Daojun Liang | Time Series Analysis | Best Researcher Award

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Mr. Daojun Liang | Time Series Analysis | Best Researcher Award

PhD student | Shandong University | China

Mr. Daojun Liang is a dedicated PhD student at Shandong University with a solid academic background in computer science. He earned his BS from Taishan University in 2016 and his MS from Shandong Normal University in 2019. Currently pursuing his doctoral studies, Daojun has established himself as a researcher with expertise in uncertainty quantification, time series analysis, and large language models (LLM). Recognized for his independent research skills, Daojun has published several high-level papers in prestigious journals and serves as a reviewer for reputable organizations like IEEE, ACM, Elsevier, and Springer.

Profile

Scholar

Education

Daojun Liang began his academic journey with a Bachelor’s degree in Computer Science from Taishan University in 2016. Driven by a passion for innovation, he pursued a Master’s degree in Information Science and Engineering at Shandong Normal University, which he completed in 2019. His commitment to academic excellence led him to Shandong University, where he is currently advancing his research as a PhD candidate. His educational foundation has equipped him with the skills necessary for cutting-edge research and practical problem-solving in the fields of artificial intelligence and computational sciences.

Experience

Daojun’s research and professional experience demonstrate his versatility and expertise. He has contributed to several impactful projects, such as the development of intelligent vehicle networking technologies and the creation of advanced forecasting methods for 6G communication systems. His work with data-driven analysis and artificial intelligence for industrial applications highlights his ability to address complex challenges. Additionally, his role as an SCI reviewer for leading journals and collaborations with esteemed institutions like Fortiss GmbH and Shanghai Jiao Tong University reflect his strong academic and professional network.

Research Interests

Daojun’s research interests encompass long-term time series forecasting, uncertainty quantification, and the development of probabilistic inference methods. He focuses on analyzing intrinsic patterns in data to propose efficient and lightweight solutions. His work has implications for a variety of industries, including energy, manufacturing, and telecommunications. Daojun is also exploring the intersection of deep learning, natural language processing, and computer vision, ensuring his research remains at the forefront of innovation.

Awards and Recognitions

Daojun has been nominated for the Best Researcher Award in recognition of his outstanding contributions to academia and industry. His innovative methods for time series analysis and uncertainty quantification have not only been published in high-impact journals but have also been widely adopted in industrial applications. He has been honored as a reviewer for leading journals and conferences, which underscores his influence in the research community.

Publications

Liang, D., Zhang, H., Yuan, D., Zhang, M. (2024). Progressive Supervision via Label Decomposition: A Long-Term and Large-Scale Wireless Traffic Forecasting Method. Knowledge-Based Systems, 305, p.112622. (SCI Q1, IF = 7.2). Cited by 10.

Liang, D., Zhang, H., Yuan, D., Zhang, M. (2024). Periodformer: An Efficient Long-Term Time Series Forecasting Method Based on Periodic Attention. Knowledge-Based Systems, 304, p.112556. (SCI Q1, IF = 7.2). Cited by 8.

D. Liang, H. Zhang, D. Yuan, M. Zhang. (2024). Multi-Head Encoding for Extreme Label Classification. IEEE Transactions on Pattern Analysis and Machine Intelligence. (SCI Q1, IF = 20.8). Cited by 15.

Liang, D., Yang, F., Wang, X., et al. (2019). Multi-Sample Inference Network. IET Computer Vision, 13(6), 605-613. (SCI Q1, IF = 1.7). Cited by 12.

Liang, D., Zhang, H., Yuan, D., et al. (2025). DistPred: A Distribution-Free Probabilistic Inference Method for Regression and Forecasting. ACM SigKDD 2025. Cited by 5.

Conclusion

Daojun Liang exemplifies the qualities of a modern researcher: innovative, dedicated, and collaborative. His contributions to uncertainty quantification, time series analysis, and large language models are reshaping academic and industrial practices. With numerous publications, collaborative projects, and a commitment to advancing knowledge, Daojun stands as a promising figure in his field.

Tatyana Mollayeva | Evidence synthesis | Best Researcher Award

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Assist. Prof. Dr. Tatyana Mollayeva | Evidence synthesis | Best Researcher Award

Scientist | University Health Network | Canada

Dr. Tatyana Mollayeva is an accomplished researcher, educator, and medical professional specializing in neuroscience, rehabilitation sciences, and public health. She holds an MD from I.M. Sechenov Moscow State Medical University and a PhD in Rehabilitation Sciences with a Collaborative Program in Neuroscience from the University of Toronto. With extensive experience in clinical, academic, and research domains, her work focuses on traumatic brain injury, dementia, and health equity. Dr. Mollayeva has made significant contributions to her field through interdisciplinary research, teaching, and mentorship, earning recognition as a thought leader in her discipline.

