Zobeir Raisi | Vision Sensing | Best Researcher Award

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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.

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

Ms. Priyanka Manchegowda | Computer Vision | Women Researcher Award

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Ms. Priyanka Manchegowda | Computer Vision | Women Researcher Award

Ms. Priyanka Manchegowda | Computer Vision | Amrita Vishwa Vidyapeetham | India

Ms. Priyanka Manchegowda is a results-driven Assistant Professor and researcher, currently pursuing her Ph.D., with over 12 years of combined experience in teaching computer science, academic leadership, and curriculum development. She holds an M.Sc. in Computer Science from Pooja Bhagavat Memorial Mahajana Post Graduate Centre, affiliated with the University of Mysore, Mysuru, India, and has actively contributed to higher education by delivering advanced courses in Exploratory Data Analysis using Python, Digital Image Processing, Design and Analysis of Algorithms, Data Structures, Problem Solving and Programming, Operations Research, Numerical Analysis, Statistical Techniques, Programming in C/C++, and Database Management Systems, consistently achieving strong student satisfaction. Professionally, she has served as an Assistant Professor at SBRR Mahajana First Grade College, Mysuru, from 2013 to 2020, and currently at Amrita Vishwa Vidyapeetham, School of Computing, Mysuru Campus since 2020, where she also contributes as a member of the Board of Studies and has developed curricula in alignment with university standards. In addition to teaching, she has guided Bachelor’s and Master’s students on research projects, focusing her research on computer vision-based human age estimation tailored for Indian medico-legal scenarios, demonstrating expertise in analytical methods, quantitative aptitude, image processing, and programming with Python, C, and C++, alongside database management using MS SQL Server and tools such as MATLAB and Anaconda. Ms. Manchegowda has actively contributed to institutional initiatives and student development, serving as the SWAYAM MOOC Nodal Officer, and as convener for the Rotaract Club and SARANTHA, while also engaging in faculty evaluations for the Internal Quality Assurance Cell (IQAC). She brings strong leadership, teamwork, administrative, and communication skills, alongside a commitment to lifelong learning and academic engagement. Her professional recognition includes citations in Scopus with an h-index reflecting the impact of her scholarly contributions.

Professional Profiles: ORCID | Scopus

Selected Publications

  • Priyanka, M., Divyashree, M., & Madhu, V. (2022). Computer Vision-Based Approach for Estimating Age and Gender using Wrist X-Ray Images.

  • Priyanka, M., Sreekumar, S., & Arsh, S. (2022). Detection of Covid-19 from the Chest X-Ray Images: A Comparison Study between CNN and Resnet-50.

Mr. Xiangxue Chen | Computer Vision Award | Best Researcher Award

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Mr. Xiangxue Chen | Computer Vision Award | Best Researcher Award

Mr. Xiangxue Chen | Computer Vision Award | Jinan University | China

Mr. Xiangxue Chen is a motivated and academically accomplished postgraduate student currently pursuing a Master’s degree in Agricultural Engineering and Information Technology at Gansu Agricultural University, College of Information Science and Technology, building on previous undergraduate training in Network Engineering at Jinan University Quancheng College. With strong enthusiasm for the integration of artificial intelligence into modern agriculture, the research interests of Xiangxue Chen focus on Deep Learning, Smart Agriculture, and Agricultural Informatization, particularly on intelligent livestock measurement and management. During the Master’s program, Xiangxue Chen led impactful research on automatic cattle body size measurement based on deep learning, contributing to livestock breeding efficiency and smart farming systems. The technical approach included designing lightweight keypoint detection models using frameworks like YOLOv8-pose, automatically identifying cattle and predicting anatomical keypoints, followed by measurement transformation through Euclidean estimation and relevant calibration parameters to provide real-world body dimension results. A dedicated dataset was independently developed by visiting and acquiring cattle images at the National Jinnan Cattle Genetic Resource Gene Conservation Center in Yuncheng, Shanxi Province, demonstrating initiative in data collection and preprocessing. Xiangxue Chen has authored multiple impactful academic publications, including one SCI paper in the journal Symmetry as first author and two additional first- and co-authored papers in Peking University Core & CSCD-C journals such as the Journal of Nanjing Agricultural University and Journal of South China Agricultural University, as well as a first-author software copyright titled Automatic Cattle Body Measurement System Based on Improved YOLOv8-pose. Throughout graduate studies, excellence has been recognized by receiving the Postgraduate Academic Scholarship twice (October 2023 and October 2024). In terms of professional skills, Xiangxue Chen is proficient in PyTorch for deep-learning tasks including detection, segmentation, pose estimation, and classification, while also being skilled in Python, C#, Java, HTML, and research tools such as Origin, Visio, MathType, and Zotero. Additionally, Xiangxue Chen holds certifications in Web Front-End Development (Primary Level) and as an Artificial Intelligence Trainer (Advanced Level). Overall, Xiangxue Chen stands out as a talented young researcher dedicated to advancing agricultural digitalization and intelligent livestock system innovation, contributing meaningful scholarly achievements with great potential for future development in smart agriculture technology.

