William Blumentals | Clinical Neuroscience | Excellence in Research Award

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Dr. William Blumentals | Clinical Neuroscience | Excellence in Research Award

Dr. William Blumentals | Sanofi | United States

Dr. William A. Blumentals is an accomplished epidemiologist and pharmaceutical executive recognized for his leadership in pharmacoepidemiology, real-world evidence generation, and global health outcomes research. He serves as Associate Vice President and Head of Specialty Care Pharmacoepidemiology at Sanofi in Cambridge, Massachusetts, where he oversees a multinational team of epidemiologists across the United States and Europe, driving innovation in inflammation, immunology, oncology, and rare disease research. With a Ph.D. in Epidemiology from the University of South Florida, along with advanced degrees in Statistics, Epidemiology, and Biology, Dr. Blumentals has held senior positions at leading organizations including Shire Pharmaceuticals, Shionogi Inc., and Hoffmann-La Roche. His expertise spans strategic development of large-scale observational studies, organizational leadership, and cross-functional collaboration to optimize evidence-based decision-making in healthcare. As a thought leader in real-world evidence and outcomes research, he has contributed significantly to advancing global epidemiological practices. Dr. Blumentals has authored 36 scientific documents, accumulated 1,594 citations from 1,463 documents, and holds an h-index of 23, reflecting his strong scientific influence and impact in epidemiology and pharmaceutical research.

Profile: Scopus

Featured Publications

Multiple sclerosis and the association with inflammatory bowel disease: Results from a retrospective cohort study. (2025). Multiple Sclerosis and Related Disorders.


Cytokine release syndrome risk model with T-cell engaging therapies. (2025). Cytotherapy.


Evaluating the accuracy of responses by large language models for information on disease epidemiology. (2025). Pharmacoepidemiology and Drug Safety.

Kushal J | Clinical Neuroscience | Best Researcher Award

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Mr. Kushal J | Clinical Neuroscience | Best Researcher Award

Mr. Kushal J |  Acharya and B M Reddy College of Pharmacy | India

Kushal J’s research focuses on pharmaceutical analysis, drug formulation, and healthcare innovation, reflecting a deep interest in bridging traditional and modern approaches to drug development. His work includes the formulation, development, and evaluation of an anti-acne serum using cow’s urine, a study that explores bioactive natural resources for dermatological applications. He has also contributed to analytical chemistry through his project on analytical method development and validation for identifying selected genotoxic impurities in bulk and pharmaceutical dosage forms by the RP-HPLC DAD method, presented at the JSS Pharmanecia International Research Conference. His academic training emphasizes analytical instrumentation, including HPLC, UV-Vis spectrophotometry, and dissolution testing, supported by a strong understanding of Good Laboratory Practices (GLP) and Good Manufacturing Practices (GMP). He has further strengthened his theoretical foundation through certifications in Food Chemistry and Biomedical Research. Kushal’s growing research portfolio highlights his dedication to advancing pharmaceutical quality control, regulatory compliance, and innovation in formulation science. His goal is to apply analytical and formulation expertise toward developing safer, more effective, and sustainable pharmaceutical products, contributing to the evolving fields of pharmaceutical technology, analytical method development, and health informatics.

Profile: Orcid

Featured Publication

Kushal, J., Loganathan, C. G., Rajesh, R., Dutta, S., Paik, A., Dasgupta, A., Reddy, G. N. N., & Suchindar, A. (2025). Recent advances in quinoline derivatives: Biological and medicinal insights. ChemistrySelect.

Seyyed Ali Zendehbad | Clinical Neuroscience | Best Researcher Award

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Dr. Seyyed Ali Zendehbad | Clinical Neuroscience | Best Researcher Award

Dr. Seyyed Ali | Zendehbad University of Mazandaran | Iran

Dr. Seyyed Ali Zendehbad is a multidisciplinary researcher specializing in biomedical signal processing, cognitive computational neuroscience, and neurorehabilitation technologies. His research integrates deep learning, pattern recognition, and multimodal biological data modeling to enhance fatigue detection and neurorehabilitation systems. He has authored several peer-reviewed papers in reputable journals such as Scientific Reports, IEEE Access, Sensing and Bio-Sensing Research, and Healthcare Technology Letters, focusing on hybrid AI frameworks, EMG signal processing, and muscle synergy-based biofeedback mechanisms. Dr. Zendehbad’s work on developing intelligent rehabilitation systems, including his models like TraxVBF and FatigueNet, contributes to advancing telemonitoring and assistive technologies for neurological recovery. His scholarly output includes more than 25 documents, over 600 citations, and an h-index of 12, reflecting his growing impact in computational neuroscience and biomedical engineering. Recognized for innovation, he has achieved first-place awards in multiple national startup competitions and was honored with the Best Poster Award at the Congress of Neurology and Clinical Electrophysiology of Iran. As a postdoctoral researcher at the University of Mazandaran, his ongoing work emphasizes integrating trustworthy AI into telehealth systems, promoting equitable and efficient digital healthcare delivery through interdisciplinary research and technological innovation.