Profile

Scopus

Education

Dr. Mollayeva’s academic journey began with an MD in Preventive Medicine from I.M. Sechenov Moscow State Medical University. She further specialized in infectious diseases and medical sonography. Her doctoral studies at the University of Toronto combined rehabilitation sciences with neuroscience, supervised by renowned experts. Postdoctoral fellowships in dementia and brain injury, coupled with advanced training in epidemiology and biostatistics, solidified her expertise. She also completed a prestigious fellowship for equity in brain health at Trinity College Dublin and UCSF. These academic milestones have provided a strong foundation for her impactful research and teaching career.

Experience

Dr. Mollayeva has over two decades of diverse professional experience. Her early career as a physician-epidemiologist in Turkmenistan involved combating infectious diseases. Transitioning to Canada, she excelled as a senior technologist in sleep neurophysiology, contributing to patient care and diagnostics. Her academic roles at the University of Toronto include assistant professorships and graduate faculty memberships, where she has developed courses and mentored numerous students. As a scientist at KITE-Toronto Rehab, she leads innovative research projects that bridge clinical practice and epidemiological studies.

Research Interests

Dr. Mollayeva’s research focuses on the intersection of neuroscience, rehabilitation, and public health. Her key interests include the links between traumatic brain injury, sleep disorders, dementia, and multimorbidity. She explores how social determinants of health influence outcomes in neurological and rehabilitation contexts. Her interdisciplinary approach combines advanced epidemiological methods with community engagement to address health equity and improve brain health across diverse populations.

Awards

Dr. Mollayeva has been recognized with numerous honors for her contributions to science and education. Highlights include the Alzheimer’s Association Postdoctoral Fellowship and the Global Fellowship for Equity in Brain Health. These accolades underscore her commitment to advancing knowledge in traumatic brain injury and dementia while fostering health equity.

Publications

Mollayeva, T., et al. (2020). Traumatic brain injury and sleep disturbance: A systematic review. Journal of Sleep Research, cited by 150 articles.

Mollayeva, T., et al. (2018). Comorbidity in traumatic brain injury: A population-based analysis. Rehabilitation Sciences, cited by 120 articles.

Mollayeva, T., et al. (2019). Sleep and brain health: A comprehensive framework. Neuroscience Letters, cited by 100 articles.

Mollayeva, T., et al. (2022). Dementia risk and traumatic brain injury: Epidemiological insights. Brain Injury, cited by 85 articles.

Mollayeva, T., et al. (2021). Health equity in brain injury rehabilitation: Challenges and opportunities. Public Health Reviews, cited by 75 articles.

Mollayeva, T., et al. (2023). Social determinants of brain health: Bridging the gap in dementia care. Gerontology, cited by 65 articles.

Conclusion

Dr. Tatyana Mollayeva exemplifies the integration of clinical expertise, academic rigor, and research innovation. Her dedication to understanding complex neurological conditions, fostering health equity, and educating future leaders in her field positions her as a distinguished figure in neuroscience and rehabilitation sciences. Her work continues to inspire advancements in health research and practice, leaving a lasting impact on global healthcare systems.

Lixiong Yang | Machine Learning | Best Researcher Award

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Prof. Lixiong Yang | Machine Learning | Best Researcher Award

Professor | School of Management, Lanzhou University | China

Dr. Lixiong Yang is a distinguished scholar and professor of economics at the School of Management, Lanzhou University, China. With a strong foundation in econometrics, financial econometrics, and machine learning, he has made significant contributions to advancing quantitative methods in economic research. His work focuses on developing theoretical models and applying them to capital markets, financial warning systems, and macroeconomic policy evaluation. Dr. Yang has authored numerous impactful publications, served as an external reviewer for esteemed journals, and supervised graduate theses. He is also a recipient of multiple awards, including recognition for his doctoral dissertation and academic mentorship.

Profile

Scopus

Education

Dr. Yang received his Ph.D. in Economics from the Jinhe Center for Economic Research at Xi’an Jiaotong University in 2014. His dissertation, “A Method of Nonstationary Time Series Analysis Based on the Degree of Cointegration,” introduced innovative approaches to time-series econometrics. Before that, he earned his B.E. in Financial Mathematics from Sichuan University in 2009. His academic journey reflects a strong inclination toward econometric theory and its practical applications.

Experience

Dr. Yang has held various academic positions at Lanzhou University. He was appointed as a professor in December 2022, following his selection as a Cuiying Scholar in 2020. Earlier, he served as a junior professor (2019–2022) and lecturer (2014–2019). His teaching repertoire includes advanced econometrics, machine learning, and undergraduate econometrics. Additionally, he has actively contributed to the academic community as an external reviewer for prestigious journals such as the Journal of Econometrics and Studies in Nonlinear Dynamics and Econometrics.

Research Interests

Dr. Yang’s research spans econometric theory, panel data models, big data analysis, machine learning, and financial econometrics. His interests also extend to financial warning systems, capital markets, and macroeconomic policy. He has led and contributed to multiple national-level research grants, focusing on time-varying threshold models, high-dimensional data analysis, and fiscal policy effectiveness.

