Pedro-Antonio Regidor | Vision Sensing | Excellence in Research Award

Excellence in Research Award

Pedro-Antonio Regidor
Affiliation Exeltis Europe & Global Projects; Women’s Health Specialist
Country Germany
Scopus ID 57212377610
Documents 70
Citations 1,126
h-index 21
Subject Area Gynecology, Obstetrics, Reproductive Medicine, Women’s Health, Vision Sensing
Event Global Sensor Awards
ORCID 0000-0002-9551-2847

Pedro-Antonio Regidor is a physician-scientist and specialist in gynecology, obstetrics, gynecological endocrinology, reproductive medicine, and gynecological oncology. His professional career spans clinical practice, academic research, surgical innovation, and pharmaceutical medical leadership. Through extensive contributions to women’s health research, reproductive endocrinology, endometriosis management, contraceptive technologies, and obstetric medicine, he has established a notable scholarly profile within international medical communities.[1]

Abstract

This article summarizes the academic and professional achievements of Pedro-Antonio Regidor, a specialist in women’s health sciences. His work integrates clinical gynecology, reproductive medicine, gynecological oncology, endocrine disorders, contraceptive technologies, and translational research. His scholarly output includes peer-reviewed publications addressing endometriosis, uterine fibroids, hormonal therapies, pregnancy outcomes, inflammatory pathways, and reproductive endocrinology.[2]

Keywords

Gynecology, Obstetrics, Reproductive Medicine, Endometriosis, Women’s Health, Hormonal Therapy, Gynecological Oncology, Contraception, Pregnancy Outcomes, Endocrinology, Clinical Research.

Introduction

The advancement of women’s healthcare requires interdisciplinary expertise combining clinical practice, surgery, endocrinology, and evidence-based medicine. Pedro-Antonio Regidor has contributed to these domains through decades of clinical leadership, academic engagement, and scientific publication. His research interests focus on improving reproductive health outcomes and expanding understanding of gynecological diseases through translational and clinical investigation.[1]

Research Profile

Dr. Regidor earned his medical degree and later completed a doctoral specialization in gynecology and obstetrics. Throughout his career, he has held appointments including assistant medical director, department chief, consultant physician, and medical director within academic hospitals and international healthcare organizations. His expertise spans gynecological oncology, reproductive endocrinology, obstetrics, perinatal medicine, breast health, and women’s hormonal therapies.[1]

Research Contributions

  • Investigation of endometriosis pathophysiology and treatment strategies.
  • Research on hormonal contraception and reproductive endocrinology.
  • Clinical studies involving dienogest-based therapeutic interventions.
  • Analysis of inflammatory mechanisms in uterine fibroids and reproductive disorders.
  • Evaluation of maternal health outcomes and pregnancy-related inflammatory conditions.
  • Contributions to gynecological oncology and surgical women’s healthcare.

Publications

Recent scholarly publications include investigations into probiotic supplementation in endometriosis, contraceptive safety evaluation, polycystic ovary syndrome-associated hirsutism, chronic inflammation in uterine myoma, omega-3 fatty acids in pregnancy outcomes, and coagulation parameters associated with hormonal contraceptive therapies. These works have appeared in internationally recognized journals such as European Journal of Contraception & Reproductive Health Care, BMC Women’s Health, EClinicalMedicine, Biomedicines, and Gynecological Endocrinology.[2]

Research Impact

The impact of Dr. Regidor’s work is reflected through sustained publication activity, international collaborations, translational clinical studies, and continuing engagement in women’s health innovation. His research supports evidence-based approaches for reproductive medicine and contributes to discussions regarding contraceptive safety, endocrine management, inflammatory gynecological disorders, and maternal health outcomes.[2]

Award Suitability

Based on his extensive clinical experience, leadership positions, multidisciplinary specialization, academic qualifications, surgical expertise, and scientific publications, Pedro-Antonio Regidor demonstrates strong alignment with international academic recognition programs focused on excellence in gynecology, reproductive medicine, women’s health research, and translational clinical science. His professional contributions illustrate sustained commitment to advancing healthcare knowledge and practice.[1]

Conclusion

Pedro-Antonio Regidor represents a distinguished profile within women’s health sciences through a combination of clinical excellence, academic scholarship, surgical expertise, and international research engagement. His body of work contributes to ongoing advances in reproductive medicine, gynecology, endocrinology, and maternal healthcare while supporting evidence-based medical practice across diverse healthcare settings.

