Shoujun Zhou | Artificial Intelligence | Best Scholar Award

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Prof. Shoujun Zhou | Artificial Intelligence | Best Scholar Award

Research Professor at Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China

Prof. Shoujun Zhou is a distinguished biomedical engineering researcher and a leading figure in the field of medical robotics and image-guided therapy. He currently serves as a specially appointed research professor at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, and concurrently holds a professorship at the National Institute for High-Performance Medical Devices. Over his career, Prof. Zhou has led and contributed to numerous national and provincial-level scientific research projects, focusing on developing interventional surgical robotics and advanced medical imaging technologies. His leadership in this interdisciplinary field has positioned him at the forefront of integrating artificial intelligence with minimally invasive therapeutic solutions.

Profile

Orcid

Education

Prof. Zhou’s academic journey began with a Bachelor’s degree in Test and Control from the Air Force Engineering University (1989–1993). He then earned a Master’s degree in Communication and Information Systems from Lanzhou University (1997–2000), further refining his technical expertise. His academic pursuits culminated in a Ph.D. in Biomedical Engineering from Southern Medical University (2001–2004). This multidisciplinary educational background laid a solid foundation for his future contributions in medical imaging, robotics, and computational modeling.

Experience

With over three decades of professional experience, Prof. Zhou has served in multiple prestigious institutions. From 1993 to 2001, he worked as an engineer in the 94921 Military Unit, followed by a postdoctoral tenure at Beijing Institute of Technology. He transitioned to industry in 2007 as an enterprise postdoctoral researcher at Shenzhen Haibo Technology Co., Ltd., and later joined the 458 Hospital of the PLA as a senior engineer. Since 2010, he has been a principal investigator and research professor at SIAT, where he leads a dedicated research team working on the convergence of robotics, imaging, and AI for medical applications.

Research Interest

Prof. Zhou’s research primarily focuses on interventional surgical robots, image-guided therapy, and medical image analysis. He is particularly interested in developing intelligent, minimally invasive systems that combine AI algorithms with real-time imaging for precise diagnostics and interventions. His work includes modeling and segmentation of vascular structures, semi-supervised learning techniques in medical imaging, and the development of surgical robots tailored for procedures such as liver tumor ablation and cardiovascular interventions. He is also actively involved in improving navigation systems that reduce or eliminate radiation exposure in image-guided procedures.

Award

Prof. Zhou’s contributions have been widely recognized both nationally and internationally. He was honored with the “Best Researcher Award” at the Global Awards on Artificial Intelligence and Robotics in 2022, organized by ScienceFather. He also received a Silver Medal in the Global Medical Robot Innovation Design Competition in 2019 for his work on a vascular interventional robotic system. His earlier work earned the Second Prize of Guangdong Provincial Science and Technology Progress Award in 2009 and contributed to a project that received a First-Class Prize in Science and Technology Progress from the Ministry of Education in 2006. These accolades reflect his sustained excellence and impact in the field of medical technology.

Publication

Prof. Zhou has authored over 100 scientific papers, including several published in top-tier journals. Selected key publications include:

  1. Zhang Z. et al. (2024). “Verdiff-Net: A Conditional Diffusion Framework for Spinal Medical Image Segmentation,” Bioengineering, 11(10):1031 – cited in spinal image AI segmentation studies.

  2. Zhang X. et al. (2024). “Automatic Segmentation of Pericardial Adipose Tissue from Cardiac MR Images,” Medical Physics, DOI:10.1002/mp.17558 – referenced for semi-supervised MR image segmentation.

  3. Tian H. et al. (2024). “EchoSegDiff: a diffusion-based model for left ventricular segmentation,” Medical & Biological Engineering & Computing, DOI:10.1007/s11517-024-03255-0 – cited in cardiac echocardiography image modeling.

  4. Li J. et al. (2024). “DiffCAS: Diffusion based Multi-attention Network for 3D Coronary Artery Segmentation,” Signal, Image and Video Processing, DOI:10.1007/s11760-024-03409-5 – relevant in coronary CT imaging analysis.

