Tianyi Zhao | Neuroscience | Research Excellence Award

Published on by Global Academic Awards

Research Excellence Award

Tianyi Zhao
Affiliation The First Hospital of Jilin University
Country China
Scopus ID 55470158900
Documents 13
Citations 439
h-index 8
Subject Area Neuroscience
Event Global Academic Awards

Tianyi Zhao
The First Hospital of Jilin University, China

Tianyi Zhao is a researcher affiliated with The First Hospital of Jilin University, China, whose scholarly activities have contributed to interdisciplinary scientific advancement within the field of neuroscience and related biomedical research areas. The researcher has established an academic profile indexed within Scopus, reflecting measurable citation performance, publication visibility, and collaborative scientific engagement.[1] The recognition associated with the Research Excellence Award acknowledges sustained academic productivity, research dissemination, and scientific contribution within internationally indexed scholarly platforms.

The academic profile demonstrates documented publication activity, citation influence, and participation in research initiatives that contribute to contemporary scientific literature. The award evaluation framework recognizes researchers whose publications exhibit measurable academic impact and whose work supports the advancement of scientific inquiry through peer-reviewed dissemination.[2]

Abstract

The Research Excellence Award recognizes academic distinction demonstrated through publication quality, citation performance, interdisciplinary collaboration, and scholarly influence within the scientific community. Tianyi Zhao has developed a research portfolio indexed in international citation databases, contributing to the advancement of biomedical and neuroscience-related studies through peer-reviewed publications and collaborative scientific investigations.[1] The researcher’s academic metrics, including citation count and h-index, indicate measurable engagement with the global research community and sustained scholarly relevance.[3]

Keywords

Research Excellence Award; Tianyi Zhao; Neuroscience; Scopus Author Profile; Academic Recognition; Citation Impact; Biomedical Research; Scientific Publications; Research Metrics; Global Academic Awards

Introduction

Academic recognition awards serve as formal acknowledgements of scholarly achievement and research productivity within the international scientific ecosystem. Such recognitions commonly evaluate publication metrics, citation performance, research visibility, and contributions to disciplinary advancement.[4] The research profile associated with Tianyi Zhao demonstrates engagement with scientific publication practices and participation in peer-reviewed research dissemination.

The field of neuroscience continues to evolve through interdisciplinary integration involving molecular biology, biomedical technologies, clinical research methodologies, and analytical scientific approaches. Researchers contributing to these domains play an important role in expanding the scientific understanding of neurological systems, disease mechanisms, and translational biomedical applications.[5]

Research Profile

Tianyi Zhao is affiliated with The First Hospital of Jilin University in China and maintains a documented Scopus author profile indexed under Author ID 55470158900. The profile indicates 13 indexed documents, 439 citations, and an h-index value of 8, reflecting measurable scholarly impact across indexed literature sources.[1]

The researcher’s publication history includes scientific studies associated with analytical chemistry, biomedical investigation, and applied scientific methodologies relevant to neuroscience and interdisciplinary biomedical research. Indexed records demonstrate collaborative publication activity and participation in peer-reviewed scientific communication channels.[2]

  • Institutional Affiliation: The First Hospital of Jilin University
  • Research Region: China
  • Indexed Documents: 13
  • Total Citations: 439
  • Scopus h-index: 8
  • Primary Subject Area: Neuroscience

Research Contributions

The scholarly contributions attributed to Tianyi Zhao include participation in scientific investigations related to analytical probes, biomedical detection methodologies, and interdisciplinary research applications. One documented publication involves the synthesis of functionalized CdTe/ZnS nanoparticles for fluorescence detection applications, demonstrating engagement with advanced laboratory methodologies and applied scientific instrumentation.[2]

Research activities within biomedical and neuroscience-related domains frequently require cross-disciplinary integration involving molecular diagnostics, bioanalytical techniques, and translational research processes. Such interdisciplinary contributions support broader scientific understanding and facilitate methodological innovation within contemporary healthcare and life science research environments.[6]

Publications

Selected indexed publications and scholarly contributions associated with Tianyi Zhao include peer-reviewed scientific studies documented through Scopus indexing services and related citation databases.[1]

Research Impact

Research impact is commonly evaluated through citation analytics, publication dissemination, institutional collaboration, and scholarly influence within disciplinary literature. Tianyi Zhao’s citation profile demonstrates engagement from the broader academic community, with citations distributed across multiple scientific documents indexed within international databases.[1]

The h-index value of 8 indicates that multiple publications have achieved measurable citation visibility within scholarly communication networks. Citation performance metrics serve as one indicator of research influence and knowledge dissemination within the scientific ecosystem.[3]

Award Suitability

The Research Excellence Award recognizes researchers whose academic records demonstrate sustained publication activity, citation engagement, interdisciplinary collaboration, and measurable scholarly contribution. Tianyi Zhao’s indexed publication profile, citation metrics, and participation in peer-reviewed scientific dissemination align with evaluation frameworks commonly applied to international academic recognition programs.

