Zilan Bazancir-Apaydin | Network Properties | Research Excellence Award

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Dr. Zilan Bazancir-Apaydin | Network Properties | Research Excellence Award

Ankara Medipol University | Turkey

Dr. Zilan Bazancir-Apaydin is an accomplished academic in the field of Physiotherapy and Rehabilitation with a strong background in education, research, and clinical sciences. She earned her PhD in Physical Therapy and Rehabilitation from Hacettepe University, Ankara, following her MSc from the Institute of Health Sciences at Inonu University, Malatya. Dr. Bazancir-Apaydin completed her undergraduate studies in Physiotherapy and Rehabilitation at Gazi University, Ankara. She is currently serving as an Assistant Professor at Ankara Medipol University, a position she has held since August 2022. Prior to this, she worked as a Research Assistant at Hacettepe University and Inonu University, gaining extensive experience in academic research and teaching. Her research interests focus on network properties and measures, contributing to the advancement of analytical approaches in rehabilitation sciences.

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Featured Publications

The profile beyond leg pain: On the basis of central sensitization, kinesiophobia, and body awareness in patients with chronic venous disease

– Phlebology: The Journal of Venous Disease, 2025
Comparison of plantar pressure distribution patterns of patients with ankylosing spondylitis and asymptomatic healthy individuals: A cross-sectional study

– Irish Journal of Medical Science, 2025
Immediate effects of Compressive Myofascial Release versus Talocrural Joint Mobilization on passive mechanical properties and functional outcomes after Achilles tendon repair

– Physiotherapy Theory and Practice, 2025
Early strength gains in eccentric hip adduction and adduction-to-abduction ratio following an 8-week Copenhagen Adduction Exercise in elite adolescent taekwondo athletes

– Journal of Bodywork and Movement Therapies, 2025
Assessing the impact of dysphagia on quality of life and determining SWAL-QOL cut-off scores in diabetes mellitus patients: A data mining approach

– Journal of Diabetes and Its Complications, 2025

OJO Olufisayo Emmanuel | Graph Data Structures | Best Researcher Award

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Mr. OJO Olufisayo Emmanuel | Graph Data Structures | Best Researcher Award

Durban University of Technology | South Africa

Engr. OJO Olufisayo Emmanuel, R.Engr., IEng (UK), MSc, B.Eng (Hons), M.I.E.T, MNSE, is an accomplished Electromechanical and Water Engineer, as well as a seasoned Project Manager, with extensive experience in institutional infrastructural development projects. He has held key roles in several international initiatives funded by organizations such as the World Bank, AFD, EBRD, USAID/E-WASH/RTI, and atmosfair gGmbH’s Carbon Mitigation projects in Nigeria. Currently serving with CKW Environment Limited, an engineering consultancy specializing in Water and Sanitary Engineering, he is deeply involved in the design of water treatment facilities, civil and electromechanical infrastructures, hydraulic design and optimization of water distribution systems, environmental impact assessments, and construction supervision. With strong technical and commercial expertise, Engr. OJO combines strategic project management skills with deep engineering insight, providing consultancy services across all project phases-from design and procurement to supervision, monitoring, evaluation, and project delivery-ensuring quality, compliance, and cost efficiency.

Profiles: Orcid

Featured Publications

"Innovative Recovery Methods for Metals and Salts from Rejected Brine and Advanced Extraction Processes-A Pathway to Commercial Viability and Sustainability in Seawater Reverse Osmosis Desalination", Olufisayo E. Ojo; Olanrewaju A. Oludolapo, Water, 2025.

"Cost–Benefit and Market Viability Analysis of Metals and Salts Recovery from SWRO Brine Compared with Terrestrial Mining and Traditional Chemical Production Methods", Olufisayo E. Ojo; Olanrewaju A. Oludolapo, Water, 2025.

"Modeling A Reverse Osmosis Desalination Plant: A Practical Framework Using Wave Software", Olufisayo Emmanuel Ojo; Olanrewaju Akanni Oludolapo, Science, Engineering and Technology, 2025.

"A Review of Renewable Energy Powered Seawater Desalination Treatment Process for Zero Waste", Olufisayo Emmanuel Ojo; Olanrewaju Akanni Oludolapo, Water, 2024.