Profile: Orcid

Featured Publications

1. Mazrooei Rad, E., Mazinani, S. M., & Zendehbad, S. A. (2025). Diagnosis of Alzheimer’s disease using non-linear features of ERP signals through a hybrid attention-based CNN-LSTM model. Computer Methods and Programs in Biomedicine Update, 5, 100192.

2. Zendehbad, S. A., Sharifi Razavi, A., Tabrizi, N., & Sedaghat, Z. (2025). A systematic review of artificial intelligence techniques based on electroencephalography analysis in the diagnosis of epilepsy disorders: A clinical perspective. Epilepsy Research, 207, 107582.

3. Mazrooei Rad, E., Zendehbad, S. A., & Hosseinzadeh, V. (2025). Fetal QRS complex detection based on adaptive filters and peak detection. Research on Biomedical Engineering, 41(3), 424–438.

4. Zendehbad, S. A., Ghasemi, J., & Samsami Khodadad, F. (2025). FatigueNet: A hybrid graph neural network and transformer framework for real-time multimodal fatigue detection. Scientific Reports, 15(1), 640.

5. Safdel, A., Zendehbad, S. A., & Ghasemi, J. (2025). Advanced deep learning approaches for accurate and efficient suspicious behavior detection in surveillance videos. Computational Sciences and Engineering, 21(2), 1099.

Chun-An Cheng | Translational Neuroscience | Lifetime achievement Award

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Assist. Prof. Dr. Chun-An Cheng | Translational Neuroscience | Lifetime achievement Award

Assist. Prof. Dr. Chun-An Cheng | Tri-Service General Hospital | Taiwan

Assistant Professor Dr. Chun-An Cheng is a distinguished researcher affiliated with the Tri-Service General Hospital, Taiwan, known for his significant contributions to medical and clinical research. He has authored 73 scholarly documents, which have collectively garnered 658 citations across 620 publications, reflecting the wide impact and recognition of his scientific work. With an h-index of 14, Dr. Cheng has demonstrated consistent research productivity and influence within his field. His research encompasses multidisciplinary areas in clinical medicine, focusing on advancing diagnostic methodologies, therapeutic innovations, and patient-centered healthcare strategies. Through his collaborations and publications, Dr. Cheng has contributed to improving the understanding of complex medical conditions and enhancing evidence-based clinical practices. His dedication to translational research bridges the gap between laboratory findings and clinical applications, reinforcing his role as a key figure in the Taiwanese medical research community. Dr. Cheng continues to drive impactful studies that promote innovation, patient safety, and improved health outcomes, positioning him as a leading voice in contemporary clinical science.

Profiles: Scopus | Orcid | Research Gate

Featured Publications

  • (2025). Effects of exposure to air pollution and cold weather on acute myocardial infarction mortality. Atmosphere.

  • (2025). The risk of ischemic stroke in patients with chronic obstructive pulmonary disease and atrial fibrillation. Life.

  •  (2024). Increased risk of psychiatric disorder in patients with hearing loss: A nationwide population-based cohort study. Journal of Translational Medicine.

  • (2024). Diabetes mellitus and gynecological and inflammation disorders increased the risk of pregnancy loss in a population study. Life.

  • (2024). The influence of fine particulate matter and cold weather on emergency room interventions for childhood asthma. Life.

  • (2024). Impact of foodborne disease in Taiwan during the COVID-19 pandemic. Medicina (Lithuania).

  • (2024). Analyzing COVID-19 and air pollution effects on pediatric asthma emergency room visits in Taiwan. Toxics.

Wenxin Deng | Social and Cultural Neuroscience | Best Researcher Award

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Dr. Wenxin Deng | Social and Cultural Neuroscience | Best Researcher Award

Dr. Wenxin Deng | Soochow University | China

Dr. Wenxin Deng is a distinguished researcher at Soochow University, China, recognized for her contributions to the scientific community through impactful research publications and scholarly influence. She has authored 4 research documents that collectively have been cited in 43 other academic works, reflecting the growing recognition of her research contributions. With an h-index of 3, Dr. Deng’s scholarly output demonstrates both productivity and citation impact within her field. Her research is characterized by a strong commitment to advancing knowledge and fostering innovation across interdisciplinary areas. Through her publications, Dr. Deng has contributed valuable insights that have informed and guided ongoing investigations in her domain. Her academic efforts underscore a dedication to excellence, intellectual curiosity, and the continuous pursuit of solutions to complex scientific challenges. At Soochow University, she continues to play an active role in research development, mentoring, and collaboration, reinforcing her position as a promising academic contributing to China’s and the global scientific community’s advancement.