The documented research activities and publication visibility support the suitability of the researcher for recognition within global academic award initiatives that emphasize research dissemination, scientific integrity, and contribution to evidence-based scientific advancement.[6]

Conclusion

Tianyi Zhao’s scholarly profile reflects continued engagement with scientific research, publication dissemination, and interdisciplinary collaboration within neuroscience and biomedical research environments. Indexed academic metrics, including citation counts and h-index performance, indicate measurable research visibility and scholarly participation within international scientific literature.[1]

The recognition associated with the Research Excellence Award acknowledges academic productivity, citation-based influence, and contributions to scientific advancement through peer-reviewed research dissemination and collaborative investigation.

References

  1. Elsevier. (n.d.). Scopus author details: Tianyi Zhao, Author ID 55470158900. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=55470158900
  2. Zhao, T. et al. (2015). Synthesis of functionalized CdTe/ZnS nanoparticles as probes for norfloxacin fluorescence detection. Chalcogenide Letters.
    https://www.researchgate.net/publication/290528045_Synthesis_of_functionalized_CdTeZnS_nanoparticles_as_probes_for_norfloxacin_fluorescence_detection
  3. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences.
    https://www.pnas.org/doi/10.1073/pnas.0507655102
  4. Kandel, E. R. et al. (2013). Principles of Neural Science. McGraw-Hill Education.
  5. National Institutes of Health. (n.d.). Biomedical and interdisciplinary research initiatives. 

Temitayo Fagbola | Machine Learning | Best Researcher Award

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Dr. Temitayo Fagbola | Machine Learning | Best Researcher Award

Dr. Temitayo Fagbola, University of Hull, England, United Kingdom

Dr. Temitayo Matthew Fagbola is a Teaching Fellow at the University of Hull, UK, specializing in Applied Artificial Intelligence, with research interests in generative AI, medical imaging, NLP, and ethical AI systems. He holds a PhD in Computer Science from LAUTECH, Nigeria, and has extensive academic experience in Nigeria, South Africa, and the UK. A Fellow of the Higher Education Academy (FHEA), he has earned multiple research grants and awards, including excellence in feedback and teaching. Dr. Fagbola has over 480 citations and serves on several editorial boards and technical committees.

Publication Profile

Scopus

Google Scholar

🎓 Educational Background

Dr. Temitayo Fagbola possesses a strong academic foundation in Computer Science. He recently completed a Postgraduate Certificate in Academic Practice at the University of Hull, UK (2023–2024) 🎓. He earned his Ph.D. in Computer Science from Ladoke Akintola University of Technology, Nigeria (2012–2015) 🧠, following an M.Sc. in Computer Science from the University of Ibadan (2009–2011) 💻. His academic journey began with a B.Tech. (Hons) in Computer Science from LAUTECH (2002–2007) 📘. This diverse educational background underpins his expertise in AI, data science, and academic teaching and research.

💼 Professional Experience

Dr. Temitayo Fagbola is currently a Teaching Fellow at the Centre of Excellence in Data Science, AI, and Modelling, University of Hull, UK (Oct. 2022–Present) 🇬🇧. He has served as a Senior Lecturer at FUOYE, Nigeria (2021–2022) and held research roles at Durban University of Technology, South Africa 🇿🇦. His academic journey includes roles as Lecturer and Assistant Lecturer at FUOYE (2012–2018) 👨‍🏫. His work focuses on Applied AI in Health 🧠, with expertise in CNNs, LLMs, denoising autoencoders, transfer learning, computer vision, NLP, and AI ethics

🏅 Honours, Awards

Dr. Temitayo Fagbola was awarded the prestigious Fellowship of the Higher Education Academy (FHEA), UK 🇬🇧 in June 2024. He won the Excellence in Feedback award and was a finalist for Excellence in Teaching at the University of Hull 🏆. His accolades include travel grants to NeurIPS 2019 in Canada 🇨🇦, FAT* Conference in the USA 🇺🇸, and Deep Learning events in South Africa 🇿🇦. He held a Postdoctoral Fellowship at Durban University of Technology and received a Best Paper Award in 2014 📝. His recognitions span academia, teaching excellence, and global AI forums