  5. Wang K.N. et al. (2024). “SBCNet: Scale and Boundary Context Attention for Liver Tumor Segmentation,” IEEE Journal of Biomedical and Health Informatics, 28(5):2854-2865 – cited in liver tumor segmentation research.

  6. Xiang S. et al. (2024). “Automatic Delineation of the 3D Left Atrium from LGE-MRI,” IEEE Journal of Biomedical and Health Informatics, DOI:10.1109/JBHI.2024.3373127 – frequently cited in atrial structural analysis.

  7. Miao J. et al. (2024). “SC-SSL: Self-correcting Collaborative and Contrastive Co-training,” IEEE Transactions on Medical Imaging, 43(4):1347-1364 – referenced in semi-supervised medical image learning.

Conclusion

Prof. Zhou’s work exemplifies the synergy between engineering and medical science, enabling significant advances in minimally invasive diagnosis and treatment. Through his persistent innovation in surgical robotics and medical image computing, he has made a profound impact on the evolution of intelligent healthcare technologies. His dedication to mentoring young researchers and contributing to national and provincial projects reflects a commitment not only to scientific discovery but also to the translation of research into clinical and industrial applications. With a career marked by excellence in research, education, and innovation, Prof. Zhou continues to be a pivotal figure shaping the future of intelligent medicine.

Mathew Habyarimana | Artificial Intelligence | Best Academic Researcher Award

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Dr. Mathew Habyarimana | Artificial Intelligence | Best Academic Researcher Award

Research Scholar at Durban University of Technology, South Africa

Mathew Habyarimana, Ph.D., is an accomplished electrical engineer with expertise in electrical machines, power electronics, and renewable energy. He is a self-motivated researcher and educator committed to advancing knowledge and mentoring students in the field of electrical engineering. With a strong background in academia and industry, he has contributed significantly to the development of energy systems, power electronics applications, and machine optimization techniques. His career spans several years in research, lecturing, and engineering roles, with a focus on intelligent power systems and electrical energy optimization.

Profile

Scopus

Education

Dr. Habyarimana obtained his Ph.D. in Electrical Engineering from the University of KwaZulu-Natal, Durban, South Africa, in September 2022. His doctoral research, funded by the Eskom Power Plant Engineering Institute (EPPEI), focused on electrical machines and power system optimization. Prior to this, he completed his MSc. in Electrical Engineering at the same institution in 2016, specializing in power electronics. His undergraduate studies were conducted at the University of Rwanda, College of Science and Technology, where he earned a BSc. in Electrical Engineering with a focus on renewable energy. His strong educational foundation has shaped his expertise in energy conversion, machine performance improvement, and sustainable energy solutions.

Experience

Dr. Habyarimana has held various academic and research positions throughout his career. Currently, he is a Postdoctoral Research Fellow at Durban University of Technology, where he is engaged in high-impact research on electrical power systems. Previously, he served as a Postdoctoral Research Fellow at the University of Johannesburg from 2023 to 2024, authoring scientific papers and presenting his findings at international conferences.

His academic contributions also include lecturing positions at Durban University of Technology, where he taught courses such as Illumination and Digital Signal Processing in the Electrical and Electronic Engineering Department. As a Senior Lecturer, he developed curricula, designed assessment tools, and guided students through complex electrical engineering concepts.

Before transitioning into academia, Dr. Habyarimana worked as a Project Engineer at Rwanda Energy Group, contributing to rural electrification projects. Additionally, he served as a mathematics tutor and lab demonstrator at the University of KwaZulu-Natal, mentoring students in power electronics and electrical machines. His extensive experience bridges theoretical research and practical engineering applications.

Research Interests

Dr. Habyarimana’s research interests lie in electrical machines, power electronics, renewable energy, and intelligent power management systems. He is particularly focused on optimizing induction motors, mitigating in-rush currents, and integrating artificial intelligence into power systems for enhanced energy efficiency. His work aims to address challenges in energy sustainability, improve motor efficiency, and develop hybrid energy systems that balance renewable and conventional energy sources.

