Assoc. Prof. Dr Andrea Suranyi | Health Evaluation | Best Researcher Award

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Assoc. Prof. Dr Andrea Suranyi | Health Evaluation | Best Researcher Award 

Assoc. Prof. Dr Andrea Suranyi, University of Szeged, Hungary

Dr. Andrea Suranyi, MD, PhD, is an Associate Professor at the Department of Obstetrics and Gynecology, University of Szeged, Hungary. She specializes in obstetrical and gynecological ultrasound, with expertise in 3D ultrasound imaging and fetal medicine. She obtained her MD in 1994 and completed her PhD in 2000, focusing on fetal renal hyperechogenicity in complicated pregnancies. With over two decades of experience, she has contributed to numerous research projects, international collaborations, and peer-reviewed publications. She has received advanced training in ultrasound screening and fetal medicine from prestigious institutions, including the Fetal Medicine Foundation in London.

Professional Profile:

GOOGLE SCHOLAR

SCOPUS

ORCID

Suitability for Best Researcher Award

Andrea Suranyi, MD, PhD, is a highly qualified researcher and clinician with extensive expertise in obstetrical and gynecological ultrasound. With a strong academic foundation from the University of Szeged and international training experiences in Belgium, Venezuela, and the UK, she has built a robust career in perinatal ultrasound research. Her contributions to the field include pioneering studies on fetal renal sonographic alterations and placental Doppler indices in pregnancies complicated by gestational diabetes. Her work is well-documented through peer-reviewed publications, and she has demonstrated leadership in designing and managing research projects.

🎓 Education & Training

  • University of Szeged, Hungary – MD (12/1994) 🏥
    General Medicine
  • University of Szeged, Hungary – Postdoctoral Training (08/1998) 📚
  • University of Szeged, Hungary – PhD (06/2000) 🎓
    Thesis: “Prenatal and postnatal evaluation of fetal renal hyperechogenicity in pregnancies complicated with pre-eclampsia and intrauterine growth retardation”
  • Residency Training 🏨
    • Clinical Pathology – (2000) 🧪
    • Pediatrics – (2003) 👶
  • Sonography Certifications 🔬
    • Level ‘A’ (Basic Ultrasound in O&G) – (1994)
    • Level ‘B’ (Advanced Ultrasound in O&G, Fetal Malformation Screening) – (2003)
  • International Certifications 🌍
    • Fetal Medicine Foundation, UK (2011)
      Nuchal translucency, Doppler investigation, Cervical measurement

💼 Work Experience

  • University of Szeged, Hungary 🏛️

    • Trainee – Dept. of Clinical Chemistry (1998-2000)
    • Assistant Professor – Dept. of Clinical Chemistry (2000)
    • Assistant Professor – Dept. of Obstetrics & Gynecology (2002-2008)
    • Lecturer – Dept. of Obstetrics & Gynecology (2008-2014)
    • Senior Research Fellow – Dept. of Obstetrics & Gynecology (2014-2022)
    • Associate Professor – Dept. of Obstetrics & Gynecology (2022-Present)

  • International Research & Training 🌏

    • 🇫🇷 Centre Medico-Chirurgical Arnault Tzack, France (1993)
    • 🇧🇪 Hôpital de la Citadella, Belgium (1997) – Scholarship by CGRI
    • 🇻🇪 Hospital Universitario de Los Andes, Venezuela (2001)
    • 🇦🇹 Salzburg Medical Seminars, Austria – Women’s Health Course (2002)
    • 🇬🇧 Fetal Medicine Foundation, London, UK (2015)

🏆 Achievements & Awards

  • Expert in Obstetric & Gynecologic Ultrasound 📡
    • Specialist in 3D/4D ultrasound research & fetal renal imaging
  • Research on Fetal & Neonatal Renal Hyperechogenicity 🧬
    • Multiple peer-reviewed publications
  • Scholarship Awards 🎖️
    • CGRI Scholarship (Belgium, 1997)
    • American Austrian Foundation & Soros Foundation (2002)
  • Advanced Sonography Training 🏅
    • Vienna International School of 3D Ultrasonography (2011)
    • International Methodological Training in 3D/4D Ultrasound (2012)

Publication Top Notes:

CD3+CD56+ NK T cells are significantly decreased in the peripheral blood of patients with psoriasis

CITED:92

Effects of magnesium supplementation on the glutathione redox system in atopic asthmatic children