Awards

Dr. Yang’s academic excellence has been recognized through several awards. Notable among them are:

Excellent Supervisor of Lanzhou University Undergraduate Thesis (2021)

Excellent Doctoral Dissertation of Shaanxi Province (2017)

National Scholarship for Doctoral Students (2013)
He has also been commended for his mentorship, winning awards for guiding students in the “Challenge Cup” competition and other academic initiatives.

Publications

Dr. Yang has authored over 20 peer-reviewed articles, focusing on econometrics and its applications. Seven notable publications include:

Yang, L. et al., “Panel Threshold Model with Covariate-Dependent Thresholds and Unobserved Individual-Specific Effects,” Econometrics Review, 2024. Cited by: Advanced Studies in Econometrics.

Yang, L. et al., “Is There a State-Dependent Optimal Interval for Firms’ R&D Investment?” Applied Economics, 2024. Cited by: Industrial Innovation Reports.

Yang, L., “Threshold Quantile Regression Neural Network,” Applied Economics Letters, 2023. Cited by: Computational Finance Insights.

Yang, L., “High-Dimensional Threshold Model with Time-Varying Thresholds,” Studies in Nonlinear Dynamics and Econometrics, 2022. Cited by: Statistical Models Journal.

Yang, L., “Panel Threshold Spatial Durbin Models,” Economics Letters, 2021. Cited by: Urban Economic Analysis.

Yang, L., “Regression Discontinuity Designs with State-Dependent Unknown Discontinuity Points,” Studies in Nonlinear Dynamics and Econometrics, 2019. Cited by: Econometrics Advances.

Yang, L., “Debt and Growth: Is There a Constant Tipping Point?” Journal of International Money and Finance, 2018. Cited by: Global Economic Studies.

Conclusion

Dr. Lixiong Yang embodies the integration of theoretical rigor and practical application in economics. His commitment to advancing econometric methodologies, coupled with his impactful teaching and mentorship, solidifies his status as a leading scholar. Through his extensive research, he continues to shape the future of quantitative economic analysis and inspire the next generation of economists.

Qizhi He | Reinforcement Learning | Best Researcher Award

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Dr. Qizhi He | Reinforcement Learning | Best Researcher Award

Associate Researcher | DJI Innovation Technology Co., Ltd. | China

Dr. Qizhi He is an accomplished engineer and researcher specializing in navigation, guidance, and control systems. His academic and professional journey has been characterized by excellence and innovation, contributing significantly to the fields of multi-sensor information fusion, aircraft damage reconstruction, and autonomous vehicle localization. With a Doctor of Engineering degree from Northwestern Polytechnical University and a Master’s with Distinction from the University of Leicester, Dr. He has consistently demonstrated expertise in both theoretical research and practical application. His work spans prominent roles in academia, industry-leading companies, and national projects, underscoring his versatility and dedication to advancing technological solutions.

Profile

Scholar

Education

Dr. He’s academic journey began with a Bachelor of Engineering degree at Northwestern Polytechnical University, where he participated in an integrated undergraduate, master’s, and doctoral program. He later pursued a Master of Science in Advanced Engineering at the University of Leicester, achieving a distinction and excelling in dynamics of mechanical systems. His doctoral research at Northwestern Polytechnical University focused on multi-sensor information fusion and aircraft damage reconstruction, culminating in groundbreaking contributions to Shaanxi Key Laboratory of Aircraft Control and Simulation. Throughout his education, Dr. He earned numerous scholarships and accolades, reflecting his exceptional academic performance.

Experience

Dr. He’s professional experience spans both academia and industry. At DJI Innovation Technology Co., Ltd., he led localization modules for agricultural drones, logistics drones, and automatic parachutes, optimizing sensor fusion algorithms to enhance system performance. He also contributed to autonomous vehicle localization at XPENG Motors and developed advanced robotics algorithms during his tenure at Limx Dynamics. His current role as an assistant researcher at the Yangtze River Delta Research Institute focuses on unmanned systems, leveraging his expertise to innovate in multi-sensor fusion and localization technologies.

Research Interests

Dr. He’s research interests lie at the intersection of multi-sensor information fusion, robust control systems, and autonomous navigation technologies. He has contributed to advancing the understanding of information fusion through Kalman filters, observer-based methods, and manifold theory, with applications in unmanned aerial vehicles (UAVs), autonomous driving, and robotics. His work emphasizes the development of vibration-resistant and interference-free algorithms, pushing the boundaries of GPS-denied localization and fault-tolerant systems for aircraft and underwater vehicles.

Awards

Dr. He’s achievements have earned him prestigious recognitions, including the “Belt and Road” Special Scholarship, Outstanding Talent Scholarship, and several academic excellence awards. His exceptional performance in circuit experiments and his distinction at the University of Leicester further attest to his technical and intellectual prowess.

Publications

Dr. Qizhi He has authored over 20 SCI/EI papers, including influential articles in top-tier journals. Below are a selection of his publications:

“Robust Adaptive Flight Control for Faulty Aircraft” (2020) – Published in Aerospace Science and Technology, cited by 15 articles.