Profiles: Scopus | Orcid

Featured Publications

Deng, W. (2025). AI and knowledge sharing in team performance: Emotional intelligence as the mediator between coordination and performance. Sustainable Futures.

Deng, W., & Jiang, M. (2025). A multilevel fuzzy AHP model for green furniture evaluation: Enhancing resource efficiency and circular design through lifecycle integration. Systems.

Jiang, M., Deng, W., & Lin, H. (2024). Sustainability through biomimicry: A comprehensive review of bionic design applications. Biomimetics.

Paula Abola | Neuroscience & Education | Neuroscience Academic Distinction Award

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Mrs. Paula Abola | Neuroscience & Education | Neuroscience Academic Distinction Award

Mrs. Paula Abola | University of Jamestown | United States

Paula Abola is a clinical researcher and academic with a strong focus on Parkinson’s disease, clinical drug development, and chemical biology. She has earned advanced degrees in Clinical Research, Clinical Drug Development, and Medicinal Chemistry & Chemical Biology, completing dissertations that explored knowledge disparities and shared decision-making in Parkinson’s disease, as well as comparative efficacy studies of pharmacological interventions and novel synthetic approaches in chemical biology. Paula has extensive experience in higher education, serving as an adjunct professor at multiple international universities, where she designs and delivers graduate- and doctorate-level courses in systematic reviews, meta-analyses, survey research, research proposal writing, study design, statistical methods, and chemical biology, while also mentoring and supervising student research projects. Her work emphasizes bridging methodological rigor with practical applications in clinical and social research, including applications in pharmacological management and vaccine development. Paula’s research contributions are documented in 2 scholarly works, which have collectively received 2 citations, giving her an h-index of 1 and an i10-index of 0. Her academic and research endeavors reflect a dedication to advancing knowledge in clinical pharmacology, research methodology, and chemical biology while fostering the development of future researchers through mentorship and teaching.

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

Featured Publications

Abola, P., Lefebvre, K., & Wolden, M. (2025). Influence of sociodemographic variables on patient and practitioner knowledge of pharmacological management options for Parkinson’s disease. American Journal of Medical and Clinical Research & Reviews, 4(1), 1–16.

Abola, P., Wolden, M. (2024). Monoamine oxidase-B inhibitor rasagiline effects on motor and non-motor symptoms in individuals with Parkinson’s disease: A systematic review and meta-analysis. Advances in Parkinson’s Disease, 13(3), 27–56.

Abola, P., & Jabishvili, G. (2025). Incidence of adverse and safety events in individuals with Parkinson’s disease treated with catechol-O-methyltransferase inhibitor opicapone as an add-on to levodopa treatment. Prospects in Pharmaceutical Sciences.

Abola, P., & Lefebvre, K. (2025). Technological advancements in the reduction of Parkinsonian tremor: A scoping review. Topics in Geriatric Rehabilitation, 41(3), 162–170.

Abola, P., Wolden, B., & Wolden, M. (2025). Journal of Neurology & Neuropsychiatry. Neuropsychiatry, 2(1).

Abola, P., & Lefebvre, K. (2025). Technological advancements in the detection and quantification of Parkinsonian tremor: A scoping review. Topics in Geriatric Rehabilitation, 41(3), 154–161.

Abola, P., & Wolden, M. (2025). Intra-individual variations in voice variables among individuals with and without Parkinson’s disease. Cureus, 17(3).

Abola, P., & Lefebvre, K. M. (2025). Technological advancements in the rehabilitation of Parkinsonian tremor: A systematic review. 2025 Combined Sections Meeting (CSM).

