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.

Irina-Oana Lixandru-Petre | Machine Learning | Best Researcher Award

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Ms. Irina-Oana Lixandru-Petre | Machine Learning | Best Researcher Award

National University of Science and Technology POLITEHNICA Bucharest, Romania

Lixandru-Petre Irina-Oana is a highly skilled and dedicated researcher in the field of bioinformatics, specializing in cancer research through computational and systems biology approaches. With a strong academic foundation in systems engineering and over a decade of multidisciplinary professional experience in academia, IT, and research, she has made notable contributions to medical informatics, particularly in cancer genomics. Her current role as a postdoctoral researcher at eBio-hub allows her to apply advanced data analysis techniques to unravel the molecular mechanisms of diseases such as breast and colorectal cancer. Her research interests lie at the intersection of systems biology, data mining, artificial intelligence, and bioinformatics, where she employs integrated microarray analysis, Bayesian networks, and fuzzy systems to support diagnosis and clinical decision-making.

Profile

Scopus

Education

Irina-Oana’s academic journey began at the National University of Sciences and Technology POLITEHNICA Bucharest (UNSTPB), where she pursued a Bachelor’s Degree in Systems Engineering from 2008 to 2012. Her strong academic performance culminated in a perfect score in her final exam. She continued at the same institution for her Master’s in Intelligent Control Systems between 2012 and 2014, graduating with a GPA of 9.81 and a top dissertation grade. Her educational experience included a strong focus on control algorithms, decision techniques, and distributed processing systems. From 2014 to 2022, she pursued her PhD in Systems Engineering at UNSTPB. Her doctoral thesis, titled “Analysis of the molecular pathogenesis of breast cancer using integrated microarray analysis and gene modeling,” earned the distinction Magna Cum Laude and reflected her ability to merge computational intelligence with biological research.

Experience

Irina-Oana has held several significant roles throughout her career. Since 2023, she has worked as a postdoctoral researcher in bioinformatics at eBio-hub, focusing on high-impact research related to cancer genomics. Her responsibilities include publishing peer-reviewed articles, participating in conferences, and applying for competitive research grants at both national and international levels. Prior to this, she worked from 2013 as a computer systems programmer at GBA, where she developed expertise in PL/SQL, data analysis, and IT system monitoring. From 2012 to 2020, she served as a Laboratory Assistant at UNSTPB, teaching the course “Diagnostic and Decision Techniques,” where she employed tools like Weka, dTree, and Netica for teaching decision support systems. Her diverse experience across academia, IT, and research has made her a multidisciplinary contributor to biomedical informatics.

Research Interest

Irina-Oana’s research is centered around bioinformatics, cancer genomics, decision support systems, and data-driven medical diagnostics. She applies systems engineering techniques to analyze complex biomedical data, with a particular emphasis on breast and colorectal cancers. Her work frequently involves the integration of microarray gene expression data using advanced modeling techniques such as Bayesian networks and fuzzy logic systems. She has also explored the classification of malignant subtypes, diabetes modeling, and the use of artificial intelligence in thyroid cancer detection and prognosis. Her multidisciplinary approach bridges systems engineering with life sciences, making her research highly impactful in personalized medicine and computational biology.

Award

Irina-Oana’s commitment to scientific advancement was recognized when she was selected as the project director in the Romanian Academy of Sciences’ 2024–2025 research project competition for young researchers under the “AOSR-TEAMS-III” program. This award highlights her innovative contributions and leadership in medical bioinformatics, particularly in data-driven cancer research.

Publication

Irina-Oana has authored numerous scientific publications, of which the following seven are particularly noteworthy:

“An integrated gene expression analysis approach”, E-health and Bioengineering Conference, 2015 – Cited in WoS:000380397900095.

“Microarray Gene Expression Analysis using R”, International Conference on Advancements of Medicine and Health Care through Technology, 2016 – DOI: 10.1007/978-3-319-52875-5_74.

“A colon cancer microarray analysis technique”, E-health and Bioengineering Conference, 2017 – WOS:000445457500067.

“Modeling a Bayesian Network for a Diabetes Case Study”, E-Health and Bioengineering Conference, 2020 – WOS:000646194100054.

“An integrated breast cancer microarray analysis approach”, U.P.B. Scientific Bulletin, Series C, 2022 – WOS:000805648400007.

“Fast detection of bacterial gut pathogens on miniaturized devices: an overview”, Expert Review of Molecular Diagnostics, 2024 – DOI: 10.1080/14737159.2024.2316756.

“Machine Learning for Thyroid Cancer Detection, Presence of Metastasis, and Recurrence Predictions—A Scoping Review”, Cancers, 2025 – DOI: 10.3390/cancers17081308.