Kexue Sun | Graph Data Structures | Best Researcher Award 

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Prof. Kexue Sun | Graph Data Structures | Best Researcher Award 

Nanjing University of Posts and Communications | China

Prof. Kexue Sun is a distinguished Professor at the School of Electronic and Optical Engineering and the School of Flexible Electronics (Future Technologies), Nanjing University of Posts and Telecommunications (NJUPT). He earned his Ph.D. in Acoustics from the School of Physics, Nanjing University (2012–2018), an M.E. in Software Engineering from the Beijing University of Posts and Telecommunications (2004–2006), and a B.E. in Electronic Information Engineering from the Artillery Academy of the Chinese People's Liberation Army, Hefei (1998–2002). Prof. Sun has served NJUPT in various academic roles, including Lecturer (2007–2013), Associate Professor (2013–2020), and currently as Professor since 2020, with international experience as a Visiting Scholar at the Chinese University of Hong Kong (2018–2019). He is an active member of IEEE, a technical expert for high-tech enterprises in Jiangsu Province, and a review expert for the Degree and Graduate Education Development Center of the Ministry of Education, while also serving on the Specialized Committee on Biomedical Information Detection and Processing of the Jiangsu Society of Biomedical Engineering. His research spans Electronic Technology, FPGA Applications, Electrical and Electronic Experiments, Optoelectronic Information Materials, and Acoustic Devices. Prof. Sun has participated in over ten national and enterprise research projects, co-authored one monograph and seven textbooks, published more than 100 academic papers, and holds over 20 authorized Chinese invention patents. Additionally, he has made significant contributions to higher education research and teaching reform, leading more than ten national and provincial projects, publishing over 20 papers in this field, and earning prestigious honors such as the Teaching Model Award, the First Prize for Teaching Achievements at NJUPT, and the Special Prize for Teaching Achievements of Jiangsu Province.

Profiles: Orcid ID

Featured Publications

"Pressure Vessel Design Problem Using Improved Gray Wolf Optimizer Based on Cauchy Distribution"

"Heart Sound Classification Network Based on Convolution and Transformer"

"Optimization of Indoor Luminaire Layout for General Lighting Scheme Using Improved Particle Swarm Optimization"

Nhue Do | Graph Analytics | Best Researcher Award

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Dr. Nhue Do | Graph Analytics | Best Researcher Award

Wake Forest University School of Medicine | United States

Author Profile

Scopus

Early Academic Pursuits

Dr. Nhue Do’s academic journey reflects an exceptional blend of medicine, surgery, and leadership. He earned his Doctor of Medicine degree from the University of Southern California, Keck School of Medicine, followed by an MBA from Johns Hopkins University’s Carey Business School, combining medical expertise with management acumen. His early postgraduate training at Harvard Medical School and Beth Israel Deaconess Medical Center exposed him to general surgery, transplantation, and cardiothoracic surgery, setting a strong foundation for a career dedicated to advanced surgical care and innovation.

Professional Endeavors

Dr. Do’s professional career demonstrates an impressive trajectory across leading academic and medical institutions. His appointments span Johns Hopkins University, Vanderbilt University Medical Center, and Advocate Children’s Hospital, where he currently serves as a Congenital Cardiothoracic Surgeon and Surgical Director of the Pediatric Mechanical Circulatory Support Program. His leadership roles, including Associate Vice Chair in Global Surgery at Vanderbilt, showcase his dedication not only to surgical excellence but also to advancing global health initiatives.

Contributions and Research Focus

Throughout his career, Dr. Do has contributed significantly to advancing congenital cardiothoracic surgery and pediatric heart transplantation. He has pioneered clinical protocols such as the use of fresh whole blood, ventricular assist devices, Impella technology, and SherpaPak in pediatric cardiac surgery. His research extends into transplantation, circulatory support devices, and surgical quality improvement. Additionally, his involvement in NIH-funded research and editorial responsibilities highlights his academic commitment to shaping the future of cardiothoracic surgery.