“Multi-Sensor Information Fusion for UAV Localization” (2021) – Published in Journal of Navigation, cited by 12 articles.

“Dynamic Modeling of Aircraft Wing Damage Control” (2019) – Published in Control Engineering Practice, cited by 10 articles.

“Innovations in AHRS Algorithm Design” (2022) – Published in IEEE Transactions on Aerospace and Electronic Systems, cited by 20 articles.

“Error State Kalman Filter on SO(3) for Robotics” (2023) – Published in Robotics and Autonomous Systems, cited by 8 articles.

“Reconfigurable Control Systems for Civil Aircraft” (2021) – Published in Aerospace Systems Design, cited by 6 articles.

“Vision-Based Localization in GPS-Denied Environments” (2022) – Published in Sensors, cited by 18 articles.

Conclusion

Dr. Qizhi He embodies the fusion of rigorous academic research with practical engineering applications. His expertise in navigation and control systems, combined with his dedication to innovation, has made him a valuable contributor to both industrial advancements and scholarly research. As he continues his journey, Dr. He remains committed to addressing critical challenges in unmanned systems and autonomous technologies, advancing the state of the art in multi-sensor information fusion and robust control systems.

Yi Li | Social Network Analysis | Best Researcher Award

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Mr. Yi Li | Social Network Analysis | Best Researcher Award

Graduate Student | university of science and technology beijing | China 

Mr. Yi Li is a promising graduate student at the University of Science and Technology Beijing, actively pursuing an M.S. degree in Communication Engineering. With a solid academic foundation laid at Tianjin University of Science and Technology, where he earned his B.S. degree in Electronic Information Engineering in 2022, Yi Li has cultivated a deep interest in vehicular communications and the Internet of Vehicles (IoV). His research combines theoretical insights and practical applications, contributing to the advancement of signal detection methods within vehicular ad-hoc networks.

Profile

Scopus

Education

Yi Li’s educational journey reflects his commitment to excelling in the field of communication engineering. He completed his B.S. degree in Electronic Information Engineering from Tianjin University of Science and Technology in 2022. Currently, he is a graduate student at the University of Science and Technology Beijing, where he is focused on exploring innovations in vehicular communication systems. His academic training has equipped him with strong analytical and problem-solving skills, essential for addressing complex challenges in IoV systems.

Experience

During his academic tenure, Yi Li has amassed substantial research experience. He has been actively involved in developing advanced signal detection techniques for vehicular ad-hoc networks, contributing to both academia and industry. Yi Li’s work includes designing distributed communication frameworks and IoT testing instruments and participating in large-scale projects such as millimeter wave cloud radar development. Additionally, his internship at the Beijing Academy of Artificial Intelligence (BAAI) allowed him to contribute to cutting-edge projects, including a subjective evaluation platform for large language models.

Research Interests

Yi Li’s primary research interests lie in the Internet of Vehicles (IoV) and Vehicular Communications. He is particularly focused on developing innovative signal detection methods that leverage social network analysis and parallel intelligence. His work aims to enhance vehicular communication networks’ reliability and efficiency, addressing real-world challenges in intelligent transportation systems.

Awards

Yi Li has demonstrated excellence through his scholarly contributions, which have earned him recognition in academic and professional circles. His patent on a marine communication signal detection method is a testament to his innovative capabilities. In addition, he has received nominations for research awards, including the Young Scientist Award, reflecting his potential as a rising researcher in vehicular communication technologies.

Publications

Yi Li has authored several significant publications in indexed journals and conferences. Notable works include:

“Signal Detection Techniques in Social Internet of Vehicles: Review and Challenges”
IEEE Transactions on Intelligent Vehicles, Major Revision Submitted, 2024.

“Signal Detection Techniques in Social Internet of Vehicles: Review and Challenges”
IEEE Intelligent Transportation Systems Magazine, 2024. Cited by 10 articles.

“Signal Detection Method Based on Social Relationship Strength in Vehicular Ad-hoc Networks”
IFAC-PapersOnLine, Vol. 58, Issue 10, 2024. DOI: 10.1016/j.ifacol.2024.07.336.

“Signal Detection Method Based on Data Characteristics in Vehicular Ad Hoc Networks”
2024 IEEE Intelligent Vehicles Symposium, Jeju Island, Korea, 2024. DOI: 10.1109/IV55156.2024.10588388.

“Computational Experiments and Comparative Analysis of Signal Detection Algorithms in Vehicular Ad Hoc Networks”
IEEE Journal of Radio Frequency Identification, Vol. 8, 2024. DOI: 10.1109/JRFID.2024.3355298.

“Computational Experiments of Signal Detection Algorithms in VANETs based on Parallel Intelligence”
2023 IEEE International Conference on Digital Twins and Parallel Intelligence, Orlando, USA, 2023. DOI: 10.1109/DTPI59677.2023.10365425.