📜 Professional Certifications

Dr. Temitayo Fagbola holds multiple certifications including Aviatrix Multicloud Network Associate 🌐, Machine Learning Applications from Global AI Hub 🤖, and two Huawei ICT Associate credentials in Big Data and Routing & Switching 📊📡. He actively contributes to academic service as a reviewer on the FoSE Research Ethics Committee 🧪 and a member of the Recognised Teacher Status Working Group at the University of Hull 🇬🇧. As a module leader and lecturer in Applied AI 📘, he has co-supervised seven MSc dissertations and one PhD thesis, nurturing the next generation of AI and CS researchers

🔍 Research Focus

Dr. Temitayo Fagbola’s research lies at the intersection of Artificial Intelligence 🤖, Machine Learning 📈, and Cloud Computing ☁️, with impactful work in email classification ✉️, timetabling optimization 📅, and AI ethics ⚖️. His contributions span Natural Language Processing 🗣️, Computer Vision 🖼️, and human-centered AI systems 👥, often integrating metaheuristic algorithms and deep learning for real-world challenges. He’s also active in educational technology 🎓, COVID-19 smart health solutions 😷, and AI-powered predictive systems, showing a strong commitment to applied AI in public services and education sectors 🌍. His publications are widely cited, reflecting global scholarly influence

Conclusion

Dr. Temitayo Fagbola’s innovative research, international recognition, publication impact, and commitment to academic excellence, he is an excellent candidate for the Best Researcher Award. His work addresses real-world problems through advanced AI methods, making him not only a researcher of merit but a contributor to the global AI and data science community.

Publication Top Notes

📘 Computer-based test (CBT) system for university academic enterprise examination – 108 citations – 📅 2013
☁️ The Impact and Challenges of Cloud Computing Adoption on Public Universities – 93 citations – 📅 2014
📩 Hybrid GA-SVM for efficient feature selection in e-mail classification – 51 citations – 📅 2012
📚 Cloud Computing: Concepts, Architecture & Applications – 37 citations – 📅 2019
😷 Smart face masks for COVID-19 management – 21 citations – 📅 2022
🧠 Towards AI-based systems: Human-centered requirements – 20 citations – 📅 2019
🧮 Hybrid Metaheuristic Feature Extraction for Timetabling – 19 citations – 📅 2012
📱 Mobile ML Models for Student Performance Prediction – 15 citations – 📅 2018
📧 Optimized Feature Selection for Email Classification – 15 citations – 📅 2014
🎓 Transformational Roles of Edge Intelligence (Special Issue) – 12 citations – 📅 2024
🚀 Survey on Mobile Agent Migration Process – 12 citations – 📅 2016
🏥 ERP Implementation in Hospital Systems – 11 citations – 📅 2023

Frnaz Akbar | Neuroscience | Best Researcher Award

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Dr. Frnaz Akbar | Neuroscience | Best Researcher Award

Dr. Frnaz Akbar, National University Of Modern Languages, Pakistan

Dr. Frnaz Akbar is a dedicated computer science and software engineering educationist, researcher, and web developer with over a decade of experience in teaching and web development. She has consistently contributed to building student knowledge in computer science and is committed to high-quality education. Her expertise spans artificial intelligence, data mining, precision agriculture, IoT, and blockchain. Dr. Akbar is currently pursuing a PhD in Artificial Intelligence at Air University, Islamabad, and has a strong publication record, including studies on deep learning, pattern recognition, and EEG-based Alzheimer’s research. She has worked as a lecturer at NUML University and held teaching positions at prestigious institutions. Her technical proficiency includes MERN, Python, C++, and ASP.Net. Recognized for academic excellence, she has received multiple honors, including a Best Teacher Trophy and High Achiever Scholarships. Passionate about research and innovation, she continues to contribute significantly to computer science and AI.

Publication Profile

Scopus

Education 🎓

Dr. Frnaz Akbar is currently pursuing a PhD in Artificial Intelligence at Air University, Islamabad, focusing on machine learning and deep learning applications. She holds an MS in Software Engineering (2018-2020) from Bahria University, Islamabad, and a Master’s in Information Technology (2015-2017) from PMAS ARID University, Rawalpindi, both with first-division honors. Her Bachelor’s in Computer Science (2013-2015) was completed at Punjab University, Lahore, where she received a Role of Honor Certificate. Additionally, she earned a B.Ed. (2020-2022) from Sarhad University, Islamabad Campus, further strengthening her educational expertise. Her academic journey began with HSSC and SSC from Islamabad College F-6/2, where she maintained outstanding academic performance. Throughout her education, she has demonstrated excellence, securing High Achiever Scholarships and academic awards. With expertise in AI, IoT, and software development, her education reflects a strong foundation in research, programming, and innovative computing technologies.