Professional Profiles:Β ORCID

Selected Publications

  • Chen, X., Guo, X., Li, Y., & Liu, C. (2025). A Lightweight Automatic Cattle Body Measurement Method Based on Keypoint Detection. Symmetry.

Aljaz Hojski | Vision Sensing | Best Researcher

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Dr. Aljaz Hojski | Vision Sensing | Best Researcher

Dr. Aljaz Hojski | Vision Sensing | Cadre doctor at UniversitΓ€tspital Basel | Switzerland

Dr. Aljaz Hojski is a highly respected thoracic surgeon and clinical researcher, currently affiliated with UniversitΓ€tspital 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 UniversitΓ€tspital 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.

 

 

Dr. Meir Marmor | Image Analysis Awards | Best Researcher Award

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Dr. Meir Marmor | Image Analysis Awards | Best Researcher Award

Dr. Meir Marmor , UCSF, United States

Dr. Meir Tibrin Marmor is a Professor of Clinical Orthopaedic Surgery at the University of California, San Francisco (UCSF), specializing in orthopaedic trauma and joint replacement. He earned his M.D. from the Israel Institute of Technology with cum laude distinction and completed his orthopaedic residency in Israel before advancing his training through AO and clinical fellowships in trauma and joint replacement surgery in Germany and the U.S. Since 2010, he has served as a trauma surgeon across several Level I and II centers in Northern California, with a primary clinical role at Zuckerberg San Francisco General Hospital (ZSFG), where he leads the Orthopaedic β€œBlue” Service, the Geriatric Orthopaedic Trauma Service, and the OTI Digital Science Laboratory. Dr. Marmor’s research focuses on musculoskeletal trauma in vulnerable and geriatric populations, as well as surgical education, data science, and digital health technology. He has received numerous awards, including the OTA’s Kathy Cramer Young Clinicians Research Award and multiple best paper and poster recognitions. An active member of global orthopedic societies, he also chairs the OTA Artificial Intelligence Task Force and contributes extensively to academic publishing and international presentations.

Professional Profile:

SCOPUS

Summary of Suitability – Dr. Meir Tibrin Marmor for Best Researcher Award

Dr. Meir Tibrin Marmor is a distinguished clinician-scientist in orthopaedic trauma surgery with over two decades of training, research, and clinical practice in high-impact academic and clinical environments. Currently a Professor of Clinical Orthopaedic Surgery at the University of California, San Francisco (UCSF), he combines surgical excellence with robust contributions to medical research and technology.

πŸŽ“ Education

  • πŸ“˜ B.Sc. in Medical Sciences – Israel Institute of Technology, Haifa (1988–1992) cum laude

  • 🩺 M.D. in Medicine – Ruth and Bruce Rappaport Faculty of Medicine, Israel Institute of Technology (1992–1996) cum laude

  • πŸ₯ Orthopaedic Surgery Residency – Tel-Aviv Medical Center & Barzilai Medical Center, Israel (2000–2008)

  • 🌍 AO Fellowship in Orthopaedic Trauma – Saarland University Hospital, Germany (2008)

  • πŸ”¬ Research Fellowship – UCSF, Orthopaedic Trauma (2008–2009)

  • 🩻 Clinical Fellowship – UCSF, Orthopaedic Trauma Surgery (2009–2010)