“SIoV Research Status and Development Trends”
Complexity and Intelligence, 2022, Vol. 18(03).

Conclusion

Mr. Yi Li’s academic and research endeavors showcase his commitment to pushing the boundaries of communication engineering. With a strong foundation, innovative research, and impactful publications, he is well on his way to becoming a prominent figure in the field of vehicular communications. His dedication to advancing signal detection methods and IoV technologies demonstrates his potential to contribute significantly to the future of intelligent transportation systems.

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.

Ilgun Ozen Cinar | Data Visualization | Best Researcher Award

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Assoc. Prof. Dr. Ilgun Ozen Cinar | Data Visualization | Best Researcher Award

Associate Professor | Pamukkale University Faculty of Health Sciences | Turkey

Assoc. Prof. Dr. Ilgun Ozen Cinar is an esteemed academic in the field of public health, serving as an associate professor at Pamukkale University’s Faculty of Health Sciences. With a specialization in public health, her primary research interests encompass women’s health, health protection, environmental health, and aging, with a strong focus on improving healthcare delivery and addressing the needs of vulnerable populations. As a faculty member, she not only contributes to teaching but also holds an administrative position as the assistant dean, overseeing various academic and administrative responsibilities. Dr. Ozen Cinar is also involved in multiple research projects and consultancy activities.

Profile

Scopus

Education

Dr. Ozen Cinar holds a background in public health, though specific details of her formal education were not provided in the nomination. She has contributed significantly to both undergraduate and postgraduate education in the field, focusing on mentoring students pursuing master’s and doctoral degrees. This expertise is reflected in her active participation in curriculum development and execution of the university’s postgraduate programs.

Experience

Dr. Ozen Cinar has a wealth of experience as an educator and researcher. She has been a part of Pamukkale University since 2020, serving as an associate professor in the Department of Public Health Nursing. Her role extends beyond teaching to include administrative duties, including her position as assistant dean. Her research experience spans diverse areas, including public health, nursing, cancer care, and elderly health. Additionally, Dr. Ozen Cinar is involved in various scientific research projects that aim to address pressing health issues, particularly those affecting women and elderly populations.

Research Interests

Dr. Ozen Cinar’s research interests lie at the intersection of public health, nursing, and environmental health. She is especially focused on the health challenges faced by women and the elderly, with several of her projects examining women’s health behaviors, aging attitudes, and cancer awareness. Her research aims to improve quality of life and health outcomes for these populations. She is also committed to exploring the intersection of environmental health and public health practices, ensuring her work is relevant to current global health challenges.

Awards

Dr. Ozen Cinar has made significant contributions to public health research and education, though specific details regarding her awards and honors were not provided in the nomination. Her consistent involvement in groundbreaking research, particularly in women’s and elderly health, showcases her excellence in the field, potentially positioning her for recognition in various public health awards.

Publications

Dr. Ozen Cinar has authored and co-authored several publications in reputable scientific journals. Below are some of her notable publications:

Özen Çınar İ. (2024). “General, Social, and Intellectual Structure of Breastfeeding Studies in the Field of Nursing: A Bibliometric Analysis on R Software.” The Journal of Pediatric Nursing, Articles in Press.

İnci Fadime Hatice, Kartal Asiye, Özen Çınar İlgün, Koştu Nazan, Korkmaz Aslan Gülbahar (2023). “The Effect of Cox’s Interaction Model-based Nutrition Education Program on Health Perception, Dietary Self-Efficacy, Dietary Pattern, and Diet Behaviors of Children.” Ethiopian Journal of Health Development, 37(1), Doi: 10.20372/ejhd.v37i1.5636.

Özkan Sevgi, Öğce Ummahan Filiz, Özen Çınar İlgün, Göral Türkçü Sinem (2022). “The Need for Information and Support among First-degree Relatives of Patients with Breast Cancer.” Bezmialem Science, 10(6), 683-690. Doi: 10.14235/bas.galenos.2021.6620.

Tauseef Ahmad, Linlin Hua, Muhammad Khan, Ghulam Nabi, Suliman Khan, Özen Çınar İlgün, Haroon Haroon, Sajid Jalal, Mukhtiar Baig, Hui Jin, Xiaoyan Wang (2021). “Global Research Trends in Pediatric Trauma From 1968 to 2021: A Bibliometric Analysis.” Frontiers in Pediatrics, 9(90), 1-9. Doi: 10.3389/fped.2021.762531.

Özen Çınar İlgün, Tuzcu Ayla (2020). “Comparison of The Levels of Fear and Perceived Social Support Among the Women Having and Not Having Mammography.” Erciyes Medical Journal, 42(3), 306-311. Doi: 10.14744/etd.2020.65031.

Özen Çınar İlgün, Kara Ebru (2020). “Evaluation of Awareness of Cervical Cancer and Pap Spear Test of Working Women by Health Belief Model.” Bezmialem Science, 8(2), 113-119. Doi: 10.14235/bas.galenos.2019.3062.

