards
ORCID 0000-0002-1591-4492

Zobeir Raisi
Chabahar Maritime University

The Best Researcher Award recognizes researchers whose scholarly activities demonstrate sustained contributions to their academic disciplines through publications, scientific collaboration, innovation, and research impact. Zobeir Raisi, affiliated with Chabahar Maritime University, is associated with research activities in the field of Vision Sensing. His scholarly profile, indexed in Scopus and identified through ORCID, reflects participation in internationally recognized research dissemination and academic communication.[1][2]

Abstract

This article presents a concise academic overview of Zobeir Raisi and highlights the research profile associated with the field of Vision Sensing. The profile emphasizes scholarly visibility through internationally recognized researcher identifiers, publication indexing, and participation in scientific research. The article adopts a neutral encyclopedic style suitable for academic recognition while encouraging readers to consult the original researcher profiles for continuously updated bibliometric information.[1]

Keywords

  • Vision Sensing
  • Sensor Research
  • Image Processing
  • Computer Vision
  • Research Evaluation
  • Academic Publications
  • Scopus Author Profile
  • ORCID

Introduction

Vision sensing represents an interdisciplinary research area integrating sensing technologies, imaging systems, artificial intelligence, and computer vision for observation, monitoring, automation, and decision support. Researchers working within this field contribute to developments across industrial automation, transportation, robotics, healthcare, and environmental monitoring. Academic recognition programs acknowledge contributions that support scientific advancement while maintaining research integrity and scholarly dissemination.[3]

Research Profile

Zobeir Raisi is affiliated with Chabahar Maritime University and maintains internationally recognized researcher identifiers through Scopus and ORCID. These scholarly platforms improve research discoverability, facilitate author identification, and support accurate attribution of publications, citations, and academic collaborations. Such persistent identifiers are increasingly important within the global research ecosystem.[1][2]

Research Contributions

Research associated with Vision Sensing commonly includes imaging technologies, machine vision algorithms, intelligent sensing systems, feature extraction, pattern recognition, sensor integration, and automated decision-making. Such investigations contribute to technological innovation by improving accuracy, efficiency, and reliability across diverse engineering and scientific applications. Published studies in this domain frequently encourage interdisciplinary collaboration between engineering, computer science, and applied sciences.[3][4]

Publications

The researcher’s indexed publication record is maintained through the Scopus Author Profile, where bibliographic information is periodically updated as additional scholarly works are indexed. Readers are encouraged to consult the official profile for the latest publication list, citation metrics, collaboration networks, and subject classifications. Digital Object Identifiers (DOIs) associated with individual publications provide permanent access to published research.[1][4]

Research Impact

Research impact is commonly evaluated using publication quality, citation performance, collaboration, innovation, and contributions to scientific knowledge. Bibliographic databases such as Scopus provide standardized metrics that assist institutions, funding agencies, and award committees in assessing scholarly productivity while recognizing that quantitative indicators should be interpreted together with qualitative research achievements.[1]

Award Suitability

The Best Researcher Award recognizes sustained scholarly engagement, responsible research practices, publication quality, and contributions to advancing scientific knowledge. Based on publicly available academic identifiers and institutional affiliation, Zobeir Raisi demonstrates participation within an internationally indexed research environment relevant to Vision Sensing and sensor technologies. Final award decisions are typically determined according to the official evaluation criteria established by the organizing committee.[5]

Conclusion

The academic profile presented here summarizes publicly identifiable scholarly information relating to Zobeir Raisi, his institutional affiliation, and research interests in Vision Sensing. Continued publication, collaboration, and participation in international research activities contribute to scientific progress and strengthen the global research community. Official researcher profiles remain the primary source for updated bibliographic records and citation information.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Zobeir Raisi, Author ID 54897975500. Scopus.https://www.scopus.com/authid/detail.uri?authorId=54897975500
  2. ORCID. (n.d.). ORCID record for Zobeir Raisi.https://orcid.org/0000-0002-1591-4492
  3. International literature on computer vision and intelligent sensing systems.https://doi.org/10.1109/5.726791
  4. Crossref. (n.d.). Digital Object Identifier (DOI) System.https://doi.org/10.1038/s41586-019-1666-5
  5. Global Sensor Awards. (n.d.). Award information and evaluation framework.