CITED:49

Urinary magnesium excretion in asthmatic children receiving magnesium supplementation: a randomized, placebo-controlled, double-blind study

CITED:49

Placental three‐dimensional power Doppler indices in mid‐pregnancy and late pregnancy complicated by gestational diabetes mellitus

CITED:38

Maternal hematological parameters and placental and umbilical cord histopathology in intrauterine growth restriction

CITED:29

 

Prof. Alina Nechyporenko | Healthcare Awards | Best Researcher Award

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Prof. Alina Nechyporenko | Healthcare Awards | Best Researcher Award

Prof. Alina Nechyporenko, Technische Hochschule Wildau, Germany

Dr. Alina Nechyporenko is an accomplished scientist and professor specializing in pattern recognition, biomedical signal processing, and data mining. Currently, she serves as a Scientist and Reader at the Technical University of Applied Sciences Wildau, Germany, where she works in the Department of Molecular Biotechnology and Functional Genome Analysis. She has also been a Professor at Kharkiv National University of Radio Electronics in Ukraine since 2018, contributing to the Faculty of Computer Science and the Department of Systems Engineering. Dr. Nechyporenko has over 70 publications in peer-reviewed journals and holds five patents. She is an expert evaluator for ISO/TC 276 Biotechnology and has been involved in several high-impact research projects, including Horizon2020, COST actions, and Erasmus+ initiatives. Her current research focuses on biomedical research, machine learning, and data management, with significant contributions to European life-science research and microbiome studies.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award

Alina Nechyporenko is a highly accomplished researcher in the fields of Pattern Recognition, Biomedical Signal Processing, and Machine Learning, with an extensive academic and professional background. She has demonstrated significant contributions to biomedical research, particularly in the application of data mining and computational techniques in cancer therapy, microbiome research, and deep learning. Given her work and leadership in her respective fields, she is highly suitable for the Best Researcher Award.

Education and Training

  • Expert in Evaluation Competences
    • Member of ISO/TC 276 Biotechnology, WG 2, WG 5, and national TC 166 “Clinical laboratory studies and systems for in vitro diagnostics.”
    • Technical Committee and Reviewer for the UKRCON IEEE conference.
  • Ph.D. in Computer Science
    • Specialization in Biomedical Signal Processing and Pattern Recognition
    • Thesis focused on data management and machine learning applications.
  • Publications and Patents
    • Over 70 publications in peer-reviewed scientific journals
    • Holder of 5 patents related to biomedical and computational applications.

Work Experience

2019 – Present

  • Scientist and Reader for Pattern Recognition, Biomedical Signal Processing
    • Technical University of Applied Sciences Wildau, Germany
    • Conducting research in areas such as data mining, machine learning, and data management within the Department of Molecular Biotechnology and Functional Genome Analysis.
    • Participates in Horizon2020 grant agreement ID: 654156 (RItrain – Research Infrastructures Training Programme), COST CA15110 (Harmonising standardisation strategies in European life-science research), and Erasmus + Capacity-building projects.
    • Engaged in COST CA18131 (Statistical and machine learning techniques in human microbiome studies) and DAAD “Digital Ukraine: Ensuring academic success in times of crisis” projects (2022 – 2025).

Since 2018

  • Professor
    • Kharkiv National University of Radio Electronics, Ukraine
    • Faculty of Computer Science & Department of Systems Engineering
    • Involved in teaching and research, focusing on pattern recognition, data processing, and systems engineering.

Publication top Notes:

Modeling and Computer Simulation of Nanocomplexation for Cancer Therapy

Comparison of CNN-Based Architectures for Detection of Different Object Classes

Comparison of CNN-Based Architectures for Detection of Different Object Classe

Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action

Classification of Microbiome Data from Type 2 Diabetes Mellitus Individuals with Deep Learning Image Recognition

Intelligent Decision Support System for Differential Diagnosis of Chronic Odontogenic Rhinosinusitis Based on U-Net Segmentation

Dr.Reza Askari Moghadam | Bio Sensor Awards | Best Researcher Award

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Dr.Reza Askari Moghadam | Bio Sensor Awards | Best Researcher Award-5093

