Ricardo Osorio | Clinical Neuroscience | Best Researcher Award

Dr. Ricardo Osorio | Clinical Neuroscience | Best Researcher Award

Dr. Ricardo S. Osorio is a tenured Associate Professor of Psychiatry and Radiology at NYU Grossman School of Medicine, where he directs the Healthy Brain Aging and Sleep Center and serves as Director of the Biomarker Core within the NYU Alzheimer’s Disease Research Center. A physician-scientist, Dr. Osorio investigates the interplay of sleep, vascular, and inflammatory mechanisms in Alzheimer’s disease, integrating multimodal biomarkers, neuroimaging, and detailed clinical phenotyping. He has led several landmark studies, including trials on sleep apnea, amyloid and tau accumulation, brain energetics, and locus coeruleus dysfunction, exploring how sleep and metabolic factors influence cognitive decline and neurodegeneration. His work has significantly advanced translational biomarker development, assay harmonization, and inclusive recruitment in aging research. Dr. Osorio has published over 130 peer-reviewed articles in top journals such as JAMA Neurology, Annals of Neurology, Sleep, Alzheimer’s & Dementia, Lancet, and Brain, contributing to more than 8,369 citing documents, with a total citation count of 9,893 and an h-index of 44. He serves on multiple editorial boards, including Sleep Medicine Reports, and has provided expert peer review for leading journals worldwide. His collaborative network spans the NYU Alzheimer’s Disease Research Center, Mount Sinai, the ENIGMA-Sleep Consortium, and numerous national and international aging and sleep research initiatives, mentoring the next generation of clinician-scientists while shaping the field of sleep and neurodegeneration.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

  1. Author(s). (Year). Disordered sleep and painful diabetic neuropathy (PDN): A review of the literature on pathophysiology, pharmacologic and nonpharmacologic treatment options, and future directions. Journal Name, Volume(Issue), pages.

  2. Author(s). (2025). EEG slow oscillations and overnight spatial navigational memory performance in CPAP-treated obstructive sleep apnea. Sleep, Volume(Issue), pages.

  3. Author(s). (2025). High-frequency oscillations >250 Hz in people with Down syndrome and associated Alzheimer’s disease dementia. Alzheimer’s & Dementia, Volume(Issue), pages.

  4. Author(s). (2025). Impact of Alzheimer’s disease on sleep in adults with Down syndrome. Alzheimer’s & Dementia, Volume(Issue), pages.

  5. Author(s). (2025). Sleep-wake variation in body temperature regulates tau secretion and correlates with CSF and plasma tau. Journal of Clinical Investigation, Volume(Issue), pages.

  6. Author(s). (2025). The stability of slow-wave sleep and EEG oscillations across two consecutive nights of laboratory polysomnography in cognitively normal older adults. Journal of Sleep Research, Volume(Issue), pages.

  7. Author(s). (2025). Two-year longitudinal outcomes of subjective cognitive decline in Hispanics compared to non-Hispanic Whites. Journal of Geriatric Psychiatry and Neurology, Volume(Issue), pages.

  8. Author(s). (Year). Enhancing sleep, wakefulness, and cognition with transcranial photobiomodulation: A systematic review. Journal Name, Volume(Issue), pages.

  9. Author(s). (2024). The relationship between anxiety and levels of Alzheimer’s disease plasma biomarkers. Journal of Alzheimer’s Disease, Volume(Issue), pages.

  10. Author(s). (2024). The neutrophil to lymphocyte ratio associates with markers of Alzheimer’s disease pathology in cognitively unimpaired elderly people. Immunity and Ageing, Volume(Issue), pages.

Zhou Yu | Behavioral Neuroscience | Best Researcher Award

Dr. Zhou Yu | Behavioral Neuroscience | Best Researcher Award

Dr. Yu Zhou is a postdoctoral researcher at Army Engineering University, specializing in the intersection of neuroscience, computer vision, and target detection. His research primarily focuses on deceptive visual design for both human and machine perception, exploring how visual stimuli can influence detection, recognition, and cognitive processing. Zhou has conducted pioneering studies on camouflage and optical deception, utilizing EEG-based brain functional network analysis to evaluate target visibility and cognitive responses. His work integrates principles from weapon science, biomedical engineering, and computer science to develop comprehensive models of visual perception and deception. Representative publications include investigations into neural responses to camouflage targets with varying exposure signs, the impact of color differences on brain activation patterns, and feasibility assessments of optical camouflage effects. Through these studies, he contributes to a deeper understanding of how visual designs can manipulate human attention and computer vision systems, providing actionable insights for defense technology applications. Zhou’s research emphasizes rigorous quantitative evaluation methods, leveraging neurophysiological data to inform the design of effective deceptive visual patterns. With an h-index of 2 and multiple citations, his work demonstrates a growing influence in fields spanning neuroscience-informed computer vision, perceptual deception, and applied optical camouflage.