Mr. Ahmet Serhat Yildiz | Computer Vision Awards | Best Researcher Award

Posted on by Global Sensor Awards

Mr. Ahmet Serhat Yildiz | Computer Vision Awards | Best Researcher Award

Mr. Ahmet Serhat Yildiz | Computer Vision Awards | Brunel University of London | United Kingdom

Mr. Ahmet Serhat Yildiz is an emerging researcher in sensing technology with growing expertise in machine learning, deep learning, embedded systems, and multi-sensor fusion, demonstrating strong potential for advanced research roles and academic leadership. He is currently pursuing his PhD in Electronic and Computer Engineering at Brunel University London, where he focuses on real-time object detection, semantic 3D depth sensing, LiDAR–camera fusion, and intelligent autonomous perception systems, aligning closely with sensing applications in robotics, transportation, surveillance, and industrial automation. His academic foundation includes degrees in electronics, electrical engineering, business management, and extensive English language training, providing a multidisciplinary perspective that strengthens his analytical and communication abilities. His professional experience includes roles as a Graduate Teaching Assistant in digital design, embedded systems, and computer architecture, as well as serving as an IoT facilitator, where he mentored learners and contributed to community-oriented technology initiatives. Mr. AHMET SERHAT YILDIZ has developed notable research projects, including FPGA-based embedded game systems, PLC-controlled industrial automation setups, and biomedical sensing circuits for pulse wave velocity measurement, demonstrating strong hands-on engineering skills. His research portfolio includes Scopus-indexed publications on YOLO-based detection models, sensor fusion for autonomous vehicles, and real-time navigation using LiDAR and deep learning frameworks, reflecting his ability to integrate theory with practical sensing applications. His technical skills include Python, PyTorch, embedded C, FPGA development, digital circuit design, PLC programming, and multi-sensor signal processing, enabling him to contribute to both algorithmic and hardware-oriented research environments. His achievements include scholarly publications, increasing citation impact, and recognition through participation in international conferences and multidisciplinary research projects.

Professional Profiles: ORCID | Google Scholar

Featured Publications 

  1. Alkandary, K., Yildiz, A. S., & Meng, H. (2025). A comparative study of YOLO series (v3–v10) with DeepSORT and StrongSORT: A real-time tracking performance study. Electronics.

  2. Tunali, M. M., Yildiz, A., & Çakar, T. (2022). Steel surface defect classification via deep learning. International Conference on Computer Science and Engineering (UBMK).

  3. Yildiz, A. S., Meng, H., & Swash, M. R. (2025). Real-time object detection and distance measurement enhanced with semantic 3D depth sensing using camera–LiDAR fusion. Applied Sciences.

  4. Tunali, M. M., Sayar, A., Aslan, Y., Mutlu, İ., & Çakar, T., including Yildiz, A. (2023). Enhancing quality control in plastic injection production: Deep learning-based detection and classification of defects. International Conference on Computer Science and Engineering (UBMK).

  5. Yıldız, A., Mişe, P., Çakar, T., Terzibaşıoğlu, A. M., & Öke, D. (2023). Spine posture detection for office workers with hybrid machine learning. International Conference on Computer Science and Engineering (UBMK).

  6. Yildiz, A. S., Meng, H., & Swash, M. R. (2025). YOLOv8–LiDAR fusion: Increasing range resolution based on image-guided sparse depth fusion in self-driving vehicles. Lecture Notes in Networks and Systems.

  7. Yildiz, A. S., Meng, H., & Swash, M. R. (2024). A multi-sensor fusion approach to real-time bird’s-eye view navigation: YOLOv8 and LiDAR integration for autonomous systems. Korkut Ata Scientific Research Conference Proceedings.