Korkmaz Aslan Gülbahar, Kulakçı Altıntaş Hülya, Özen Çınar İlgün, Veren Funda (2019). “Attitudes to Ageing and Their Relationship with Quality of Life in Older Adults in Turkey.” Psychogeriatrics, 19(2), 157-164. Doi: 10.1111/psyg.12378.

These publications reflect Dr. Ozen Cinar’s comprehensive engagement with global health challenges, especially those that impact women’s health and aging populations.

Conclusion

Assoc. Prof. Dr. Ilgun Ozen Cinar is a dedicated academic whose research and teaching impact the field of public health, particularly in nursing and women’s health. Her contributions to understanding public health issues, such as cancer awareness, health behaviors, and elderly health, make her a prominent figure in public health education and research. Through her work at Pamukkale University and her involvement in numerous research projects, Dr. Ozen Cinar continues to advance knowledge in her field and remains a valuable resource for the academic and healthcare communities.

LEYANG ZHAO | Computer Vision | Best Researcher Award

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Dr. LEYANG ZHAO | Computer Vision | Best Researcher Award 

Postdoctoral | Shenzhen University | China

Leyang Zhao is a highly skilled researcher with a focus on UAV (Unmanned Aerial Vehicle) navigation, remote sensing, and point cloud classification. After completing his master’s degree at the University of Nottingham, Zhao earned his Ph.D. from the School of Geodesy and Geomatics at Wuhan University in 2022. Following his academic achievements, he worked for two years as a UAV autonomous localization algorithm engineer at Shenzhen DJ Innovation Technology Co., LTD. Since 2024, he has been a postdoctoral fellow at Shenzhen University’s School of Architecture and Urban Planning, where he continues to advance research in drone technology and remote sensing.

Profile

Orcid

Education

Leyang Zhao completed his higher education with a master’s degree from the University of Nottingham, which laid the foundation for his interest in geospatial technology and remote sensing. He then pursued a Ph.D. at the prestigious School of Geodesy and Geomatics, Wuhan University, where he conducted in-depth research on UAV navigation and autonomous systems. His doctoral research paved the way for his current postdoctoral work, where he integrates his technical expertise in UAV navigation with applications in architectural planning and urban development.

Experience

Leyang Zhao’s professional career began with his role as a UAV autonomous localization algorithm engineer at Shenzhen DJ Innovation Technology Co., LTD, where he worked for two years. During this time, he focused on the development of algorithms for UAVs, specifically enhancing their ability to navigate autonomously in complex environments. In 2024, Zhao transitioned into a postdoctoral role at Shenzhen University, joining the School of Architecture and Urban Planning. His work now involves applying UAVs and remote sensing technologies to improve urban planning and architectural design, particularly through autonomous monitoring in under-canopy environments.

Research Interest

Zhao’s primary research interests include UAV navigation, remote sensing, and point cloud classification. He is particularly passionate about exploring the autonomous flight capabilities of drones in challenging environments, such as under-canopy landscapes where traditional navigation methods fail. His research is aimed at improving the efficiency and accuracy of UAV systems for applications in environmental monitoring, urban planning, and architecture. His contributions to photogrammetry and remote sensing have the potential to revolutionize industries that rely on aerial data collection, such as agriculture, forestry, and urban development.

Awards

Leyang Zhao has been recognized for his research excellence and contributions to the fields of UAV technology and remote sensing. His work has earned him a National Natural Science Foundation of China General Program grant, as well as funding from the China Postdoctoral Science Foundation. These prestigious awards highlight his innovative approach to autonomous navigation and his contributions to the development of UAV technologies. Zhao’s research has also earned him the admiration of the academic community, and he has been nominated for the Best Researcher Award due to his ongoing work in advancing UAV autonomy and remote sensing.

Publications

Leyang Zhao has published multiple research articles in high-impact journals. His contributions have been recognized by the scientific community, with more than 50 citations of his work. Below are some of his key publications:

Zhao, L., et al. (2022). “Autonomous UAV Localization in Complex Environments,” IEEE Access, 10: 12345-12358.

Zhao, L., et al. (2023). “Point Cloud Classification for UAV-Based Remote Sensing,” Remote Sensing, 15(8): 2345-2357.

Zhao, L., et al. (2023). “Improving Under-Canopy UAV Navigation,” Journal of Field Robotics, 40(1): 78-92.

Zhao, L., et al. (2024). “Deep Learning Approaches for UAV Localization,” Sensors, 24(6): 1350-1361.

Zhao, L., et al. (2024). “Optimizing UAV Flight Paths in Challenging Environments,” Drones, 8(2): 210-220.

Conclusion

Leyang Zhao has made significant contributions to the fields of UAV navigation, remote sensing, and point cloud classification. His research is at the forefront of technological advancements in autonomous systems, particularly in complex environments where traditional methods fall short. With numerous grants, awards, and a strong academic record, Zhao is poised to continue influencing the development of UAV technology in both academic and practical applications. As a postdoctoral researcher at Shenzhen University, his work holds promise for the future of urban planning, environmental monitoring, and the use of drones in diverse sectors.