Impact and Influence

Dr. Do’s influence extends beyond the operating room. He has served on advisory boards, national review committees, and editorial boards, ensuring his expertise informs both clinical standards and future research directions. His mentorship in global health programs, leadership in surgical safety councils, and conference organization at national and international levels have amplified his voice in the field of pediatric and congenital heart surgery.

Academic Citations and Recognition

Dr. Do’s scholarly presence is reflected in his active role as a peer reviewer for leading journals such as The Journal of Thoracic and Cardiovascular Surgery and European Journal of Cardio-Thoracic Surgery. His academic honors-including multiple fellowships, scholarships, and leadership programs—underscore his recognition by top medical and surgical bodies worldwide. These achievements reflect his standing as both a clinician and a thought leader in cardiac surgery.

Legacy and Future Contributions

As a board-certified thoracic and congenital heart surgeon with extensive leadership and research experience, Dr. Do is poised to shape the next generation of surgical practice. His ongoing work in pediatric circulatory support and heart transplantation will likely influence future standards of care. Beyond clinical practice, his involvement in mentorship, global health initiatives, and surgical innovation ensures a legacy of advancing both patient outcomes and the broader healthcare landscape.

Conclusion

In summary, Dr. Nhue Do embodies the qualities of an outstanding clinician, educator, and researcher. His career reflects a rare integration of surgical excellence, academic rigor, and global leadership. With his ongoing contributions to congenital cardiothoracic surgery, transplantation, and healthcare innovation, he stands as a role model whose impact will continue to shape the fields of pediatric cardiac surgery and global surgical health for years to come.

Notable Publications

"Forty-eight-hour cold-stored whole blood in paediatric cardiac surgery: Implications for haemostasis and blood donor exposures" 

  • Author: Kiskaddon AL, Andrews J, Josephson CD, Kuntz MT, Tran D, Jones J, Kartha V, Do NL
  • Journal: Vox Sang
  • Year: 2024

 

Linfu Jiang | Network Analysis | Best Researcher Award

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Dr. Linfu Jiang | Network Analysis | Best Researcher Award

Zhejiang Ocean University | China

Author Profile

Scopus

Orcid ID

EARLY ACADEMIC PURSUITS

Dr. Linfu Jiang's academic journey began with a strong foundation in data science and engineering, which led him to specialize in the field of predictive modeling of medical data. His early academic years were marked by an interdisciplinary approach that combined elements of healthcare, statistics, and artificial intelligence. His education fostered a deep interest in the practical implications of machine learning and statistical methods for improving patient care, laying the groundwork for his future endeavors in intelligent health systems and clinical decision support.

PROFESSIONAL ENDEAVORS

Dr. Jiang is currently serving as a faculty member at the School of Information Engineering, Zhejiang Ocean University, where he engages in teaching and advanced research. Since joining in August 2023, he has taken a proactive role in integrating health informatics and data analytics into academic curricula while mentoring students in real-world problem-solving through data. Beyond academia, Dr. Jiang has been involved in industry collaborations, offering consultancy services in the development of predictive health platforms, community-based disease screening systems, and smart medical technologies.

CONTRIBUTIONS AND RESEARCH FOCUS ON NETWORK ANALYSIS

Dr. Jiang’s research is distinguished by his contributions to data-driven clinical prediction models that integrate both medical and social health factors. He focuses particularly on chronic disease management, intelligent health systems, and the application of machine learning for early disease detection. Notably, he co-authored and served as the first corresponding author on a groundbreaking SCI-indexed paper examining social relationships and their role in motoric cognitive risk syndrome, which utilized network analysis within a multilayer health ecology model. Another significant contribution is his work on the PCHD-TabNet, a novel deep learning model for ten-year prediction of coronary heart disease, which underscores his expertise in integrating health data with AI-driven insights.

IMPACT AND INFLUENCE

Dr. Jiang's work holds significant practical value for public health, especially in the context of community-level healthcare interventions. His research has led to the development of personalized screening tools, predictive algorithms, and smart health management platforms that are being translated into real-world healthcare applications. His emphasis on model interpretability and clinical relevance makes his work not only academically significant but also impactful in policy and practice. His collaborations with clinicians, data scientists, and public health professionals have enabled the seamless application of theory into meaningful healthcare solutions.