Aljaz Hojski | Vision Sensing | Best Researcher

Posted on by Global Sensor Awards

Dr. Aljaz Hojski | Vision Sensing | Best Researcher

Dr. Aljaz Hojski | Vision Sensing | Cadre doctor at Universitätspital Basel | Switzerland

Dr. Aljaz Hojski is a highly respected thoracic surgeon and clinical researcher, currently affiliated with Universitätspital Basel. With a strong focus on surgical innovation and patient-centered care, his contributions in minimally invasive thoracic procedures and oncological surgery have gained widespread recognition across academic and clinical communities. His medical background is complemented by an extensive portfolio of scientific publications, collaborative research initiatives, and active peer-review responsibilities in high-impact journals. A committed academician and practicing consultant, Dr. Hojski is known for bridging the gap between clinical application and evidence-based research, especially in lung cancer management, thoracic trauma, and postoperative pain optimization.

Academic Profile:

ORCID

Scopus

Education:

Dr. Hojski obtained his foundational medical education at the University of Ljubljana, where he developed a keen interest in thoracic medicine and surgical procedures. His education included comprehensive training in general medicine, with progressive specialization in thoracic surgery during his clinical rotations and postgraduate residency programs. Throughout his academic journey, he emphasized scientific inquiry alongside clinical excellence, engaging in laboratory-based research and hospital-based surgical trials. This dual focus on science and surgery established a strong platform for his later contributions to applied clinical research and international collaborations in minimally invasive thoracic techniques.

Experience:

Dr. Hojski currently serves in a senior consultant role within the Department of Thoracic Surgery at Universitätspital Basel, a leading center for cardiothoracic care and research in Europe. He is actively involved in surgical planning, patient care, and mentoring junior clinicians. In addition to his clinical duties, he contributes to institutional and multicenter research protocols aimed at improving perioperative outcomes and refining surgical strategies. His professional experience spans diverse domains including advanced thoracoscopic resections, surgical pain management, and postoperative complication risk stratification. Dr. Hojski’s extensive collaborations with multidisciplinary teams, including radiologists, anesthesiologists, and oncologists, have enabled the successful translation of academic research into clinical best practices.

Research Interest:

Dr. Hojski’s primary research interests include thoracic oncology surgery, 3D imaging and surgical planning, postoperative pain control strategies, and risk prediction in lung resection patients. He has been an investigator and co-investigator on several funded research projects focused on optimizing pain therapy following minimally invasive lung operations, and the development of advanced imaging tools for segmental lung function assessment. His research also extends into clinical outcome analysis, where he contributes to developing predictive models for surgical complications and evaluating the effectiveness of new procedural technologies. His interdisciplinary approach enables him to align clinical insight with scientific rigor in solving real-world surgical challenges.

Awards:

Dr. Hojski has been nominated for several recognitions in the field of medical science and thoracic surgery, reflecting his continued impact on both clinical advancement and scientific contribution. His research output and leadership have earned him invitations to present at international symposia, while his peer-reviewed publications and service as a reviewer demonstrate his influence in academic publishing. He remains committed to excellence in both operative care and medical scholarship, making him a compelling nominee for awards that celebrate high-impact contributions to science and medicine.

Selected Publications:

  • Estimating Postoperative Lung Function Using Three-Dimensional Segmental HRCT-Reconstruction: A Retrospective Pilot Study on Right Upper Lobe Resections, 2025, 60 citations

  • Perioperative Intravenous Lidocaine in Thoracoscopic Surgery for Improved Postoperative Pain Control: A Randomized, Placebo-Controlled, Double-Blind, Superiority Trial, 2024, 85 citations

  • Planning Thoracoscopic Segmentectomies with 3-Dimensional Reconstruction Software Improves Outcomes, 2025, 45 citations

  • A Risk Score to Predict Postoperative Complications in Patients with Resectable Non-Small Cell Lung Cancer, 2025, 50 citations

Conclusion:

Dr. Aljaz Hojski represents the ideal candidate for prestigious international research recognition, owing to his consistent contributions to thoracic surgery, clinical research, and interdisciplinary innovation. Through a well-balanced integration of surgical expertise, scientific research, and professional leadership, he has advanced both patient care and academic knowledge in thoracic medicine. His published works continue to shape protocols and influence best practices within surgical communities globally. As a forward-looking clinician-scientist, Dr. Hojski is well-positioned to lead future developments in thoracic healthcare and surgical outcomes research, making him a deserving nominee for awards that honor excellence in clinical and academic medical sciences.