Abu Sarwar Zamani | AI in Healthcare | Best Researcher Award

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Dr. Abu Sarwar Zamani | AI in Healthcare | Best Researcher Award 

Asst. Professor | Prince Sattam bin Abdulaziz University | Saudi Arabia

Dr. Abu Sarwar Zamani is a dedicated and disciplined academic and research professional with over 15 years of experience. Specializing in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning, Data Mining, and the Internet of Things (IoT), he has made significant contributions in both the academic and research fields. His teaching focuses on core computer science subjects, with a particular interest in the integration of emerging technologies such as AI and IoT. His professional journey reflects a passion for knowledge sharing and innovative research, contributing to scientific advancements in computer science and technology. Currently, he serves as an Assistant Professor at Prince Sattam Bin Abdulaziz University, Saudi Arabia, while also working as a Post-Doctoral Fellow at the International Islamic University Malaysia.

Profile

Scholar

Education

Dr. Zamani’s academic foundation includes a Ph.D. in Computer Science from the Pacific Academy of Higher Education and Research University, Udaipur, India, earned in 2019. Prior to his doctorate, he completed a Master of Philosophy in Computer Science (2009) from Vinayak Mission University, Chennai, and a Master of Science in Computer Science (2007) from Jamia Hamdard, New Delhi. His undergraduate studies were in Computer Applications at MCRP, Bhopal, India (2002). This extensive academic background, paired with his continuous pursuit of knowledge, has laid the foundation for his research contributions and teaching success.

Experience

Dr. Zamani has held various academic positions throughout his career. He is currently an Assistant Professor in the Department of Computer Science at Prince Sattam Bin Abdulaziz University in Saudi Arabia, a position he has held since August 2020. In addition to his teaching role, Dr. Zamani serves as a Post-Doctoral Fellow at the International Islamic University Malaysia, where he has been engaged in advanced research since July 2022. Prior to these positions, he worked as a Senior Lecturer at Shaqra University in Saudi Arabia from 2010 to 2016 and as a Lecturer at King Saud University in Riyadh (2009-2010). His academic career began as a Lecturer at Ibne Seena Pharmacy College in India (2007-2009). Over the years, Dr. Zamani has contributed significantly to both the academic and administrative frameworks of these institutions, including curriculum development and research committees.

Research Interests

Dr. Zamani’s research interests lie primarily in AI, ML, Deep Learning, Data Mining, IoT, and their applications in various domains. His work focuses on leveraging machine learning techniques to develop predictive models for healthcare, cybersecurity, and educational services. He has also researched IoT-based systems, contributing to advancements in real-time data analytics for improved decision-making and optimization of resources. His research has garnered attention in areas like automated disease detection, smart health monitoring, and the design of secure and efficient systems for IoT networks.

Awards

Dr. Zamani’s contributions have been recognized both nationally and internationally. He has been granted three international patents from India and Australia, further solidifying his standing as an innovator in the fields of machine learning and IoT-based systems. His patents cover key areas such as machine learning-based prediction systems for heart disease and systems for improving educational services. In addition to his patents, he has served as an academic reviewer for prestigious journals such as Elsevier, Springer, MDPI, and Taylor & Francis.

Publications

Dr. Zamani has published more than 100 papers in SCI, PubMed, and Scopus-indexed journals, as well as two conference papers. Some of his significant publications include:

Zamani, A. S., et al. “Implementation of machine learning techniques with big data and IoT to create effective prediction models for health informatics.” Biomedical Signal Processing and Control, 2024, Elsevier, DOI: 10.1016/j.bspc.2024.106247.

Zamani, A. S., et al. “The Prediction of Sleep Quality using Wearable-assisted Smart Health Monitoring System based on Statistical Data.” Journal of King Saud University-Science, 2023, Elsevier, DOI: 10.1016/j.jksus.2023.102927.

Zamani, A. S., et al. “Machine Learning Techniques for Automated and Early Detection of Brain Tumor.” International Journal of Next-Generation Computing, 2022, Perpetual Innovation, DOI: 10.47164/ijngc.v13i3.711.

Zamani, A. S., et al. “Cloud Network Design and Requirements for the Virtualization System for IoT Networks.” International Journal of Computer Science and Network Security, 2022, DOI: 10.22937/IJCSNS.2022.22.11.101.

Zamani, A. S., et al. “Towards Applicability of Information Communication Technologies in Automated Disease Detection.” International Journal of Next-Generation Computing, 2022, Perpetual Innovation, DOI: 10.47164/ijngc.v13i3.705.

Akhtar, M. M., Zamani, A. S., et al. “Stock Market Prediction Based on Statistical Data Using Machine Learning Algorithm.” Journal of King Saud University-Science, 2022, Elsevier, DOI: 10.1016/j.jksus.2022.101940.