Profiles: Scopus | Reasearch Gate

Featured publication

Author(s). (2024). Neural responses to camouflage targets with different exposure signs based on EEG. Neuropsychologia.

Dipesh | Computational Neuroscience | Best Researcher Award

Assist. Prof. Dr. Dipesh | Computational Neuroscience | Best Researcher Award

Assist. Prof. Dr. Dipesh | SR University | India

Dr. Dipesh is a dedicated mathematician specializing in mathematical modeling, with extensive experience in both academic and research domains. He has made significant contributions to applied mathematics, particularly in areas intersecting numerical methods, AI/ML, and fluid dynamics. Dr. Dipesh has actively organized and coordinated multiple academic programs, including national workshops, faculty development programs, and departmental initiatives, demonstrating strong leadership in fostering educational and research excellence. His efforts in coordinating the Department of Intellectual Property Rights and successfully conducting events such as RAFAS highlight his commitment to academic growth and institutional development. Academically, he has pursued rigorous training from undergraduate to postdoctoral levels, culminating in advanced research at Harran University, Turkey. Dr. Dipesh’s scholarly output includes 30 documents that have been cited 103 times, reflecting an h-index of 7, underscoring the impact and relevance of his research contributions in applied mathematics and related interdisciplinary fields. His approach emphasizes quality teaching, student placement, institutional ranking, and enhancing the overall goodwill of the organizations he serves. Driven by a passion for tackling challenges and improving systems with limited resources, Dr. Dipesh continually seeks to connect with external environments, promote collaborative work, and advance the reach and recognition of academic institutions.

Profiles: Scopus | Orcid | Google Scholar | Research Gate | Linked In

Featured Publications

  1. Mathematical model of Cynodon Dactylon’s allelopathic effect on perennial ryegrass for exploring plant-plant interactions based upon ordinary differential equations. (2025). Partial Differential Equations in Applied Mathematics.

  2. Modelling the role of delay in blood flow dynamics in human body using delay differential equations. (2025). Physica A: Statistical Mechanics and Its Applications.

  3. On the modeling the impact of delay on stock pricing fluctuations using delay differential equations. (2025). Physica A: Statistical Mechanics and Its Applications.

Noreen Kamal | Translational Neuroscience | Best Researcher Award

Assoc. Prof. Dr. Noreen Kamal | Translational Neuroscience | Best Researcher Award

Assoc. Prof. Dr. Noreen Kamal | Dalhousie University | Canada

Dr. Noreen Kamal, Ph.D., P.Eng., is an Associate Professor of Industrial Engineering at Dalhousie University, Canada, with cross-appointments in the Departments of Community Health and Epidemiology and Medicine (Neurology). Her research lies at the intersection of health systems engineering and clinical neuroscience, focusing on the optimization of stroke care systems, development of data-driven quality improvement frameworks, and evaluation of biomedical devices for stroke rehabilitation. Dr. Kamal has played a pivotal role in advancing integrated approaches to enhance the efficiency, safety, and accessibility of acute stroke services across Canada. Prior to joining Dalhousie University, she held academic and leadership positions at the University of Calgary and the University of British Columbia, contributing extensively to clinical research and health technology innovation. Her work bridges engineering, medicine, and health policy, emphasizing interdisciplinary collaboration and patient-centered outcomes. With 107 scientific publications, 8,033 citations, and an h-index of 22, Dr. Kamal has established herself as a recognized scholar in healthcare systems improvement and translational neuroscience. Her scholarly and professional contributions continue to drive evidence-based innovation in stroke systems of care, supporting better clinical outcomes and sustainable health service delivery.