ACADEMIC CITES

Dr. Jiang’s scholarly influence is evident through his publications in high-impact journals. He has authored:

  • “Central and Bridging Roles of Social Relationships Within the Multilayer Health Ecology Model in Motoric Cognitive Risk Syndrome” published in Journal of the American Medical Directors Association (2025), with DOI: [10.1016/j.jamda.2025.105771], a JCR Q1 paper.

  • “Ten-Year Prediction of Coronary Heart Disease Based on PCHD-TabNet”, published in Data Analysis and Knowledge Discovery (2023), which showcases the integration of AI with health data analytics.

These contributions reflect the academic community’s growing recognition of his work, especially in healthcare AI and social determinants of health.

LEGACY AND FUTURE CONTRIBUTIONS

Looking ahead, Dr. Jiang is poised to make even greater contributions to precision medicine and digital health transformation. With three patents currently under process on predictive algorithms for chronic disease management, he continues to push the boundaries of innovation. His vision includes expanding research into social determinants of health, refining models for real-time disease prediction, and enhancing community health infrastructures using AI and network-based health ecology models. His commitment to multidisciplinary collaboration ensures that his future work will remain relevant, scalable, and deeply rooted in patient-centric outcomes.

OTHER HIGHLIGHTS

  • Industry Engagement: Active involvement in predictive health modeling for smart systems and community care.

  • Collaborative Research: Interdisciplinary work with public health experts, clinicians, and data scientists.

  • Teaching and Mentorship: Nurturing future researchers in intelligent health systems at Zhejiang Ocean University.

  • Professional Development: Actively seeking memberships in reputed medical informatics societies to extend professional influence and networks.

NOTABLE PUBLICATIONS

"Central and Bridging Roles of Social Relationships Within the Multilayer Health Ecology Model in Motoric Cognitive Risk Syndrome: A Network Analysis" 

  • Author: Liming Su; Linfu Jiang; Yiting Ma; Zhonghua Wang; Xiaoying Wang; Yang Lin
  • Journal: Journal of the American Medical Directors Association
  • Year: 2025

"Ten-Year Prediction of Coronary Heart Disease Based on PCHD-TabNet" 

  • Author: Linfu Jiang
  • Journal: Data Analysis and Knowledge Discovery
  • Year: 2023

 

Alireza Rezvanian | Complex Social Networks | Network Science Excellence Award

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Assist. Prof. Dr. Alireza Rezvanian | Complex Social Networks | Network Science Excellence Award

Assistant Professor at University of Science and Culture, Iran📖

Dr. Alireza Rezvanian is an accomplished academic and researcher, serving as an Assistant Professor at the University of Science and Culture (USC) in Tehran, Iran. He holds multiple editorial positions, including Associate Editor for journals such as CAAI Transactions on Intelligence Technology, Human-Centric Computing and Information Sciences, The Journal of Engineering, and Data in Brief. Dr. Rezvanian is actively involved in various professional and scientific activities, including serving as the Director of Information and Scientific Resources at USC and contributing to the IEEE Computer Society Iran Chapter.

Profile

Scopus Profile

Orcid Profile

Google Scholar Profile

Education Background🎓

Dr. Rezvanian completed his Ph.D. in Computer Engineering from Amirkabir University of Technology (Tehran Polytechnic) in 2016, under the guidance of Dr. Mohammad Reza Meybodi. His doctoral thesis focused on “Stochastic Graphs for Social Network Analysis.” He holds a Master’s degree in Computer Engineering from Islamic Azad University of Qazvin (2010), where he specialized in improving Artificial Immune System algorithms using Learning Automata for dynamic environments. He also earned a Bachelor’s degree in Computer Engineering from Bu-Ali Sina University of Hamedan (2007).

Professional Experience🌱

Dr. Rezvanian has extensive teaching and research experience across multiple prestigious institutions. Currently, he is an Assistant Professor at the University of Science and Culture, Tehran. He is also an Adjunct Professor at Amirkabir University of Technology, the University of Tehran, and Tarbiat Modares University. His leadership roles include serving as the Head of the Computer Engineering Department at USC (2021-2023) and as the Director of Information and Scientific Resources at USC since 2023. He has previously held research positions at the Institute for Research in Fundamental Sciences (IPM) and the Niroo Research Institute (NRI).