Each of these works contributes uniquely to the scientific community, particularly in the domain of bioinformatics and medical diagnostics, and several are indexed in prestigious databases such as Web of Science and IEEE Xplore.

Conclusion

Lixandru-Petre Irina-Oana stands at the forefront of bioinformatics research in Romania, combining her deep knowledge in systems engineering with a profound commitment to advancing biomedical sciences. Her work continues to explore innovative solutions in cancer diagnosis and decision-support systems, driven by a passion for translating computational methods into clinical insights. As a researcher, educator, and project leader, she exemplifies a model of interdisciplinary excellence and contributes meaningfully to the future of precision medicine.

Jaya Raju G | Machine Learning | Best Researcher Award

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Mr. Jaya Raju G | Machine Learning | Best Researcher Award

Assistant Professor at Aditya University, India

G. Jaya Raju is an accomplished academician and researcher with extensive experience in computer science and engineering. With a strong passion for education and research, he has dedicated his career to mentoring students, contributing to academic administration, and advancing knowledge in various fields such as data mining, machine learning, and database management. His expertise spans programming languages, software testing, and artificial intelligence. Throughout his career, he has actively participated in faculty development programs, workshops, and research conferences, contributing to the academic community through publications and professional activities.

Profile

Scopus

Education

G. Jaya Raju is currently pursuing a Ph.D. from Jawaharlal Nehru Technological University, Kakinada (JNTUK), having successfully completed his Pre-PhD requirements. He obtained his M.Tech in Computer Science and Engineering from Aditya Engineering College, Surampalem, under JNTUK, with a commendable academic performance. Additionally, he holds an M.Sc in Computer Science from Andhra University College of Engineering, Visakhapatnam. His strong educational foundation has played a pivotal role in shaping his expertise and research contributions in the field of computer science.

Experience

With over a decade of experience in academia, G. Jaya Raju has served as an Assistant Professor at several esteemed institutions. Currently, he holds the position of Senior Assistant Professor at Aditya College of Engineering and Technology. Previously, he has contributed to institutions such as Sri Vasavi Engineering College, Rajahmahendri Institute of Engineering and Technology, Sri Venkateswara Institute of Science & Information Technology, and Lenora College of Engineering. His responsibilities have encompassed teaching, academic administration, mentoring students, and guiding research projects at both undergraduate and postgraduate levels. Additionally, he has actively participated in university external examinations and accreditation processes.

Research Interests

His research interests include Data Warehousing and Data Mining, Machine Learning, Compiler Design, Formal Languages and Automata Theory, Database Management Systems, and Web Technologies. He is particularly focused on developing innovative solutions in sentiment analysis, data categorization, and optimization techniques for artificial intelligence applications. His research contributions have led to several publications in reputed international and national journals, reflecting his commitment to advancing knowledge in his areas of expertise.

Awards and Recognitions

G. Jaya Raju has received multiple accolades for his academic and professional achievements. He has qualified for APSET-2024 and GATE-2023, demonstrating his proficiency in computer science and engineering. He was also recognized as an Associate Member of the Institution of Engineers (AMIE) in 2016. Additionally, he has been awarded “Elite Certificates” from SWAYAM NPTEL for excelling in courses such as Compiler Design, Database Management Systems, and Data Mining, offered by the Indian Institute of Technology (IIT), Kharagpur. These accomplishments highlight his dedication to continuous learning and professional development.

Publications

“Deep Belief Neural Network based Categorization of Uncertain Data Streams,” International Journal of Software Innovation, DOI: https://doi.org/10.4018/IJSI.312262, cited by multiple research articles.

“Classical Software Testing Using Semi-Proving,” IJCST Vol. 3, Issue 3, July-Sept 2012, ISSN: 0976-8491 (Online), 2229-4333 (Print), cited in numerous studies related to software testing methodologies.

“Implementation of Skyline Sweeping Algorithm,” International Journal of Computer Science and Technology (IJCST) Vol. 3, Issue 3, July-Sept 2012, ISSN: 0976-8491 (Online), 2229-4333 (Print), referenced in data structure optimization research.

“Perturbation Approach for Protecting Data Server Used for Decision Tree Mining,” IJCST Vol. 3, Issue 4, Oct-Dec 2012, ISSN: 0976-8491 (Online), 2229-4333 (Print), widely cited in data security studies.

Conclusion

G. Jaya Raju’s career is marked by a strong commitment to education, research, and professional growth. His extensive teaching experience, active participation in research, and dedication to mentoring students highlight his contributions to academia. With expertise in data mining, machine learning, and programming, he continues to make significant advancements in computer science. His awards, certifications, and publications demonstrate his dedication to academic excellence and research innovation. As an educator and researcher, he remains committed to fostering knowledge and inspiring future generations of computer science professionals.