Awards

Dr. Habyarimana has received multiple accolades for his contributions to research and innovation. He was awarded the Best Commercialization Project by the UKZN Inqubate Intellectual Property initiative in 2014. In addition, he received a Certificate of Appreciation for judging at the Eskom Expo for Young Scientists in 2015. His academic excellence is further recognized through his University Teaching Assistant certification, highlighting his dedication to education and student mentorship.

Publications

M. Habyarimana, G. Sharma, P. N. Bokoro, and K. A. Ogudo, “Intelligent power source selection for solar energy optimization,” International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, 2024.

M. Habyarimana, G. Sharma, and P. N. Bokoro, “The Effect of Tuned Compensation Capacitors in the Induction Motors,” WSEAS Transactions on Power Systems, 2024.

Habyarimana, M., Dorrell, D. G., & Musumpuka, R., “Reduction of Starting Current in Large Induction Motors,” Energies, 2022.

Habyarimana, M., Musumpuka, R., & Dorrell, D. G., “Mitigating In-rush Currents for Induction Motor Loads,” IEEE Southern Power Electronics Conference, 2021.

Habyarimana, M., & Dorrell, D. G., “Methods to reduce the starting current of an induction motor,” IEEE International Conference on Power, Control, Signals and Instrumentation Engineering, 2017.

Venugopal, C., Subramaniam, P. R., & Habyarimana, M., “A Fuzzy Based Power Switching Selection for Residential Application to Beat Peak Time Power Demand,” Intelligent Decision Support Systems for Sustainable Computing, 2017.

Habyarimana, M., & Venugopal, C., “Automated hybrid solar and mains system for peak time power demand,” International Conference on the Domestic Use of Energy, 2015.

Conclusion

Dr. Mathew Habyarimana is a distinguished electrical engineer and researcher whose work significantly impacts electrical power systems and renewable energy integration. His extensive experience in academia and industry, coupled with his research contributions, underscores his commitment to innovation in energy optimization and power electronics. Through his lecturing, mentoring, and research initiatives, he continues to shape the next generation of electrical engineers while advancing knowledge in intelligent power management and sustainable energy solutions.

Diana Morales | Deep Learning | Best Researcher Award

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Dr. Diana Morales | Deep Learning | Best Researcher Award

Critical Care Fellow | University of Toronto | Canada

Dr. Diana Morales Castro, MD, MSc, is a renowned Costa Rican physician specializing in critical care medicine, echocardiography, and perioperative medicine. Currently serving as an Adult Critical Care Senior International Fellow at Toronto General Hospital, University Health Network, and University of Toronto, Dr. Morales Castro has an extensive academic and clinical background. With advanced training in critical care, anesthesiology, and echocardiography, her expertise has been shaped by prestigious fellowships and master’s programs in various global institutions, including the University of Toronto and University College London. She has contributed significantly to research in pharmacokinetics, critical care, and echocardiography, publishing in esteemed medical journals. Her dedication to education is evidenced by her role as a mentor for the European Diploma in Advanced Critical Care Echocardiography.

Profile

Scholar

Education

Dr. Morales Castro’s educational background is rooted in excellence and dedication to advancing medical knowledge. She graduated with a Licentiate in Medicine and Surgery from the University of Costa Rica in 2011, followed by a Specialty in Anesthesiology and Recovery in 2015 from the same institution. Seeking to deepen her knowledge in critical care, she completed a Master in Perioperative Medicine at University College London in 2018. Her journey continued with a series of fellowships, including the Adult Critical Care Medicine Fellowship and Adult Critical Care Echocardiography Fellowship at the University of Toronto in 2018 and 2020, respectively. Dr. Morales Castro further expanded her expertise by pursuing a Master in Pharmaceutical Sciences at the University of Toronto, which she is expected to complete in 2024.