References

  1. Professional curriculum vitae and academic profile of Pedro-Antonio Regidor, including medical qualifications, appointments, memberships, and clinical expertise.
  2. Regidor, P.A., et al. Recent publications in gynecology, reproductive medicine, endometriosis, contraception, and women’s health.
    https://doi.org/10.1080/13625187.2026.2644896
  3. Elsevier. (n.d.). Scopus author details: Pedro-Antonio Regidor, Author ID 57212377610.
    https://www.scopus.com/authid/detail.uri?authorId=57212377610

Assist. Prof. Dr. Hye-Youn Lim | Computer Vision | Excellence in Research Award

Assist. Prof. Dr. Hye-Youn Lim | Computer Vision | Excellence in Research Award

Assist. Prof. Dr. Hye-Youn Lim | Computer Vision | Dong-A University | South Korea

Assist. Prof. Dr Hye-Youn Lim is a distinguished researcher and academic in artificial intelligence, computer vision, and intelligent systems, serving in the Department of Electronics Engineering at Dong-A University, Republic of Korea. Hye-Youn Lim obtained her Ph.D. from a leading research university and has accumulated extensive professional experience, including leading national and international research projects and collaborating with multiple industry partners on AI-based technology applications. Her research interests focus on intelligent video analysis, visual recognition, and smart city applications, demonstrating her expertise in applying computational methods to real-world problems. Hye-Youn Lim possesses a diverse set of research skills, including deep learning model development, attention-driven network design, data preprocessing and augmentation strategies, and applied computer vision for automated systems. Her scholarly output includes more than 30 SCI- and Scopus-indexed journal articles, with verified metrics of 22 Scopus documents, over 100 citations, and a recorded h-index, reflecting both impact and consistency in high-quality research dissemination.

Citation Metrics (Scopus)

120

90

60

30

0

Citations
105

Documents
22

h-index
3

Citations
Documents
h-index

View Scopus Profile
View ORCID Profile

Featured Publications

Mr. Suresha R | Computer Vision Awards | Excellence in Research Award

Mr. Suresha R | Computer Vision Awards | Excellence in Research Award 

Mr. Suresha R | Computer Vision Awards | Amrita Vishwa Vidyapeetham | India

Mr. Suresha R. is a results-driven educator and technologist with over six years of combined experience in teaching computer science and academic leadership. He holds an M.Sc. in Computer Science and has qualified in UGC-NET and K-SET, while currently pursuing a Ph.D. Mr. Suresha R. has demonstrated expertise in curriculum design and research, particularly focusing on AI in autonomous solutions and computer vision applications. In his professional career, Mr. Suresha R. has served as an Assistant Professor at Amrita Vishwa Vidyapeetham, School of Computing, Mysuru Campus, and at SBRR Mahajana First Grade College, Mysuru, where he delivered advanced courses in Computer Vision, Digital Image Processing, Pattern Recognition, Computational Intelligence, Computer Graphics, Machine Learning, Exploratory Data Analysis, R Programming, Information Retrieval, Data Mining, Numerical Analysis, and Operations Research, consistently achieving high student satisfaction. His research interests encompass small traffic sign detection and recognition in challenging scenarios using computer vision and LiDAR-based techniques with ROS2 framework, deep learning-based vehicle detection and distance estimation for autonomous systems, motion blur image restoration, wild animal recognition through vocal analysis, and SVM-based medical image classification. Mr. Suresha . possesses strong research skills in Python, MATLAB, ROS2, machine learning, deep learning, image processing, and data analysis. He has successfully guided Bachelor’s and Master’s students in research projects, fostering innovation and academic growth. His academic contributions are recognized through multiple publications in prestigious journals and conferences, including IEEE Access, Procedia Computer Science, ICCCNT, CCEM, ICECAA, and INDIACom. Mr. Suresha . has a proven record of collaborating in interdisciplinary teams, effectively communicating complex technical concepts, and mentoring students to achieve excellence in research and practical applications. His dedication to lifelong learning and active engagement in both teaching and research demonstrates his commitment to advancing knowledge in computer science and autonomous systems. Throughout his career, Suresha  has received awards and recognitions for research excellence, contributing to the development of sustainable and intelligent solutions in the field of computer vision and AI. Overall, Mr. Suresha exemplifies a passionate and innovative professional, bridging theoretical foundations with applied research, and continues to make significant contributions to academia and technology

Professional Profiles: ORCID

Selected Publications 

  1. Suresha, R., Manohar, N., Ajay Kumar, G., & Singh, R. (2024). Recent advancement in small traffic sign detection: Approaches and dataset.

