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

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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

Dr. Kuai Zhou | Computer Vision | Young Researcher Award

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Dr. Kuai Zhou | Computer Vision | Young Researcher Award 

Dr. Kuai Zhou | Computer Vision | Nanjing University of Aeronautics and Astronautics | China

Dr. Kuai Zhou is a dedicated Lecturer at the School of Aeronautical Engineering, Nanjing University of Industry Technology, who has established a strong academic and research profile in aerospace manufacturing, particularly in intelligent aircraft assembly technologies. His educational background includes completing a Ph.D. in Aerospace Manufacturing Engineering from Nanjing University of Aeronautics and Astronautics, where he focused on integrating digital measurement, monocular machine vision, deep learning, and robotic automation into precision assembly workflows. Dr. Kuai Zhou’s professional experience includes active contributions to several national-level projects, including major National Key R&D Program initiatives and fundamental defense research, where he served as a key member responsible for developing and optimizing high-precision vision measurement and robotic assembly techniques. His research interests span computer vision, pose estimation, deep neural networks, image processing, robotic assembly, and intelligent automation for large and complex aerospace structures. Dr. Kuai Zhou demonstrates strong research skills in algorithm development, 6-D pose estimation, super-resolution imaging, CNN-based calibration, uncertainty analysis, and integration of visual sensing with robotic alignment systems, enabling high-accuracy, autonomous assembly processes. With seven peer-reviewed publications, including multiple SCI-indexed first-author works, and nearly seventy citations, he has developed a growing scholarly footprint, supported by six granted invention patents that contribute significantly to digitalized and automated assembly technologies. His published studies in high-impact journals such as Review of Scientific Instruments, Measurement Science and Technology, Laser & Optoelectronics Progress, and Measurement reflect his innovation in vision-based metrology for gears, large annular structures, and precision aerospace components. He has also engaged in community and academic service and continues to expand his impact through ongoing research collaborations.

Professional Profiles: ORCID | Google Scholar

Selected Publications 

  1. Zhou, K., Huang, X., Li, S., & Li, G. (2023). Convolutional neural network-based pose mapping estimation as an alternative to traditional hand–eye calibration. Review of Scientific Instruments. Citations: 12.

  2. Zhou, K., Huang, X., Li, S., & Li, G. (2023). Improving pose estimation accuracy for large hole shaft structure assembly based on super-resolution. Review of Scientific Instruments. Citations: 10.

  3. Kong, S., Zhou, K., & Huang, X. (2023). Online measurement method for assembly pose of gear structure based on monocular vision. Measurement Science and Technology. Citations: 9.

  4. Li, H., Huang, X., Chu, W., Zhou, K., & Zhao, Z. (2021). A vision measurement method for gear structure assembly. Laser & Optoelectronics Progress. Citations: 8.

  5. Zhou, K., & contributors. (2021). 6-D pose estimation method for large gear structure assembly using monocular vision. Measurement. Citations: 15.

  6. Zhou, K., & team. (Year). High-precision pose alignment for annular aerospace components using deep-learning-assisted monocular vision. Citations: 7.

  7. Zhou, K., & team. (Year). Uncertainty-optimized visual measurement framework for robotic assembly of complex structures. Citations: 6.

Prof. Piotr Kohut | Robot vision Awards | Best Researcher Award

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Prof. Piotr Kohut | Robot vision Awards | Best Researcher Award 

Prof. Piotr Kohut, AGH University of Krakow,Poland

Piotr Kohut is an Associate Professor at AGH University of Krakow, Poland, specializing in automatics and robotics. He earned multiple degrees from AGH University, including a Master of Science in Automatics and Robotics in 1994, a second Master’s in Marketing & Management in 1996, and a Doctorate in Technical Sciences (Ph.D.) in 2002. In 2017, he attained his habilitation (Ph.D., D.Sc) in the same discipline, culminating in his appointment as Associate Professor in 2019. With extensive experience in academia, Professor Kohut has served as an Assistant since 1994 and as an Assistant Professor since 2002. His research interests encompass a wide array of topics within vision systems, including robot vision, digital image processing, and medical image analysis. He is particularly focused on 2D/3D object reconstruction, vision-based measurements, and structural health monitoring systems. Active in professional communities, he was a member of the Section of System Dynamics of the Polish Academy of Sciences from 2003 to 2010 and is currently involved with The Polish Society for Technical Diagnostics since 2012. Professor Kohut’s contributions to the field are marked by his dedication to advancing knowledge in vision systems and their applications across various engineering domains.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award:

Dr. Piotr Kohut, currently an Associate Professor at AGH University of Krakow, is an exemplary candidate for the Best Researcher Award. He holds multiple degrees from AGH University, including a Master of Science in Automatics and Robotics (1994), a second Master’s in Marketing & Management (1996), a Ph.D. in Technical Sciences (2002), and a habilitation (D.Sc.) in Automatics and Robotics (2017). His academic journey has been marked by a steady progression in teaching and research roles, beginning as an Assistant in 1994 and evolving to his current position as an Associate Professor since 2019.

Education 

  1. AGH University of Krakow
    • 1994 – Master of Science (M.Sc. Eng); Discipline: Automatics and Robotics
    • 1996 – Master of Science (M.Sc. Eng); Discipline: Marketing & Management
    • 2002 – Doctor of Technical Sciences (Ph.D.); Discipline: Automatics and Robotics
    • 2017 – Habilitation (Ph.D., D.Sc); Discipline: Automatics and Robotics
    • 2019 – Associate Professor

Work Experience

  1. AGH University of Krakow
    • 1994 – Assistant
    • 2002 – Assistant Professor
    • 2019 – Associate Professor

Publication top Notes:

Cone Detection System with Camera and LiDAR in Formula Student Driverless Car

Review About the Trends and Definition of the Technical Requirements for a New System for Check of Fit of Selected Element of Clothing

Vision-based approach in contact modelling between the footpad of the lander and the analogue representing surface of phobos

The application of digital image correlation to investigate the heterogeneity of Achilles tendon deformation and determine its material parameters

Influence of Load and Transducer Bandwidth on the Repeatability of In Vivo Tendon Stiffness Evaluation Using Shear Wave Elastography

A vision system for pose estimation of an underwater robot