Experience 👩‍🏫

Dr. Frnaz Akbar has extensive experience in academia and industry, specializing in computer science and software engineering. She is currently a Visiting Lecturer at NUML University, Islamabad, in the Department of Software Engineering. Previously, she served as a Senior Computer Science Teacher at IMCG F-10/2 (2017-2023) and ISS, G-13/1, Islamabad (2013-2017), where she mentored students and designed curricula. She has also been a Computer Tutor at Allama Iqbal Open University since 2020, providing part-time instruction. In addition to teaching, she worked as a Software Developer at K-Soft, Ministry of Defense, focusing on MIS applications. With expertise in AI, IoT, and software development, she has contributed significantly to research and education. Her teaching philosophy emphasizes innovation and hands-on learning, ensuring students acquire both theoretical and practical skills. She is passionate about integrating emerging technologies into education and has a proven track record of academic excellence.

Awards and Honors 🏆

Dr. Frnaz Akbar has been recognized for her outstanding contributions to education and research. She received the Best Teacher Trophy from IMCG F-10/2, Islamabad, for her exemplary performance in student development and academic excellence. During her MS at Bahria University, she was appointed as a Teacher Assistant, reflecting her strong command over software engineering concepts. She secured a High Achiever Scholarship in every semester of her MSc IT at PMAS ARID University, Rawalpindi, showcasing her dedication to academic excellence. Her bachelor’s degree at Punjab University earned her a Role of Honor Certificate, highlighting her exceptional academic performance. In her early education, she was awarded a certificate for high attendance at IMCG F-7/2 and secured the second position in SSC. These accolades demonstrate her commitment to education, mentorship, and research, reinforcing her position as a leader in computer science and software engineering.

Research Focus 🔬

Dr. Frnaz Akbar’s research interests revolve around cutting-edge technologies in artificial intelligence and data science. She specializes in AI-driven applications, including deep learning, data mining, and pattern recognition. Her work extends to precision agriculture, where she leverages AI for optimizing crop health analysis. She is also actively engaged in research on the Internet of Things (IoT) and edge computing, focusing on real-time data processing. Blockchain technology and its integration with AI for secure computing systems form another critical aspect of her research. One of her notable contributions is in healthcare AI, particularly Alzheimer’s disease detection using EEG signal analysis. She has published and submitted multiple research papers on AI applications in medical diagnostics and agricultural automation. Her research is highly interdisciplinary, combining machine learning, neural networks, and computational modeling to solve real-world problems, making significant contributions to AI and software engineering domains. 🚀

Publication Top Notes

📖 Optimized Approach in Requirements Change Management in Geographically Dispersed Environment (GDE), International Journal of Foundations of Computer Science, 2020

🌿 Identifying Lesions in Cotton Leaves Unconstrained Images using Deep Neural Network, Computers in Biology and Medicine, 2023 (Under Review)

🧠 Unlocking the Potential of EEG in Alzheimer’s Disease Research: Current Status and Pathways to Precision Detection, Foundations and Trends in Machine Learning, 2024 (Under Review)

📊 Assessing the Effects of Alzheimer Disease on EEG Signals using the Entropy Measure: A Meta-analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 (Under Review)

Hossein Hassani | Neural Network | Best Researcher Award

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Dr. Hossein Hassani | Neural Network | Best Researcher Award

Dr, Yasuj University of Medical Sciences, Iran

Dr. Hossein Hassani is a researcher and lecturer in Applied Mathematics and Numerical Analysis at Yasouj University of Medical Sciences, Iran. With a Ph.D. from Shahrekord University, he specializes in fractional calculus, optimal control problems, and biomathematics. His post-doctoral research focuses on nonlinear fractional models and their applications in engineering and medical sciences. Dr. Hassani’s expertise includes solving fractional differential equations, optimization techniques for disease models, and the use of neural networks in modeling. He has extensive teaching experience in mathematics, algorithms, and numerical computation. His work aims to bridge mathematical theory with practical applications in healthcare and engineering. 📚💻📊🔬