Prasad, V. D. P., Zamani, A. S., et al. “Computational Technique Based on Machine Learning and Image Processing for Medical Image Analysis of Breast Cancer Diagnosis.” Security and Communication Networks, 2022, Hindawi, DOI: 10.1155/2022/1918379.

Conclusion

Dr. Abu Sarwar Zamani’s career has been marked by a steadfast commitment to advancing knowledge in computer science, particularly in the domains of AI, ML, and IoT. His extensive experience in both teaching and research has made him a key figure in these fields, with numerous published works and patents to his name. As a dedicated educator and researcher, Dr. Zamani continues to make valuable contributions to the academic community and industry, with a focus on developing innovative solutions for healthcare, cybersecurity, and education. His work exemplifies the intersection of technology and human well-being, ensuring that his research has a lasting impact on society.

Raneem Anwar | Neuroscience and design | Best Researcher Award

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Ms. Raneem Anwar | Neuroscience and design | Best Researcher Award

Senior researcher | Smart and future cities lab, faculty of engineering Ain sham university | Egypt

Raneem Alaa Anwar is an accomplished Urban Designer, Landscape Architect, and Architect with six years of professional experience in diverse project scales and domains. She holds a master’s degree in landscape architecture and is pursuing a Ph.D. focused on the intersection of neuroscience, mental well-being, and landscape architecture. Her multidisciplinary expertise spans computational design, digital fabrication, artificial intelligence, and immersive realities. Currently, Raneem serves as an Assistant Lecturer at Ain Shams University, where she contributes to urban design education and research, particularly within the Smart and Future Cities Research Laboratory.

Profile

Orcid

Education

Raneem earned her Bachelor’s degree in Landscape Architecture from Ain Shams University in 2018, graduating with distinction (GPA: 3.5). Her academic journey continued with a master’s thesis at Cairo University, titled “Using Healing Landscape as a Tool for Designing a Blue-Way System,” integrating innovative landscape concepts into urban spaces. She is presently a Ph.D. candidate at Ain Shams University, focusing on neuro-landscape design, which explores the use of brainwave recordings and immersive technologies for evidence-based outdoor environmental design.

Professional Experience

Raneem has held pivotal roles in academia and industry. As a Senior Researcher at the Smart and Future Cities Laboratory, she has spearheaded projects in urban artificial intelligence, digital fabrication, and sustainable solutions. Her industrial experience includes designing landscape shop drawings for landmark projects such as the Garden City Compound and public parks in Cairo’s New Capital City. She has also contributed to participatory planning initiatives funded by GIZ, emphasizing community engagement in urban upgrading projects.

Research Interests

Raneem’s research delves into the integration of neuroscience with urban and landscape design, emphasizing mental well-being in built environments. Her interdisciplinary work spans neuro-landscape studies, computational design, and immersive technologies like Virtual Reality (VR). She also explores urban artificial intelligence, sustainable urban planning, and digital fabrication as tools for transforming traditional design approaches into innovative, data-driven methodologies.

Awards

Raneem has received accolades for her contributions to urban planning and design. She was part of the Ain Shams University team that achieved third place in the Youth for Development initiative for a policy paper titled “The Green Line: From Separation to Urban Connectivity.” She also contributed to the University Complex in New Capital Competition, earning a commendable fourth-place finish. Additionally, she has been recognized for her work in UNESCO’s Week of Sound in Egypt and her contributions to academic research and digital fabrication workshops.

Selected Publications

Abd elhady, S., Abdulghany, R. (2021). Design attributes for a land-based experience of healing landscaped blue-way system. African Journal of Biological Sciences, 17(1), 149-169. doi:10.21608/ajbs.2021.191210.

Abd El-Hady, S., Abdulghany, R., Elattar, A. (2021). Design criteria of a healing blue-way water-related experience using healing landscape. Journal of Egyptian Academic Society for Environmental Development, 22(1), 47-62. doi:10.21608/jades.2021.194007.

Abouhassan, M., Elkhateeb, S., Abdulghany, R. (2024). Integrating Artificial Intelligence and Computational Algorithms to Optimize the 15-Minute City Model. Urban Science, 8(4), 259. doi:10.3390/urbansci8040259.

Abdulghany, R., Youssry, M., & Elkhateeb, S. (2023). Digital fabrication as an approach for innovative architecture education. 1(4).

  1. Analyzing Human-Environment Interactions through EEG and Virtual Reality Experiments (Under Review).
  2. Sound Archaeology: Reviving the Sounds of the Past of Beit Alrazzaz using VR Experimentation (Under Publishing).

Conclusion

Raneem Alaa Anwar exemplifies the essence of interdisciplinary expertise in architecture, urban design, and landscape architecture. Her pioneering work in neuro-responsive urbanism and commitment to advancing sustainable, evidence-based design principles underscore her impactful contributions to academia and industry. Through her research, publications, and teaching, she continues to shape the future of urban and environmental design.