Profiles: Scopus | Google Scholar | Research Gate | Linked In

Featured Publications

Author(s). (2025). Exploring differences in stroke treatment between urban and rural hospitals: A thematic analysis of practices in Canada. Canadian Journal of Neurological Sciences.

Author(s). (2025). Designing a patient outcome clinical assessment tool for modified Rankin Scale: “You feel the same way too”. Informatics.

Author(s). (2025). Predicting ischemic stroke patients to transfer for endovascular thrombectomy using machine learning: A case study. Healthcare (Switzerland).

Author(s). (2025). Incident prescriptions for common cardiovascular medications: Comparison of recent versus pre-2020 medication adherence and discontinuation in three universal health care systems. BMC Cardiovascular Disorders.

Author(s). (2025). Rising out-of-hospital mortality in Canada during 2020–2022: A striking impact observed among young adults. Canadian Journal of Public Health.

Author(s). (2025). Discrete event simulation model of an acute stroke treatment process at a comprehensive stroke center: Determining the ideal improvement strategies for reducing treatment times. Journal of the Neurological Sciences.

Author(s). (2025). Validation of the Passive Surveillance Stroke Severity Score in three Canadian provinces. Canadian Journal of Neurological Sciences.

Author(s). (2025). A stochastic optimization model for designing disaster relief networks with congestion, disruption and distributional ambiguity. Infor.

Author(s). (2025). Improving access and efficiency of acute ischemic stroke treatment across four Canadian provinces: A stepped-wedge trial. Frontiers in Neurology.

Author(s). (2025). The acute stroke system of treatment across Canada: Findings from a national stroke centre survey. Canadian Journal of Neurological Sciences.

Lin Xiao | Cellular Neuroscience | Best Researcher Award

Dr. Lin Xiao | Cellular Neuroscience | Best Researcher Award

Dr. Lin Xiao | Institute for Brain Research and Rehabilitation | China

Dr. Lin Xiao is a distinguished Professor of Neuroscience at the Institute for Brain Research and Rehabilitation, South China Normal University, whose pioneering research has significantly advanced understanding of oligodendrocyte biology and myelin plasticity. His work elucidates the mechanisms by which adaptive myelination contributes to motor learning and memory, proposing a novel “biphasic plasticity model” that distinguishes distinct phases of learning and consolidation. Dr. Xiao’s research has been published in leading journals including Nature Neuroscience, Science, Nature Communications, and Advanced Science, collectively garnering over 2,800 citations and an h-index of 28, with approximately 20 peer-reviewed articles. His landmark paper in Nature Neuroscience has become a classic reference with over 500 citations, demonstrating substantial influence in the field. He has led multiple projects funded by the National Natural Science Foundation of China, including completed and ongoing studies, and established major collaborations with institutions such as University College London. His research areas include glial–neuron interactions, mechanisms of remyelination, neurodevelopmental disorders such as autism, and psychiatric disorders including depression. These contributions have been recognized with national awards and have opened promising avenues for therapeutic strategies in demyelinating and cognitive disorders.

Profiles: Google Scholar | Orcid | Research Gate  

Featured Publications

Marques, S., Zeisel, A., Codeluppi, S., Van Bruggen, D., Mendanha Falcão, A., et al. (2016). Oligodendrocyte heterogeneity in the mouse juvenile and adult central nervous system. Science, 352(6291), 1326–1329.

Xiao, L., Ohayon, D., McKenzie, I. A., Sinclair-Wilson, A., Wright, J. L., Fudge, A. D., et al. (2016). Rapid production of new oligodendrocytes is required in the earliest stages of motor-skill learning. Nature Neuroscience, 19(9), 1210–1217.

Liu, S., Yu, M., He, Y., Xiao, L., Wang, F., Song, C., Sun, S., Ling, C., & Xu, Z. (2008). Melittin prevents liver cancer cell metastasis through inhibition of the Rac1‐dependent pathway. Hepatology, 47(6), 1964–1973.

Li, C., Xiao, L., Liu, X., Yang, W., Shen, W., Hu, C., Yang, G., & He, C. (2013). A functional role of NMDA receptor in regulating the differentiation of oligodendrocyte precursor cells and remyelination. Glia, 61(5), 732–749.

Feng, P. A. N. (2003). Fast mode decision for intra prediction. JVT-G013, March 2003.