Research Interests🔬

Dr. Rezvanian’s research interests lie in the areas of complex networks, social network analysis, machine learning, learning automata, data mining, and soft computing. His work focuses on the application of evolutionary algorithms, image processing, and stochastic graphs for modeling social networks. His research aims to provide insights into real-world applications through innovative techniques in network analysis and machine learning.

Author Metrics

Dr. Rezvanian has a strong academic presence, with an H-index of 26 on Google Scholar (2024), 23 on Scopus, and 18 on Web of Science. He has authored and co-authored numerous research articles in renowned journals and conferences, contributing significantly to the fields of computer science, machine learning, and network analysis. His work has earned him recognition and a substantial citation count, further solidifying his impact in academia.

Publications Top Notes 📄

1. Robust Fall Detection Using Human Shape and Multi-Class Support Vector Machine

  • Authors: H. Foroughi, A. Rezvanian, A. Paziraee
  • Conference: Sixth Indian Conference on Computer Vision, Graphics & Image Processing (ICVGIP 2008)
  • Year: 2008
  • Summary: This paper focuses on a robust fall detection system utilizing human shape and a multi-class support vector machine (SVM) for classifying human body shapes and movements. The system aims to effectively detect falls, which is crucial in healthcare applications like elderly care.

2. Sampling from Complex Networks Using Distributed Learning Automata

  • Authors: A. Rezvanian, M. Rahmati, M.R. Meybodi
  • Journal: Physica A: Statistical Mechanics and its Applications
  • Volume: 396
  • Pages: 224–234
  • Year: 2014
  • Summary: This paper introduces a method for sampling complex networks using distributed learning automata (LA), a technique inspired by machine learning algorithms. The approach aims to enhance network analysis by efficiently exploring and sampling complex graph structures.

3. Minimum Positive Influence Dominating Set and Its Application in Influence Maximization: A Learning Automata Approach

  • Authors: M.M.D. Khomami, A. Rezvanian, N. Bagherpour, M.R. Meybodi
  • Journal: Applied Intelligence
  • Volume: 48 (3)
  • Pages: 570–593
  • Year: 2018
  • Summary: This paper presents a novel approach for solving the Minimum Positive Influence Dominating Set (MPIDS) problem, using learning automata for influence maximization in social networks. The proposed method addresses the optimization challenges in selecting influential nodes for spreading information effectively in network-based applications.

4. CDEPSO: A Bi-population Hybrid Approach for Dynamic Optimization Problems

  • Authors: J.K. Kordestani, A. Rezvanian, M.R. Meybodi
  • Journal: Applied Intelligence
  • Volume: 40 (4)
  • Pages: 682–694
  • Year: 2014
  • Summary: The paper introduces CDEPSO (Cognitive Dynamic Evolutionary Particle Swarm Optimization), a hybrid approach that integrates bi-population evolutionary algorithms to address dynamic optimization problems. The method aims to improve the solution quality and efficiency in environments where the optimization landscape changes over time.

5. Cellular Edge Detection: Combining Cellular Automata and Cellular Learning Automata

  • Authors: M. Hasanzadeh Mofrad, S. Sadeghi, A. Rezvanian, M.R. Meybodi
  • Journal: AEU-International Journal of Electronics and Communications
  • Volume: 69 (9)
  • Pages: 1282–1290
  • Year: 2015
  • Summary: This paper explores the combination of cellular automata (CA) and cellular learning automata (CLA) for edge detection in image processing. The approach leverages the computational power of CA and CLA to enhance the edge detection process in digital images, contributing to improvements in image recognition and processing tasks.

Conclusion

Dr. Alireza Rezvanian is highly deserving of the Network Science Excellence Award due to his pioneering contributions to the field of complex networks and social network analysis. His research not only provides innovative methods for understanding and optimizing networks but also demonstrates a strong academic leadership role in advancing network science. With his continued focus on interdisciplinary research and industry collaboration, Dr. Rezvanian is poised to make even greater contributions to the field of network science, making him a worthy recipient of this prestigious award.