  2. Suresha, R., Manohar, N., & Jipeng, T. (2024). Two-stage traffic sign classification system.

  3. Sudharshan Duth, P., Manohar, N., Suresha, R., Priyanka, M., & Jipeng, T. (2024). Wild animal recognition: A vocal analysis.

  4. Suresha, R., Jayanth, R., & Shriharikoushik, M. A. (2023). Computer vision approach for motion blur image restoration system.

  5. Srinivasa, C., Suresha, R., Manohar, N., Dharun, G. K., Sheela, T., & Jipeng, T. (2023). Deep learning-based techniques for precise vehicle detection and distance estimation in autonomous systems.

  6. Suresha, R., Devika, K. M., & Prabhu, A. (2022). Support vector machine classifier based lung cancer recognition: A fusion approach.

Mr. Adrian Barglazan | Computer Vision | Best Researcher Award

Mr. Adrian Barglazan | Computer Vision | Best Researcher Award

Mr. Adrian Barglazan, University “Lucian Blaga” Sibiu, Romania

Adrian Barglazan is a Senior Software Engineer at Cognizant Softvision, based in Sibiu, Romania, with a strong focus on continuous learning and growth in software development. He holds a Bachelor’s and Master’s degree in Computer Science from Lucian Blaga University of Sibiu, where he is also pursuing a Ph.D. with a research focus on media forensics. With over 15 years of professional experience, Adrian has worked in various roles, including software development, team leadership, and teaching. His expertise spans Microsoft-related technologies, agile development, clean code principles, and design patterns. Throughout his career, he has contributed to projects in cloud ERP systems, pharmaceutical software, and ERP applications, working with technologies such as C#, ASP.NET, JavaScript, React, and Azure. In addition to his industry work, Adrian has been a teaching assistant at Lucian Blaga University of Sibiu since 2011, specializing in data compression and DirectX. His interests extend to computer vision and machine learning, reflecting his passion for innovative and high-quality software solutions

Professional Profile:

ORCID

Suitability for Best Researcher Award – Adrian Barglazan

Adrian Barglazan demonstrates strong expertise in software development, computer vision, and media forensics, with a balance of industry experience and academic involvement. His Ph.D. research in media forensics, combined with over a decade of teaching experience in data compression and image processing, positions him as a knowledgeable professional in his field. However, for a Best Researcher Award, factors such as high-impact publications, patents, funded research projects, and citations play a crucial role. While Adrian has valuable technical contributions, his eligibility for this award would be strengthened by more peer-reviewed research publications and recognized contributions to the scientific community. Therefore, he is a strong candidate for an innovation or industry-academic impact award but may need further academic credentials to be fully competitive for a Best Researcher Award.

🎓 Education:

  • PhD in Computer Science (2019 – Present) 📖🔍
    Lucian Blaga University of Sibiu – Focus on Media Forensics
  • Master’s Degree in Computer Science (2009 – 2011) 🎓
    Lucian Blaga University of Sibiu
  • Bachelor’s Degree in Computer Science (2005 – 2009) 🎓
    University “Lucian Blaga”, Faculty of Engineering “Hermann Oberth”, Sibiu

💼 Work Experience:

🔹 Senior Software Engineer – Cognizant Softvision (Sept 2020 – Present)
📍 Sibiu, Romania

  • Focus on Microsoft-related technologies, agile development, and clean code
  • Expertise in software architecture, development, testing, and mentoring

🔹 PhD Student & Teaching Assistant – Lucian Blaga University of Sibiu (Sept 2011 – Present)
📍 Sibiu County, Romania

  • Research in Media Forensics 🔍
  • Teaching Data Compression & DirectX to 4th-year students 🎓
  • Covers key algorithms like Shannon, Huffman, LZ77, JPEG, MPEG

🔹 Software Developer – Visma (Apr 2017 – Sept 2020)
📍 Sibiu County, Romania

  • Senior developer in cloud ERP Single Page Application (SPA) development ☁️💻
  • Technologies: C#, ASP.NET MVC, Azure SQL, React, TypeScript
  • Worked with Kanban methodology, CI/CD, and cross-country teams

