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

 

Haripriya | Complex dynamical Networks | Best Researcher Award

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Haripriya | Complex dynamical Networks | Best Researcher Award

Vellore Institute of Technology | India

Author Profile

Scopus

BIOGRAPHY OF M. HARIPRIYA: A RISING SCHOLAR IN MATHEMATICAL SCIENCES

EARLY ACADEMIC PURSUITS

M. Haripriya’s journey into the world of mathematics began with strong academic foundations. She completed her SSLC in 2012 from GRG Matric. Higher Secondary School , followed by her HSC from Mani Higher Secondary School in 2014. Her passion for numbers and logical reasoning guided her to pursue a Bachelor of Science in Mathematics at Nirmala College for Women, Coimbatore, where she graduated in 2017. Demonstrating a deep interest in education, she earned a Bachelor of Education (B.Ed) in Mathematics from Avinashilingam Institute, Coimbatore, in 2019. Her academic momentum continued as she completed her Master of Science (M.Sc) in Mathematics at PSGR Krishnammal College for Women, Coimbatore.

PROFESSIONAL ENDEAVORS

Haripriya’s academic career is closely aligned with her commitment to both teaching and research. While she has not explicitly listed professional teaching roles, her academic path, particularly her B.Ed qualification, suggests a foundation in pedagogy and mathematics instruction. Her current pursuit of a Ph.D. in Mathematics at the Vellore Institute of Technology (VIT), Chennai, beginning in 2022, marks her serious foray into scholarly research and higher education leadership.

CONTRIBUTIONS AND RESEARCH FOCUS ON COMPLEX DYNAMICAL NETWORKS

Haripriya’s research delves into Complex Dynamical Networks, with a focus on Synchronization, Lyapunov Stability, and Control Theory. These topics are at the intersection of applied mathematics, systems engineering, and theoretical physics, and play a critical role in modern technology such as neural networks, power grids, and communication systems. Her notable contribution includes a scholarly article titled: “Synchronization for coupling delayed complex dynamical networks in time-square-dependent looped-functionals via a new sampled-data control approach”, which reflects the novelty and technical depth of her work.

IMPACT AND INFLUENCE

Though early in her research journey, Haripriya’s work in the field of complex networks shows promising potential. By exploring advanced synchronization methods for delayed systems, she contributes to enhancing the stability and control mechanisms in interconnected systems—relevant in both scientific and industrial domains. Her work is expected to influence future research in control systems, intelligent networks, and robust systems design.

ACADEMIC CITES

While citation metrics are not provided yet, her research area is niche and rapidly expanding. As she continues to publish in reputed journals and present at conferences, her visibility in the academic world is bound to grow. Her foundational knowledge in mathematical theory, paired with practical research tools like MATLAB and LaTeX, positions her well for impactful scholarly output.

PERSONAL TRAITS AND SKILLS

M. Haripriya stands out not only for her academic proficiency but also for her personal and professional skills. She is known for her problem-solving ability, good communication, teamwork, time management, and active participation—all crucial traits for a successful researcher. Her computer proficiency in MATLAB and LaTeX further enhances her ability to conduct simulations and prepare high-quality scientific documentation.

LEGACY AND FUTURE CONTRIBUTIONS

With her rigorous academic background and active research in cutting-edge mathematical domains, Haripriya is poised to make lasting contributions to the field of dynamical systems and control theory. Her dedication to both learning and innovation reflects her potential to become a thought leader and educator. As she continues her Ph.D., the academic community can anticipate impactful research publications, international collaborations, and valuable contributions to interdisciplinary applications in science and engineering.

SUMMARY: A MATHEMATICIAN IN THE MAKING

In summary, M. Haripriya exemplifies the qualities of a dedicated academic and researcher. Her educational journey, domain expertise, and research aspirations make her a strong candidate for accolades such as the Best Researcher Award. With a blend of theoretical knowledge, practical application, and an unwavering commitment to growth, she is undeniably on a path toward academic excellence and societal impact.

NOTABLE PUBLICATIONS

"Synchronization for coupling delayed complex dynamical networks in time-square-dependent looped-functionals via a new sampled-data control approach" 

  • Author: Haripriya Muralikrishnan, N. Padmaja, E. Umamaheswari, Lakshmanan Shanmugam
  • Journal: Neurocomputing
  • Year: 2025

 

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.