Kareem Al-Khalil | Cognitive Neuroscience | Best Researcher Award

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Dr. Kareem Al-Khalil | Cognitive Neuroscience | Best Researcher Award

Dr. Kareem Al-Khalil | University of Wisconsin – Madison | United States

Kareem I. Al-Khalil is a Multimodal Imaging Scientist at the Institute on Aging, University of Wisconsin-Madison, with extensive expertise in human development, family sciences, and neuroscience. He earned his Ph.D. in Human Development & Family Sciences, focusing on differences in brain activation and connectivity among college students with varying mathematical abilities, and holds dual M.Sc. degrees in Psychology and Experimental Psychology, as well as a B.Sc. in Biology. His professional trajectory spans postdoctoral research and associate positions at Duke University School of Medicine and the Mind Research Network, where he contributed to understanding neurocognitive processes in psychiatric and behavioral contexts. He has also served as a research analyst, teaching assistant, and graduate instructor, gaining substantial experience in experimental design, psychometrics, and cognitive neuroscience. Al-Khalil’s research contributions include peer-reviewed publications on connectomics, brain network disruption in HIV and substance use, and structural connectivity alterations associated with chronic cannabis use. His work has garnered a total of 201 citations, with an h-index of 8 and an i10-index of 7, reflecting his influence in the fields of cognitive neuroscience and neuroimaging. Through his research, he advances understanding of brain function, network connectivity, and cognitive processes in health and disease, integrating behavioral science with multimodal imaging approaches.

Profiles: Google Scholar | Linked In

Featured Publications

Al-Khalil, K., Vakamudi, K., Witkiewitz, K., & Claus, E. D. (2021). Neural correlates of alcohol use disorder severity among nontreatment‐seeking heavy drinkers: An examination of the incentive salience and negative emotionality domains of the … Alcoholism: Clinical and Experimental Research, 45(6), 1200–1214.

Hou, J., Rajmohan, R., Fang, D., Kashfi, K., Al-Khalil, K., Yang, J., & Westney, W. (2017). Mirror neuron activation of musicians and non-musicians in response to motion captured piano performances. Brain and Cognition, 115, 47–55.

Niehuis, S., Reifman, A., Al-Khalil, K., Oldham, C. R., Fang, D., & O’Boyle, M. (2019). Functional magnetic resonance imaging activation in response to prompts of romantically disillusioning events. Personal Relationships, 26(2), 209–231.

Gonzales, J. U., James, C. R., Yang, H. S., Jensen, D., Atkins, L., & Thompson, B. J. (2016). Different cognitive functions discriminate gait performance in younger and older women: A pilot study. Gait & Posture, 50, 89–95.

Calderon-Delgado, L., Barrera-Valencia, M., Noriega, I., & Al-Khalil, K. (2020). Implicit processing of emotional words by children with post-traumatic stress disorder: An fMRI investigation. International Journal of Clinical and Health Psychology, 20(1), 46–53.

Noriega, I., Trejos-Castillo, E., Chae, Y., & Calderon-Delgado, L. (2021). Emotional memory processing in post‐traumatic stress disorder affected Colombian youth. International Journal of Psychology, 56(3), 387–393.

Kashfi, K., Al-Khalil, K., Hou, J., Fang, D., Anderson, R., Rajmohan, R., & Syapin, P. (2017). Hyper-brain connectivity in binge drinking college students: A diffusion tensor imaging study. Neurocase, 23(3–4), 179–186.

Kashfi, K., Fang, D., Hou, J., Al-Khalil, K., Anderson, R., Syapin, P. J., & O’Boyle, M. W. (2017). Spatial attention in binge-drinking and moderate-drinking college students: An fMRI investigation. Alcoholism Treatment Quarterly, 35(3), 260–278.

Swartz, M., Burton, F., Vakamudi, K., Al-Khalil, K., Witkiewitz, K., & Claus, E. D. (2021). Age dependent neural correlates of inhibition and control mechanisms in moderate to heavy drinkers. NeuroImage: Clinical, 32, 102875.

Yue Ding | Cognitive Neuroscience | Best Researcher Award

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Dr. Yue Ding | Cognitive Neuroscience | Best Researcher Award

Dr. Yue Ding | Shanghai Mental Health Center | China

Dr. Yue Ding is a distinguished neuroscientist and biomedical engineer whose research focuses on the neural mechanisms of music and rhythm-based interventions for affective and anxiety disorders, particularly in children and adolescents. With a Ph.D. in Neuroscience from Tsinghua University and a B.S. in Biomedical Engineering from Dalian University of Technology, Dr. Ding has extensive experience in both academic and industry settings, including leadership roles at Shanghai Mental Health Center, AI Institute at iFlytek, and Nielsen Consumer LLC, as well as a visiting scholar position at Johns Hopkins University. Dr. Ding’s research integrates neuroscience, artificial intelligence, and virtual reality to develop personalized interventions, including closed-loop music therapies, rhythm interactive training, and controllable music generation models, supported by numerous national and municipal grants. His work also explores neural oscillations in depression and anxiety, taste perception, and language impairments in Alzheimer’s patients. He is actively involved in professional organizations, including the Art Psychotherapy Committee, Music Psychology Committee, and editorial boards of prominent journals such as Scientific Reports and Frontiers in Psychiatry. With 17 published documents, Dr. Ding has garnered 228 citations and holds an h-index of 8, reflecting his influential contributions to the fields of neuroscience, neuroengineering, and mental health research.