🔹 Developer – iQuest Technologies (Sept 2011 – Apr 2017)
📍 Sibiu County, Romania

  • Lead developer in Pharma sector projects 💊
  • Software architecture, risk management, and recruitment 📋

🏆 Achievements, Awards & Honors:

🌟 PhD Researcher in Media Forensics 📸🔬
🌟 Senior Software Engineer with over 17 years of experience in the software industry 💻
🌟 Specializes in Microsoft technologies, Agile development, and Clean Code principles ⚡
🌟 Mentor & Teacher – educating future developers on Data Compression & DirectX 🎓
🌟 Experienced in cloud-based ERP systems, software architecture, and machine learning ☁️🤖
🌟 Contributor to recruitment & technical interviews in multiple companies 🏅

Publication Top Notes:

Wavelet Based Inpainting Detection

Enhanced Wavelet Scattering Network for Image Inpainting Detection

Lung Sounds Anomaly Detection with Respiratory Cycle Segmentation

Image Inpainting Forgery Detection: A Review

Image Inpainting Forgery Detection: A Review

Ms. Maryam Moshrefizadeh | Computer Vision Awards | Best Researcher Award

Ms. Maryam Moshrefizadeh | Computer Vision Awards | Best Researcher Award 

Ms. Maryam Moshrefizadeh, Siant Louis University, United States

Maryam Moshrefizadeh is a Ph.D. student in Computer Science at Saint Louis University, with previous experience as a Graduate Research Assistant at South Dakota State University. She holds a Master’s degree in Artificial Intelligence from Amirkabir University of Technology and a Bachelor’s degree in Computer Software Engineering from K. N. Toosi University of Technology, both in Tehran, Iran. Maryam’s research interests lie in computer vision, deep learning, and machine learning. Professionally, she has worked as an AI researcher and developer, including roles at DRNEXT.IR, Payesh24, and Cobenefit, where she contributed to the development of AI-driven platforms, machine learning models, and website functionality. She has a strong technical background in programming languages like Python, JavaScript, and C, as well as expertise in frameworks and tools like PyTorch, TensorFlow, Vue.js, and Docker. Maryam is fluent in English and Persian and is passionate about mountaineering, cycling, photography, and outdoor activities.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award

Maryam Moshrefizadeh is a promising and highly capable PhD student with extensive experience and research contributions in the field of Artificial Intelligence (AI), Machine Learning (ML), and Computer Vision. Her academic background, practical work experience, and emerging research output position her as an excellent candidate for the Best Researcher Award.

Education

🎓 Saint Louis University
Ph.D. | Graduate Research Assistant | Computer Science
📅 Jan 2024 ‑ Dec 2028 | St. Louis, MO, USA

🎓 South Dakota State University
Ph.D. | Graduate Research Assistant | Computer Science
📅 Aug 2022 ‑ Dec 2023 | Brookings, SD, USA

🎓 Amirkabir University of Technology (Polytechnic)
M.S. in Artificial Intelligence
📅 Jan 2014 ‑ Sept 2017 | Tehran, Iran

🎓 K. N. Toosi University of Technology
B.S. in Computer Software Engineering
📅 Sept 2009 ‑ Aug 2013 | Tehran, Iran

Work Experience

💼 DrNext.ir | Developer and AI Researcher
📅 Nov 2020 – Present
• Developed prescription writing notepad allowing doctors to type or use a pen 🖊️
• Implemented features for appointment scheduling and clinic reception handling 🗓️
• Worked in an agile team with Kanban, Scrum, Jira, and Git 🔧

💼 Payesh24 | AI Engineer
📅 Nov 2017 – Jul 2020
• Researched and implemented various AI algorithms and machine learning models 🤖
• Worked with supervised and unsupervised learning algorithms such as SVM and KNN 📊

💼 BeFine | Developer
📅 Apr 2006 – Feb 2009
• Developed and maintained website for diabetic products and information 💻
• Shared health tips and updates on diabetes 🩺

💼 Cobenefit Developer | Remote
📅 Oct 2021 – Present
• Develop and maintain websites using Vue.js, ES6, HTML5, CSS3, and SASS 🌐

Research Interests

🔍 Computer Vision | 🤖 Deep Learning | 📚 Machine Learning

Publication Top Notes

EC-WAMI: Event Camera-Based Pose Optimization in Remote Sensing and Wide-Area Motion Imagery

Multimodal Fusion of Heterogeneous Representations for Anomaly Classification in Satellite Imagery