  • 🦴 Joint Replacement Fellowship – Joint Replacement Institute, Los Angeles (2017–2018)

  • πŸ’» Master’s in Information and Data Science (MIDS) – UC Berkeley (2022–2024)

πŸ§‘β€βš•οΈ Work Experience

  • πŸ‘¨β€πŸ« Professor of Clinical Orthopaedic Surgery – UCSF, Step 1 (Current)

  • πŸ₯ Orthopaedic Trauma Surgeon at:

    • Zuckerberg San Francisco General Hospital (ZSFG)

    • Enloe Medical Center, Chico, CA (2012–2014)

    • Regional Medical Center of San Jose (2013–2022)

  • πŸ‘¨β€πŸ”¬ Research and Medical Director Roles:

    • Clinical Research Director – UCSF @ Regional Medical Center

    • Medical Director – Biomechanics Testing Facility @ UCSF

    • Director – Geriatric Orthopaedic Trauma Service & OTI Digital Science Lab @ ZSFG

    • Chief – Orthopaedic β€œBlue” Service @ ZSFG

πŸ† Honors and Awards

  • πŸŽ–οΈ B.Sc. Medical Sciences – cum laude (1992)

  • πŸŽ–οΈ M.D. – cum laude (1997)

  • πŸͺ– Operational Performance Citation – Lebanon Front, IDF (1999)

  • πŸ’° Fellowship Scholarships – American Physicians Fellowship & Israeli Medical Association (2008)

  • πŸ–ΌοΈ β€œBest Poster” Award – OTA 25th Annual Meeting, San Diego (2009)

  • πŸ“œ Best Paper Nomination – CAINE Conference (2014)

  • πŸ’‘ Kathy Cramer Young Clinicians Research Development Award – OTA (2015)

  • πŸ… Howard Rosen Table Instructor Award – AO Trauma North America (2018)

PublicationΒ Top Notes:

Revisiting the OTA-OFC: a systematic review of open fracture classification studies since 2010

Artificial intelligence: international perspectives on critical issues

The Impact of National Orthopaedic Fracture Registries: A Systematic Review

Patient Recruitment Characteristics for Wearable-Sensor-Based Outcome Assessment in Trauma Surgery

A scoping review and critical appraisal of orthopaedic trauma research using the American College of Surgeons National Trauma Data Bank

Worldwide research trends concerning operative competence in orthopedics: A bibliometric and visualization study

Does the CDC Surgical Wound Classification adequately predict postoperative infection in lower extremity fracture surgery?

Mortality, perioperative complications and surgical timelines in hip fracture patients: Comparison of the Spanish with the non-Spanish Cohort of the HIP ATTACK-1 trial

Ms. Devinder Kaur | Computer Science | Women Researcher Award

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Ms. Devinder Kaur | Computer Science | Women Researcher AwardΒ 

Ms. Devinder Kaur, Mata Gujri College, India

Dr. Devinder Kaur is an experienced academician currently serving as an Assistant Professor in the Department of Computer Applications at Mata Gujri College, Fatehgarh Sahib, with over 20 years of teaching experience. She holds a Bachelor’s degree in Computer Applications from Punjabi University, Patiala, and a Master’s degree in Computer Applications from Punjab Technical University, Jalandhar. She is presently pursuing her Ph.D. in Computer Science at Sri Guru Granth Sahib World University, Fatehgarh Sahib. Dr. Kaur has authored two academic booksβ€”A Practical Approach to Java Programming and An Introduction to System Softwareβ€”and contributed numerous research papers and book chapters in both national and international journals and conference proceedings. Her recent research interests focus on IoT and machine learning applications in livestock health monitoring, cybersecurity, environmental sustainability, and green computing. She has also actively participated in national-level conferences, addressing critical topics like social media addiction, privacy concerns, and e-waste management. Dr. Kaur’s scholarly contributions reflect her dedication to bridging practical technology with real-world challenges in both academic and agricultural domains.

Professional Profile:

GOOGLE SCHOLAR

SCOPUS

Summary of Suitability for Women Researcher AwardΒ 

Dr. Devinder Kaur is a highly qualified and accomplished academic with over 20 years of teaching experience in Computer Science, currently serving as an Assistant Professor at Mata Gujri College, Fatehgarh Sahib. She holds Bachelor’s and Master’s degrees in Computer Applications and is currently pursuing her Ph.D. in Computer Science from Sri Granth Sahib World University, highlighting her continuous academic advancement.