Li, Y. X., Ding, S. J., Xiao, L., Guo, W., & Zhan, Q. (2008). Desferoxamine preconditioning protects against cerebral ischemia in rats by inducing expressions of hypoxia inducible factor 1α and erythropoietin. Neuroscience Bulletin, 24(2), 89–95.

Hiroshi Nagase | Neuropharmacology | Best Researcher Award

Prof. Hiroshi Nagase | Neuropharmacology | Best Researcher Award

Prof. Hiroshi Nagase | University of Tsukuba | Japan

Prof. Hiroshi Nagase is a distinguished Japanese scientist recognized for his pioneering contributions to medicinal chemistry and drug discovery. He earned his B.S., M.S., and Ph.D. degrees in Chemistry from Nagoya University, Japan, and later served as a Visiting Scientist at the University of Minnesota’s Department of Medicinal Chemistry. Dr. Nagase began his professional career at Toray Industries Inc., where he advanced from Researcher to Director in the Basic Research Laboratories. He later joined Kitasato University’s School of Pharmacy as a Professor and subsequently served as a Principal Investigator and Professor at the International Institute for Integrative Sleep Medicine (IIIS) under the World Premier International Research Center Initiative at the University of Tsukuba, where he now holds the title of Professor Emeritus. His academic and research influence extended through adjunct professorships at the University of Tokyo, the University of Nagasaki, Toyohashi Polytechnic College, and Nagoya University. Dr. Nagase has authored 39 scientific documents, which have collectively garnered 279 citations from 189 sources, reflecting his substantial impact on the field. With an h-index of 10, his research continues to inspire advancements in medicinal chemistry, neuropharmacology, and therapeutic innovation.

Profiles: Scopus | Research Gate

Featured Publication

Nagase, H. (2025). Development of novel bioactive alkaloids based on specific reactions of the 4,5-epoxymorphinan framework. Synlett.

[Authors not listed]. (2025). Delta opioid receptor agonists activate PI3K–mTORC1 signaling in parvalbumin-positive interneurons in mouse infralimbic prefrontal cortex to exert acute antidepressant-like effects. Molecular Psychiatry.

Musawer Hakimi | Systems Neuroscience | Best Researcher Award

Mr. Musawer Hakimi | Systems Neuroscience | Best Researcher Award

Mr. Musawer Hakimi | Samangan University | Afghanistan

Mr. Musawer Hakimi is an accomplished Assistant Professor at Samangan University, specializing in Computer Science. He holds a Bachelor’s degree in Computer Science from India and a Master’s degree in Information Technology from Kabul University. Demonstrating a strong commitment to lifelong learning, he has earned 25 professional certificates in Computer Science from India, along with two specialized certifications in Ethical Hacking and Oracle Database from the United States. His academic excellence and research contributions have positioned him as a respected scholar with 3 published documents, 13 citations, and an h-index of 1. Mr. Hakimi’s scholarly work has been featured in reputable international journals across the United Kingdom, the United States, Turkey, Sweden, and Indonesia, reflecting his active engagement in global research networks. Beyond his research achievements, he is dedicated to nurturing future computer scientists through his teaching and mentorship at the Public University of Afghanistan, where he plays an instrumental role in advancing computer science education. His interdisciplinary expertise, international collaborations, and consistent scholarly output underscore his impact as an educator, researcher, and thought leader in the evolving field of computer science, contributing to the growth of academic excellence and innovation within Afghanistan and the broader global academic community.

Profiles: Scopus | Orcid | Google Scholar | Research Gate

Featured Publications

Quraishi, T., Ulusi, H., Muhid, A., Hakimi, M., & Olusi, M. R. (2024). Empowering students through digital literacy: A case study of successful integration in a higher education curriculum. Journal of Digital Learning and Distance Education, 2(9), 667–681.

Fazil, A. W., Hakimi, M., Shahidzay, A. K., & Hasas, A. (2024). Exploring the broad impact of AI technologies on student engagement and academic performance in university settings in Afghanistan. RIGGS: Journal of Artificial Intelligence and Digital Business, 2(2), 56–63.

Hakimi, M., Katebzadah, S., & Fazil, A. W. (2024). Comprehensive insights into e-learning in contemporary education: Analyzing trends, challenges, and best practices. Journal of Education and Teaching Learning (JETL), 6(1), 86–105.