Experience

Dr. Morales Castro’s clinical experience spans across several high-profile institutions in Costa Rica and Canada. She began her career as a General Physician at the El Caoba EBAIS in Costa Rica, where she served in mandatory social service. She then advanced to become an Attending Anesthesiologist at Trauma Hospital and Hospital Calderón Guardia, before further specializing in adult critical care at the University of Toronto. Her role as an Attending Intensivist at the National Transplant and ECMO Center in Costa Rica was a significant milestone, where she provided critical care to patients undergoing complex treatments like ECMO. Currently, she balances her work as an attending physician with her position as a mentor for advanced critical care echocardiography at the European Society of Intensive Care Medicine.

Research Interests

Dr. Morales Castro’s research primarily focuses on pharmacokinetics and pharmacodynamics in critically ill patients, particularly those undergoing extracorporeal membrane oxygenation (ECMO). Her work delves into optimizing sedative and anesthetic pharmacokinetics during critical illness and exploring the role of therapeutic drug monitoring for drugs like propofol and fentanyl in patients on ECMO. She also investigates the impact of echocardiography and ultrasound techniques in the management of critically ill patients, with a special interest in COVID-19-related complications. Her work not only contributes to improving clinical outcomes but also advances the education of healthcare providers through innovative teaching methods like self-learning videos in transthoracic echocardiography.

Awards

Dr. Morales Castro has received numerous accolades throughout her career, recognizing her excellence in research, education, and clinical care. She was awarded the 2023 Allan Spanier Award for the best education study on simulator-based echocardiography training. In 2022, she received the MD Program Teaching Award of Excellence from the Temerty Faculty of Medicine at the University of Toronto. Her dedication during the COVID-19 pandemic was recognized with a certificate from the Costa Rican Social Security. Further demonstrating her academic prowess, she received honors for her master’s degree in perioperative medicine from University College London in 2019 and honors for her specialty in anesthesiology from the University of Costa Rica in 2015.

Publications

Dr. Morales Castro has authored several impactful publications in leading medical journals, reflecting her research contributions in critical care and pharmacokinetics. Key publications include:

Morales Castro D, Wong I, Panisko D, Najeeb U, Douflé G. Self-Learning Videos in Focused Transthoracic Echocardiography Training. Clin Teach. 2025 Feb;22(1):e70014.

Morales Castro D, Balzani E, Abdul-Aziz MH, et al. Propofol and Fentanyl Pharmacokinetics and Pharmacodynamics in Extracorporeal Membrane Oxygenation. Annals of the American Thoracic Society. 2025;22(1):121-9.

Morales Castro D, Granton J, Fan E. Ceftobiprole and Cefiderocol for Patients on Extracorporeal Membrane Oxygenation: The Role of Therapeutic Drug Monitoring. Current Drug Metabolism. 2024;25:1-5.

Morales Castro D, Ferreyro B.L., McAlpine D, et al. Echocardiographic Findings in Critically Ill COVID-19 Patients Treated with and Without ECMO. J Cardiothorac Vasc Anesth. 2024.

Douflé G, Dragoi L, Morales Castro D, et al. Head-to-Toe Bedside Ultrasound for ECMO Patients. Intensive Care Med. 2024.

Morales Castro D, Dresser L, Granton J, Fan E. Pharmacokinetic Alterations in Critical Illness. Clin Pharmacokinet. 2023; 62(2):209-220.

Morales Castro D, Abdelnour-Berchtold E, Urner M, et al. Transesophageal Echocardiography-Guided ECMO Cannulation in COVID-19. J Cardiothorac Vasc Anesth. 2022;36(12):4296-4304.

Conclusion

Dr. Diana Morales Castro stands out as a dedicated physician, educator, and researcher with a profound impact on the fields of critical care medicine and pharmacokinetics. Through her academic achievements, clinical experience, and innovative research, she has contributed to improving the quality of care in critical settings, especially for patients undergoing complex treatments like ECMO. Her commitment to education and mentorship further elevates the standards of healthcare. As she continues to explore the intersections of critical care, pharmacokinetics, and echocardiography, Dr. Morales Castro’s work promises to shape the future of intensive care and pharmacological management in critically ill patients.