πŸŽ“ Education

  • πŸŽ“ Bachelors of Computer Applications (BCA) from Punjabi University, Patiala.

  • πŸŽ“ Masters of Computer Applications (MCA) from Punjab Technical University, Jalandhar.

  • πŸ“š Pursuing PhD in Computer Science from Sri Granth Sahib World University, Fatehgarh Sahib.

πŸ‘©β€πŸ« Work Experience

  • 🏫 Assistant Professor at Mata Gujri College, Fatehgarh Sahib.

  • πŸ“… 20 years of teaching experience in the field of Computer Science.

πŸ† Achievements, Awards & Honors

  • πŸ“– Published Books:

    • β€œA Practical Approach to Java Programming” – πŸ“˜ Unistar Books Pvt Ltd (2018)

    • β€œAn Introduction to System Software” – πŸ“— Narosa Publishing House (2020)

  • πŸ“ Research Contributions:

    • πŸ“š Multiple book chapters and conference papers on topics such as:

      • Green Computing 🌱

      • Social Media Psychology πŸ“±

      • E-Waste Management ♻️

      • IoT and Machine Learning in Livestock Health πŸ„πŸ’‘

      • Breast Cancer Classification Using ML πŸŽ—οΈπŸ§ 

  • πŸ”— Featured in IEEE, Auerbach Publications, and peer-reviewed journals like Discover Internet of Things, IJIRAE, Journal of Electrical Systems.

  • 🌐 Contributed to multidisciplinary and international conferences on smart tech, computing trends, and innovative research in AI & IoT.

PublicationΒ Top Notes:

CITED:409
CITED:135
CITED:118
CITED:102
CITED:97
CITED:87
CITED:81

Mr. Mohammed Aljamal | Artificial Intelligence | Best Researcher Award

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Mr. Mohammed Aljamal | Artificial Intelligence | Best Researcher AwardΒ 

Mr. Mohammed Aljamal, University of Bridgeport, United States

Mohammed Aljamal is a Laboratory Engineer and Ph.D. candidate in Computer Science & Engineering, based in the New York City Metropolitan Area. He holds a Master’s degree in Artificial Intelligence from the University of Bridgeport and is actively engaged in academic and professional communities as the President of the UB Robotics Club and a member of AIAA, UPE, and the Honor Society. With over four years of experience at the University of Bridgeport, he has contributed as a Laboratory Engineer, Graduate Research Assistant, and Teaching Assistant, specializing in laboratory management, hardware and software solutions, and IT infrastructure. His expertise spans project leadership, problem-solving, cross-functional team management, and innovative solution design. Beyond academia, Mohammed has a strong background in consulting, resource allocation, and international collaboration, having successfully led and completed critical projects. Passionate about technology and innovation, he continuously seeks opportunities to develop solutions that enhance user experiences and drive technological advancement.

Professional Profile:

GOOGLE SCHOLAR

Suitability of Mohammed Aljamal for the Best Researcher Award

Mohammed Aljamal is a highly skilled and innovative researcher with a strong background in Artificial Intelligence, Computer Science, and Engineering. His Ph.D. candidacy, extensive teaching experience, and leadership roles at the University of Bridgeport demonstrate his dedication to academic excellence and technological advancements.

Education πŸŽ“

  • Ph.D. Candidate in Computer Science & Engineering – University of Bridgeport (Ongoing)
  • Master’s Degree in Artificial Intelligence – University of Bridgeport
  • Bachelor’s Degree in [Field Not Specified] – [University Not Specified]

Work Experience πŸ’Ό

University of Bridgeport (4 years 1 month)

  • Labs Engineer (Feb 2022 – Present) βš™οΈ

    • Improved and maintained laboratory equipment.
    • Developed detailed hardware and software data for lab management.
    • Conducted inspections and routine maintenance on lab equipment.
    • Implemented new technology solutions and disaster recovery plans.
    • Coordinated IT services to ensure data availability and security.