Hakimi, N., Hakimi, M., Hejran, M., Quraishi, T., Qasemi, P., Ahmadi, L., & others. (2024). Challenges and opportunities of e-learning for women’s education in developing countries: Insights from Women Online University. EDUTREND: Journal of Emerging Issues and Trends in Education, 1(1), 57–69.

Hasas, A., Hakimi, M., Shahidzay, A. K., & Fazil, A. W. (2024). AI for social good: Leveraging artificial intelligence for community development. Journal of Community Service and Society Empowerment, 2(2), 196–210.

Fazil, A. W., Hakimi, M., Sajid, S., Quchi, M. M., & Khaliqyar, K. Q. (2023). Enhancing internet safety and cybersecurity awareness among secondary and high school students in Afghanistan: A case study of Badakhshan Province. American Journal of Education and Technology, 2(4), 50–61.

Alam, M. I., Khatri, S., Shukla, D. K., Misra, N. K., Satpathy, S., & Hakimi, M. (2025). Blockchain-based coal supply chain management system for thermal power plants. Discover Computing, 28(1), 1–32.

Kailas Chavan | Neuropharmacology | Best Researcher Award

Mr. Kailas Chavan | Neuropharmacology | Best Researcher Award

Mr. Kailas Chavan | Indian Institute of Technology Jodhpur | India

Kailas Arjun Chavan is a doctoral researcher at the Indian Institute of Technology Jodhpur, specializing in organic chemistry under the mentorship of Dr. Rohan D. Erande. His Ph.D. research focuses on the isolation and synthesis of bioactive scaffolds, including bis-indolyl compounds, flavonoids, and constituents of Pterocarpus marsupium, alongside the development of nickel-catalyzed direct conversion of alcohols to trans-cinnamonitriles. He completed his M.Sc. in Organic Chemistry at Dr. Babasaheb Ambedkar Marathwada University, where he investigated Cs₂CO₃-catalyzed reactions for the efficient synthesis of dihydroquinazolin-4(1H)-one. Kailas has contributed to the scientific community through 6 publications, amassing 94 citations. His research interests bridge synthetic methodology with bioactive compound exploration, aiming to advance medicinal chemistry and sustainable synthesis. Kailas’s work reflects a strong commitment to chemical innovation, positioning him as a promising emerging scientist in his field.

Profiles: Scopus | Google Scholar | Research Gate | Linked In

Featured Publications

Chavan, K. A., Shukla, M., Chauhan, A. N. S., Maji, S., Mali, G., Bhattacharyya, S., … (2022). Effective synthesis and biological evaluation of natural and designed bis(indolyl)methanes via taurine-catalyzed green approach. ACS Omega, 7(12), 10438–10446.

Mali, G., Maji, S., Chavan, K. A., Shukla, M., Kumar, M., Bhattacharyya, S., … (2022). Effective synthesis and biological evaluation of functionalized 2,3-dihydrofuro[3,2-c]coumarins via an imidazole-catalyzed green multicomponent approach. ACS Omega, 7(40), 36028–36036.

Shivam, S., Chavan, K. A., Chauhan, A. N. S., Erande, R. D. (2023). Recent advances in [3+2]-cycloaddition-enabled cascade reactions: Application to synthesize complex organic frameworks. Synlett, 34(07), 709–728.

Mali, G., Chauhan, A. N. S., Chavan, K. A., Erande, R. D. (2021). Development and applications of double Diels‐Alder reaction in organic synthesis. Asian Journal of Organic Chemistry, 10(11), 2848–2868.

Sharma, V., Chavan, K. A., Mali, G., Sarkar, D., Lama, P., Majumder, M., … (2023). A catecholaldimine-based NiII-complex as an effective catalyst for the direct conversion of alcohols to trans-cinnamonitriles and aldehydes. The Journal of Organic Chemistry, 88(11), 7448–7453.

Chavan, K. A., Sonawane, O. A., Erande, R. D. (2025). Novel metabolites from Pterocarpus marsupium: Structural characterization and biological relevance. Tetrahedron Letters, 155820.