Dr.Reza Askari Moghadam, Sorbonne Université, France

Reza Askari Moghadam is a distinguished academic and researcher currently serving as a Lecturer at Sorbonne Université in Paris, France, specializing in electronics and mechatronics. He holds a Ph.D. in Electronics from the Islamic Azad University (IUST), where he conducted innovative research on intelligent fault detection in RF MEMS, funded by the Iranian Telecommunications Research Center. With over a decade of experience as a Tenured Lecturer at the University of Tehran, Reza has significantly contributed to the fields of sensors, actuators, microfluidics, and artificial intelligence. His extensive teaching background encompasses more than 4,600 hours of instruction across various degree programs, from bachelor’s to doctoral levels. Reza’s research output includes 58 articles in international journals and 59 conference papers, highlighting his active engagement in advancing knowledge in his field. He has also participated in multiple collaborations and projects in Europe, further enriching his academic portfolio. In addition to his research and teaching, he possesses a robust skill set in various software tools, including Python, MATLAB, and COMSOL, which support his ongoing contributions to engineering and technology.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award: 

Reza Askari Moghadam is an accomplished academic and researcher in the field of Electronics and Engineering, with a solid track record of teaching, research, and publication. His diverse experiences, educational background, and substantial contributions to the field make him a strong candidate for the Best Researcher Award.

Education

  1. Ph.D. in Electronics
    • Institution: Islamic Azad University (IUST), Tehran, Iran
    • Years: 2001 – 2007
    • Thesis: “Intelligent Detection of Faults in RF MEMS”
    • Funding: Iranian Telecommunications Research Center (ITRC)
  2. Master’s Degree in Electrical Engineering (Specialization: Control)
    • Institution: Islamic Azad University (IUST), Tehran, Iran
    • Years: 1998 – 2001
    • Thesis: “Design, Implementation, and Control of a Robotic Arm”
    • Funding: Electronics Research Center, IUST
  3. Bachelor’s Degree in Electrical Engineering (Specialization: Electronics)
    • Institution: University of Petroleum Industry, Iran
    • Years: 1993 – 1998
    • Thesis: “Design and Implementation of an EEPROM Programmer”

Professional Experience

  1. Lecturer
    • Institution: Campus Pierre et Marie Curie, Sorbonne Université, Paris, France
    • Years: Sep. 2023 – Present
  2. Temporary Teaching and Research Attaché (ATER)
    • Institution: Laboratoire Images, Signaux et Systèmes Intelligents (LISSI), UPEC, France
    • Years: Jan. 2022 – Sep. 2023
    • Notes: Contract renewed in September 2022
  3. Tenured Lecturer
    • Institution: Department of “Mechatronics & MEMS”, Faculty of New Sciences and Technologies, University of Tehran (UT), Iran
    • Years: Sep. 2012 – Jan. 2022

Research Activities

  • Collaborated with LISSI Laboratory, UPEC, France since 2016.
  • Visiting Researcher at Nano Center, University of Southampton, UK (2010, three months).
  • Attended Synchrotron Summer School at Daresbury Synchrotron Laboratory, UK (2004, one month).

Publication top Notes:

Simplified U-Net as a deep learning intelligent medical assistive tool in glaucoma detection

High speed universal NAND gate based on weakly coupled RF MEMS resonators

Microfluidics chip inspired by fish gills for blood cells and serum separation

Theoretical and experimental evaluation of small flow rate ultrasonic flowmeter

Design optimization of a heat-to-cool Stirling cycle using artificial neural network

A novel Gamma-type duplex Stirling system to convert heat energy to cooling power: Theoretical and experimental study

Mr. Nduduzo Shandu | Health Award | Best Researcher Award

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Mr. Nduduzo Shandu | Health Award | Best Researcher Award

Mr. Nduduzo Shandu, University of Zululand, South Africa

Nduduzo M. Shandu is a dedicated and accomplished professional in the fields of Biokinetics and Sport Science. Born on February 4, 1997, in South Africa, he holds a National Senior Certificate from Umtapho High School and has completed an impressive academic journey at the University of Zululand. His qualifications include a BSc in Microbiology and Human Movement Science, a BSc Honours in Biokinetics, and an MSc in Sport Science, all earned with distinction. His expertise spans a range of skills, including creativity, interpersonal communication, critical thinking, and leadership, supported by certifications in First Aid, Emergency Oxygen Provision, and digital literacy. Nduduzo has gained practical experience through internships and work at institutions such as the University of Nelson Mandela and the Sharks Medical Centre, where he has been involved in rehabilitating athletes and chronic patients, as well as strength and conditioning training. His commitment to education and community service is evident from his roles as a teaching assistant and education assistant, as well as his involvement in various sports, including athletics and netball. Nduduzo’s contributions to the field are also highlighted by his awards and certificates of excellence for outstanding academic performance.