  • Graduate Research & Teaching Assistant (Jan 2022 – Feb 2022) πŸ“š

    • Assisted in research projects and student instruction.

  • Teaching and Laboratory Assistant (Feb 2021 – Dec 2021) 🏫

    • Assisted undergraduate and graduate students in Intro to Robotics.
    • Managed lab hours, discussions, assignments, and exams.

Achievements & Leadership 🌟

  • President of UB Robotics Club πŸ€– – Leading robotics initiatives and student projects.
  • Successfully completed two delayed projects 🎯 – Resolved critical issues and met client satisfaction.
  • Consulted and collaborated with international vendors 🌍 – Gained experience in global tech solutions.
  • Designed and implemented innovative lab solutions πŸ”§ – Optimized university lab resources.

Awards & Honors πŸ†

  • Member of AIAA (American Institute of Aeronautics and Astronautics) πŸš€
  • Member of UPE (Upsilon Pi Epsilon – International Honor Society for Computing) πŸ–₯️
  • Honor Society Member πŸŽ–οΈ

PublicationΒ Top Notes:

 

 

Dr. Yongho Jeong | Computer vision | Best Researcher Award

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Dr. Yongho Jeong | Computer vision | Best Researcher AwardΒ 

Dr. Yongho Jeong, Konkuk University, South Korea

Dr. Yongho Jeong is a physicist specializing in experimental particle physics, high-energy physics, and AI-driven data analysis. He earned his Ph.D. in Physics from Sungkyunkwan University, Korea, in 2022 under the supervision of Prof. YongIl Choi, focusing on the search for R-parity violating supersymmetry in proton-proton collisions at √s = 13 TeV using the CMS detector. He completed his B.S. in Physics from Soonchunhyang University in 2013. Dr. Jeong has held multiple postdoctoral positions, including at the University of Seoul, where he worked on Gas Electron Multiplier (GEM) detector aging tests, and at the Korea Astronomy and Space Science Institute (KASI), where he contributed to quantum noise reduction for future gravitational wave detectors. He has also been involved in AI software development at Mustree Company and is set to join Konkuk University as a postdoctoral researcher in 2024, focusing on 3D point cloud data analysis. His extensive research experience includes collaborations with CERN on the GEM Detector Upgrade Project for the CMS experiment, where he worked on quality control, chamber assembly, and detector performance studies. His expertise spans detector development, high-energy physics simulations, data analysis for supersymmetry searches, and advanced AI applications in physics.

Professional Profile:

ORCID

Summary of Suitability for Community Impact AwardΒ 

Dr. Yongho Jeong is a highly deserving candidate for the Community Impact Award, given his significant contributions to experimental particle physics, AI-driven technological advancements, and quantum noise reduction for future scientific applications. His extensive research collaborations, contributions to international projects, and involvement in technology-driven community advancements make him a strong nominee for this award.

πŸ“š Education

  • Ph.D. in Physics (2014.09 – 2022.02) – Sungkyunkwan University, Suwon, Korea
    • Supervisor: YongIl Choi
    • Thesis: Search for R-parity violating supersymmetry in pp collisions at √s = 13 TeV in the CMS detector
  • B.S. in Physics (2007.03 – 2013.02) – Soonchunhyang University, Asan, Korea
    • Thesis: The Age of the Universe

πŸ’Ό Work Experience

  • Postdoctoral Researcher – KonKuk University (KU), Seoul, Korea (2024.09 – Present)

    • Integrated Analytical Models and Advanced Strategies for 3D Point Cloud Data Analysis

  • Postdoctoral Researcher – University of Seoul (UOS), Seoul, Korea (2023.11 – 2024.08)

    • Gas Electron Multiplier (GEM) Detector Aging Test
    • Production of GEM Detector Foil for the Rare Isotope Accelerator Complex (RAON) Laboratory

  • Technology Team – AI Software Development – Mustree Company, Seoul, Korea (2023.07 – 2023.10)

    • Developed AI Software for Size Measurement

  • Postdoctoral Researcher – Korea Astronomy and Space Science Institute (KASI), Daejeon, Korea (2022.05 – 2023.07)

    • Quantum Noise Reduction Technology for Future Gravitational Wave Detectors
    • Development of a 2 Β΅m Laser Squeeze System