Profiles: Scopus | Google Scholar | Linked In

Featured Publications

Ding, Y., Hu, X., Li, J., Ye, J., Wang, F., & Zhang, D. (2018). What makes a champion: The behavioral and neural correlates of expertise in multiplayer online battle arena games. International Journal of Human–Computer Interaction, 34(8), 682–694.

Ding, Y., Hu, X., Xia, Z., Liu, Y. J., & Zhang, D. (2021). Inter-brain EEG feature extraction and analysis for continuous implicit emotion tagging during video watching. IEEE Transactions on Affective Computing, 12(1), 92–102.

Ding, Y., Zhang, Y., Zhou, W., Ling, Z., Huang, J., Hong, B., & Wang, X. (2019). Neural correlates of music listening and recall in the human brain. Journal of Neuroscience, 39(41), 8112–8123.

Ding, Y., Chu, Y., Liu, M., Ling, Z., Wang, S., Li, X., & Li, Y. (2022). Fully automated discrimination of Alzheimer’s disease using resting-state electroencephalography signals. Quantitative Imaging in Medicine and Surgery, 12(2), 1063–1077.

Ding, Y., Gray, K., Forrence, A., Wang, X., & Huang, J. (2018). A behavioral study on tonal working memory in musicians and non-musicians. PLOS ONE, 13(8), e0201765.

Zhang, Y., Ding, Y., Huang, J., Zhou, W., Ling, Z., Hong, B., & Wang, X. (2021). Hierarchical cortical networks of “voice patches” for processing voices in human brain. Proceedings of the National Academy of Sciences of the United States of America, 118(44), e2103518118.

Zhou Yu | Behavioral Neuroscience | Best Researcher Award

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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.

Congbo Cai | Neurotechnology | Best Researcher Award

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Prof. Dr. Congbo Cai | Neurotechnology | Best Researcher Award

Prof. Dr. Congbo Cai | Xiamen University | China

Professor Congbo Cai is a distinguished researcher at the School of Electronic Science and Technology, Xiamen University, specializing in advanced Magnetic Resonance Imaging (MRI) technology development. His research encompasses ultra-fast imaging, multi-parametric quantitative MRI, deep learning reconstruction, novel neuroimaging techniques, and quantitative medical image analysis. He has led and contributed to numerous high-impact projects, including national key R&D programs, NSFC key projects, and international cooperative projects, with funding totaling several million yuan. His innovations include pioneering high-entropy encoding and overlapping-echo designs, enabling rapid, high-fidelity MRI mapping, and integrating physics-informed deep learning for enhanced image reconstruction and clinical applications. Professor Cai has published over 80 papers in leading journals such as NeuroImage, IEEE Transactions on Medical Imaging, and Medical Image Analysis. He holds 12 patents and serves on editorial boards, including Health and Metabolism, and as a guest editor for Frontiers in Neuroscience. His professional contributions extend to active membership and leadership roles in major MRI societies. His work has garnered significant academic recognition, with a citation count exceeding 2,300 across 872 documents, an h-index of 25, and an i10-index of 55. Professor Cai’s research continues to advance MRI science, bridging cutting-edge technology and clinical translation.

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

Featured publications

  • Author(s). (2018). Accelerating multi-slice spatiotemporally encoded MRI with simultaneous echo refocusing. Journal of Magnetic Resonance.

  • Author(s). (2018). Single-shot T2 mapping using overlapping-echo detachment planar imaging and a deep convolutional neural network. Magnetic Resonance in Medicine.

  • Author(s). (2018). Referenceless distortion correction of gradient-echo echo-planar imaging under inhomogeneous magnetic fields based on a deep convolutional neural network. Computers in Biology and Medicine.

  • Author(s). (2018). Weighted total variation using split Bregman fast quantitative susceptibility mapping reconstruction method. Chinese Physics B.

  • Author(s). (2018). Simultaneous single- and multi-contrast super-resolution for brain MRI images based on a convolutional neural network. Computers in Biology and Medicine.

  • Author(s). (2018). Motion-tolerant diffusion mapping based on single-shot overlapping-echo detachment (OLED) planar imaging. Magnetic Resonance in Medicine.