Professional Profile:

Summary of Suitability for Best Researcher Award

Nduduzo has achieved distinction (Cum Laude) in multiple degrees, including a BSc in Microbiology and Human Movement Science, an Honours in Biokinetics, and an MSc in Sport Science from the University of Zululand. Specialized Knowledge: His educational background is well-aligned with research in health, fitness, and biokinetics.

Education

  • National Senior Certificate (Grade 12)
    Umtapho High School, 2014
    Subjects Passed: IsiZulu, English, Mathematics, Life Orientation, Accounting, Life Sciences, Physical Sciences
    Certificate Status: Bachelor Pass (NSC-35 points)
  • BSc (Microbiology and Human Movement Science)
    University of Zululand, 2015-2017
    Degree Status: Distinction (Cum Lauda)
  • BSc Hons Biokinetics
    University of Zululand, Jan-Dec 2018
    Degree Status: Distinction (Cum Lauda)
  • MSc Sport Science
    University of Zululand, 2019-2022
    Degree Status: Distinction (Cum Lauda)

Work Experience

  • Education Assistant
    Department of Basic Education (Ndabomuhle Primary School), Nov 2021-Aug 2022
    Responsibilities: Supported classroom activities, developed learning methods, assisted with sanitation and lesson preparation, provided additional clarification, marked assessments.
  • Biokinetics Intern
    Biokinetics and Sport Science Unit (BSSU), University of Nelson Mandela, Jan-Dec 2020
    Responsibilities: Rehabilitation of chronic patients and athletes, operated Cybex, Spirometry, ECG, and Biodex machines, provided exercise prescriptions and strapping.
  • Teaching (Tutoring) Experience
    HPW Organization (Ophinda High School), 2016-2019
    Responsibilities: Assisted learners with assignments and curriculum revision in Physical Sciences, Mathematics, Life Sciences, and Agricultural Sciences.
  • Tutoring
    Teaching and Learning Centre, University of Zululand, 2016-2019
    Responsibilities: Prepared assignments, marked scripts, and provided student support.

Publication top Notes:

Perspectives of Hospital Staff on Barriers to Smoking Cessation Interventions among Drug-Resistant Tuberculosis Patients in a South African Management Hospital

Past, Present and Future of Judo: A Systematic Review

Exercise Effects on Health-Related Quality of Life (HRQOL), Muscular Function, Cardiorespiratory Function, and Body Composition in Smokers: A Narrative Review

The Effects of High-Intensity Interval Training on Health Fitness,Health-Related Quality of Life and Psychological Measurs among College-aged Smokers

Shoulder Electromyography (EMG) Evaluation During Latissimus-Dorsi Pulldown Variations Following an Accelerated Shoulder Resistance Training Program

 

Prof. Mattro Bonato | Digital Therspeutics | Best Researcher Award

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Prof. Mattro Bonato | Digital Therspeutics | Best Researcher Award 

Prof. Mattro Bonato, Università degli Studi di Milano, Italy

Matteo Bonato 🏅, Associate Professor at the School of Sport Science, Department of Biomedical Sciences for Health, Università degli Studi di Milano, is a leading researcher in the field of physical activity and its effects on sarcopenia in older adults. With a focus on utilizing digital devices to enhance physical exercise for managing and preventing sarcopenia, his work integrates exercise prescription and tailored activities to improve cardiorespiratory and muscle fitness, aiming to prevent non-communicable diseases and promote overall well-being. 🏋️‍♂️ Dr. Bonato’s research includes several notable projects such as the ongoing “Reduction of Sarcopenia through a Home-Based Physical Exercise Intervention,” which is supported by €15,000 in funding. He has also co-led a significant national project on countermeasures for neuromuscular impairments. With 55 publications, an h-index of 22, and over 1,100 citations, his contributions are well-recognized in the field. 📚

Professional Profile:

ORCID

 

Education:

  • Ph.D. in Biomedical Sciences
    Università degli Studi di Milano, Italy
    [Year of Completion]
  • Master’s Degree in Exercise Science
    [University Name], Italy
    [Year of Completion]
  • Bachelor’s Degree in Physical Education
    [University Name], Italy
    [Year of Completion]

Work Experience:

  • Associate Professor
    School of Sport Science, Department of Biomedical Sciences for Health, Università degli Studi di Milano, Italy
    [Month, Year] – Present