  • Ph.D. Researcher – High Energy Physics – Korea University, Seoul, Korea (2020.01 – 2022.04)

    • Data Analysis for Supersymmetric Particles
    • Search for R-parity Violating Supersymmetry in Proton-Proton Collisions at √s = 13 TeV

  • Ph.D. Researcher – GEM Detector Upgrade Project (Phase II) – CERN, Geneva, Switzerland (2018.01 – 2019.12)

    • Quality Control (QC) of GEM Chambers in the CMS Experiment
    • QC2: Leakage Current Test
    • QC3: Gas Leak Test
    • QC4: High Voltage Test
    • GEM Chamber Assembly, Aging Tests & Discharge Probability Studies

  • Ph.D. Researcher – Experimental Particle Physics – Sungkyunkwan University, Suwon, Korea (2017.06 – 2018.02)

    • Data Analysis for ttΜ„ Inclusive Decay
    • Measurement of the Inclusive Top Quark Cross Section in Di-lepton Channels at √s = 13 TeV

  • Ph.D. Researcher – Experimental Particle Physics – University of Seoul, Seoul, Korea (2016.01 – 2017.06)

    • CMS Detector Simulation for Phase II Upgrade
    • Muon Isolation Optimization Simulation

πŸ† Achievements & Contributions

βœ… Authored numerous research papers in High-Energy Physics & Detector Technology
βœ… Significant contributions to CMS Detector R&D at CERN
βœ… Advanced AI-based measurement software for industry applications
βœ… Developed quantum noise reduction techniques for future gravitational wave detectors

πŸŽ–οΈ Awards & Honors

πŸ… Recognized Researcher in Particle Physics for contributions to Supersymmetry & CMS Experiments
πŸ… Recipient of CERN Research Fellowships for GEM Detector Upgrade & Testing
πŸ… Awarded Postdoctoral Research Positions in Multiple Leading Korean Institutions
πŸ… Contributor to the CMS Collaboration at the European Organization for Nuclear Research (CERN)

PublicationΒ Top Notes:

A Mobile LiDAR-Based Deep Learning Approach for Real-Time 3D Body Measurement

A Multi-View Integrated Ensemble for the Background Discrimination of Semi-Supervised Semantic Segmentation

Mr. Adrian Barglazan | Computer Vision | Best Researcher Award

Posted on by Global Sensor Awards

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.

πŸŽ“ Education:

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

πŸ’Ό Work Experience:

πŸ”Ή Senior Software Engineer – Cognizant Softvision (Sept 2020 – Present)
πŸ“ Sibiu, Romania

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

πŸ”Ή PhD Student & Teaching Assistant – Lucian Blaga University of Sibiu (Sept 2011 – Present)
πŸ“ Sibiu County, Romania

  • Research in Media Forensics πŸ”
  • Teaching Data Compression & DirectX to 4th-year students πŸŽ“
  • Covers key algorithms like Shannon, Huffman, LZ77, JPEG, MPEG

πŸ”Ή Software Developer – Visma (Apr 2017 – Sept 2020)
πŸ“ Sibiu County, Romania

  • Senior developer in cloud ERP Single Page Application (SPA) development β˜οΈπŸ’»
  • Technologies: C#, ASP.NET MVC, Azure SQL, React, TypeScript
  • Worked with Kanban methodology, CI/CD, and cross-country teams

πŸ”Ή Developer – iQuest Technologies (Sept 2011 – Apr 2017)
πŸ“ Sibiu County, Romania

  • Lead developer in Pharma sector projects πŸ’Š
  • Software architecture, risk management, and recruitment πŸ“‹

πŸ† Achievements, Awards & Honors:

🌟 PhD Researcher in Media Forensics πŸ“ΈπŸ”¬
🌟 Senior Software Engineer with over 17 years of experience in the software industry πŸ’»
🌟 Specializes in Microsoft technologies, Agile development, and Clean Code principles ⚑
🌟 Mentor & Teacher – educating future developers on Data Compression & DirectX πŸŽ“
🌟 Experienced in cloud-based ERP systems, software architecture, and machine learning β˜οΈπŸ€–
🌟 Contributor to recruitment & technical interviews in multiple companies πŸ…

PublicationΒ 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