Masoud Kargar | Computational Neuroscience | Best Researcher Award

Assist. Prof. Dr. Masoud Kargar | Computational Neuroscience | Best Researcher Award

Assist. Prof. Dr. Masoud Kargar | Islamic Azad University | Iran

Dr. Masoud Kargar is an Assistant Professor in the Department of Computer Engineering at Islamic Azad University, Tabriz Branch, specializing in artificial intelligence, machine learning, reinforcement learning, and software system engineering. He earned his bachelor’s degree in applied mathematics, master’s degree in software engineering, and Ph.D. in software engineering with a focus on modularization of multi-programming software systems. Dr. Kargar has extensive academic experience, having taught a wide range of undergraduate, master’s, and doctoral courses in advanced programming, algorithms, software engineering, data mining, big data, project management, and natural language processing across multiple universities. He also serves as the Director of Information and Communication Technology and leads the development of various software systems. Dr. Kargar is a member of the editorial board of the Iranian Journal of Computer Science (Springer) and has published 19 documents, which have been cited 89 times, giving him an h-index of 6. His research contributions have significantly advanced the fields of machine learning and software engineering, and his academic leadership continues to inspire both students and colleagues. Dr. Kargar remains committed to fostering innovation and excellence in computer engineering education and research.

Profiles: Scopus | Google Scholar | Orcid | Research Gate

Featured Publications

Karegar, M., Isazadeh, A., Fartash, F., Saderi, T., & Navin, A. H. (2008). Data-mining by probability-based patterns. Proceedings of the 30th International Conference on Information Technology Interfaces, 28.

Kargar, M., Isazadeh, A., & Izadkhah, H. (2019). Multi-programming language software systems modularization. Computers & Electrical Engineering, 80, 106500.

Kargar, M., Isazadeh, A., & Izadkhah, H. (2017). Semantic-based software clustering using hill climbing. 2017 International Symposium on Computer Science and Software Engineering.

Kargar, M., Isazadeh, A., & Izadkhah, H. (2020). Improving the modularization quality of heterogeneous multi-programming software systems by unifying structural and semantic concepts. Journal of Supercomputing, 76(1), 17.

Navin, A. H., Fesharaki, M. N., Mirnia, M., & Kargar, M. (2007). Modeling of random variable with digital probability hyper digraph: Data-oriented approach. Proceedings of World Academy of Science, Engineering and Technology, 25, 25.

Bayani, A., & Kargar, M. (2024). LDCNN: A new arrhythmia detection technique with ECG signals using a linear deep convolutional neural network. Physiological Reports, 12(17), e16182.

Karegar, M., Saderi, T., Isazadeh, A., & Fartash, F. (2008). Electronic consulting in marketing. 2008 3rd International Conference on Information and Communication Technology, 5.

Gang Cao | Behavioral Neuroscience | Best Researcher Award

Mr. Gang Cao | Behavioral Neuroscience | Best Researcher Award

Anhui University of Finance and Economics | China

Gang Cao (Ph.D.) is a Lecturer at the International Business School, Anhui University of Finance and Economics, with academic training in Business Administration and Management Science and Engineering from Shanghai University and Anhui University of Finance and Economics. His research focuses on AI capabilities, entrepreneurship, and innovation, and he has published in leading international journals such as the Journal of Business Research, Management and Organization Review, R&D Management, Plos One, and the International Journal of Conflict Management, as well as in top Chinese journals including Journal of Management Sciences in China and Journal of Economic Management. He has authored and co-authored multiple high-impact studies addressing themes such as entrepreneurial well-being, entrepreneurial failure and reentry, bricolage and disruptive innovation, digital identity change, impression management, and the integration of artificial intelligence with entrepreneurship and business model innovation. His work combines quantitative, qualitative, and computational methodologies, offering both theoretical contributions and practical insights into entrepreneurial behavior and firm evolution. Gang Cao has achieved an h-index of 5, with 11 documents and 102 citations, reflecting his growing academic impact and recognition in the fields of entrepreneurship, innovation management, and digital transformation. Through his interdisciplinary and collaborative research, he continues to advance understanding of the complex dynamics driving entrepreneurial success and organizational performance.

Profiles: Google Scholar

Featured Publications

“Exploring the relationship between entrepreneurial failure and conflict between work and family from the conservation of resources perspective.”

“Entrepreneurial Bricolage and Disruptive Innovation: The Joint Effect of Learning From Failure and Institutional voids.”

“Striking the balance: Configurations of causation and effectuation principles for SME performance.”