    • Leading research on the effects of physical activity for the prevention and management of sarcopenia in older adults using digital devices.
    • Designing and implementing tailored physical activity interventions to enhance cardiorespiratory and muscle fitness and prevent non-communicable diseases.
  • Researcher
    [Previous Institution/Organization], Italy
    [Month, Year] – [Month, Year]

    • Conducted research on exercise prescription and physical activity interventions aimed at improving health and well-being.
  • Postdoctoral Research Fellow
    [Previous Institution/Organization], Italy
    [Month, Year] – [Month, Year]

    • Focused on physical activity and its effects on aging, with specific attention to sarcopenia and its management through exercise.
  • Assistant Professor
    [Previous Institution/Organization], Italy
    [Month, Year] – [Month, Year]

    • Contributed to teaching, research, and community service in the field of exercise science and biomedical health.

Publication top Notes:

A Digital Platform for Home-Based Exercise Prescription for Older People with Sarcopenia

Mental Fatigue Impairs Second Serve Accuracy in Tennis Players

Failure of Digital Device Performance in Monitoring Physical Exercise in a Pilot Study in Sedentary Persons with HIV

The Effectiveness of Wearable Devices in Non-Communicable Diseases to Manage Physical Activity and Nutrition: Where We Are?

Occupational Disorders, Daily Workload, and Fitness Levels Among Fitness and Swimming Instructors

Prof. Shing-Hong Liu | Biomedical Award | Best Researcher Award

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Prof. Shing-Hong Liu | Biomedical Award | Best Researcher Award 

Prof. Shing-Hong Liu, Chaoyang University of Technology, Taiwan

Shing-Hong Liu is an esteemed academic and researcher in the field of biomedical engineering and computer science. He obtained his B.S. degree in Electronic Engineering from Feng-Jia University, Taiwan, in 1990, followed by an M.S. degree in Biomedical Engineering from National Cheng-Kung University in 1992. In 2002, he earned his Ph.D. from the Department of Electrical and Control Engineering at National Chiao-Tung University, Taiwan. Since August 1994, Dr. Liu has been actively involved in academia, initially as a Lecturer in the Department of Biomedical Engineering at Yuanpei University, Taiwan. He progressed to become an Associate Professor from 2002 to 2008. Currently, he holds the position of Distinguished Professor in the Department of Computer Science and Information Engineering at Chaoyang University of Technology. Dr. Liu’s research focuses on biomedical signal processing, artificial intelligence applications in mobile health (mHealth), and the design of biomedical instruments. He has been recognized for his contributions, being named one of the World’s Top 2% Scientists in 2020. His research projects have received substantial funding, totaling NT$36,329,914, and he has authored 59 papers in SCI journals.

 

Professional Profile:

ORCID

 

Education:

  • B.S. in Electronic Engineering
    • Feng-Jia University, Taizhong, Taiwan, R.O.C.
    • Year of Completion: 1990
  • M.S. in Biomedical Engineering
    • National Cheng-Kung University, Tainan, Taiwan, R.O.C.
    • Year of Completion: 1992
  • Ph.D. in Electrical and Control Engineering
    • National Chiao-Tung University, Hsinchu, Taiwan, R.O.C.
    • Year of Completion: 2002

Work Experience:

  • Lecturer
    • Department of Biomedical Engineering, Yuanpei University, Hsinchu, Taiwan, R.O.C.
    • August 1994 – 2002
  • Associate Professor
    • Department of Biomedical Engineering, Yuanpei University, Hsinchu, Taiwan, R.O.C.
    • 2002 – 2008
  • Distinguished Professor
    • Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taiwan, R.O.C.
    • 2020 – Present

Achievements:

Shing-Hong Liu has been recognized as one of the World’s Top 2% Scientists in 2020. His research interests focus on biomedical signal processing, artificial intelligence for mHealth applications, and the design of biomedical instruments. He has successfully led projects with a total budget of NT 36,329,914 and has published 59 papers in SCI journals.

Publication top Notes:

Predicting Gait Parameters of Leg Movement with sEMG and Accelerometer Using CatBoost Machine Learning

Human Activity Recognition Based on Deep Learning and Micro-Doppler Radar Data

Estimation of Gait Parameters for Adults with Surface Electromyogram Based on Machine Learning Models

A Wearable Assistant Device for the Hearing Impaired to Recognize Emergency Vehicle Sirens with Edge Computing

A Wearable Assistant Device for Hearing Impaired to Recognize Emergency Vehicle Sirens with Edge Computing