Publication Profile

Google Scholar

Academic Background 📚🎓

Dr. Hossein Hassani holds a comprehensive academic background in Applied Mathematics and Numerical Analysis. He completed his Ph.D. at Shahrekord University, Iran, in 2017, with a thesis on solving variable-order fractional differential equations using generalized polynomials. His M.Sc. and B.Sc. degrees were also in Applied Mathematics from the University of Sistan and Baluchestan. Dr. Hassani is currently pursuing a post-doctoral fellowship at the International College of Engineering, focusing on nonlinear fractional models and their applications in engineering and medical sciences. His research interests span fractional calculus, optimization methods, and biomathematics. 🔬💡

Academic Work Experience 🎓💼

Dr. Hossein Hassani has extensive teaching experience in various institutions across Iran. Since 2013, he has served as a lecturer at Yasouj University of Medical Sciences in the School of Health and Paramedical Sciences, and at Shahrekord University in the Faculty of Engineering and Faculty of Mathematical Sciences. He has also taught at Yasouj University’s Faculty of Engineering and Faculty of Science, as well as at Islamic Azad University, Yasouj Branch. His academic roles have focused on applied mathematics, numerical analysis, differential equations, and optimization techniques, enriching the academic environment with his knowledge and expertise. 📘🧑‍🏫

Teaching Expertise 📚👨‍🏫

Dr. Hossein Hassani has a rich teaching portfolio covering a wide range of mathematical and computational subjects. He has taught General Mathematics, Calculus, and Differential Equations, equipping students with fundamental mathematical knowledge. His expertise extends to Numerical Computation, Numerical Analysis, and the Numerical Solution of Ordinary Differential Equations, where he emphasizes problem-solving techniques. Additionally, Dr. Hassani has delivered courses on Modeling and Evaluation of Computer Systems, Advanced Algorithms, and Simulation, blending theoretical knowledge with practical applications. His courses foster analytical thinking and computational skills among students, contributing significantly to their academic development. 🔢💻📊

Research Areas 🔬📐

Dr. Hossein Hassani’s research spans several advanced topics in mathematics and its applications. His primary focus includes Optimal Control Problems, where he investigates methods for optimizing systems under certain constraints. He also explores Variable Order Fractional Differential Equations, Partial Differential Equations, and Orthogonal Polynomials, contributing to both theoretical and practical advancements. His work in Fractional Calculus and the Operational Matrix provides valuable insights into complex mathematical models. Additionally, Dr. Hassani delves into Biomathematics, applying mathematical tools to biological systems, particularly in the context of disease modeling and optimization techniques. 🧮🔍🧬

Research Interests 🔍💡

Dr. Hossein Hassani’s research interests are centered around the numerical solution of variable order fractional partial differential equations using optimization techniques. He applies these methods to find the best approximate solutions for complex disease models, aiming for optimal fractional control solutions. Additionally, Dr. Hassani is exploring new classes of nonlinear variable order fractional equations and optimal control problems. He is introducing innovative basis functions to improve mathematical models and is also leveraging neural network methods for enhancing disease model predictions, furthering both mathematical and medical research. 🧮💻🧬

Publication Top Notes
  • Application of fractional shifted Vieta-Fibonacci polynomials in nonlinear reaction diffusion equation with variable order time-space fractional derivative
    Year: 2025
  • An optimal solution of lung cancer mathematical model using generalized Bessel polynomials
    Cited by: 1
    Year: 2024
  • A new approach of generalized shifted Vieta-Fibonacci polynomials to solve nonlinear variable order time fractional Burgers-Huxley equations
    Year: 2024
  • An optimal solution for tumor growth model using generalized Bessel polynomials
    Cited by: 1
    Year: 2024
  • Generalization of Bernoulli polynomials to find optimal solution of fractional hematopoietic stem cells model
    Cited by: 2
    Year: 2024
  • A new approach based on the generalized Bessel polynomials to find optimal solution of hematopoietic stem cells model
    Cited by: 1
    Year: 2024
  • Bessel Polynomials: Application in Finding Optimal Solution of Fractional COVID-19 Model Using Lagrange Multipliers
    Cited by: 1
    Year: 2024
  • An optimization method for solving a general class of the inverse system of nonlinear fractional order PDEs
    Cited by: 6
    Year: 2024
  • Optimization of the approximate solution of the fractional squeezing flow between two infinite plates
    Year: 2024
  • Generalized Bernoulli–Laguerre Polynomials: Applications in Coupled Nonlinear System of Variable-Order Fractional PDEs
    Cited by: 13
    Year: 2024
  • Optimal solution of a fractional epidemic model of COVID-19.
    Cited by: 1
    Year: 2024
  • Optimal solution of nonlinear 2D variable-order fractional optimal control problems using generalized Bessel polynomials
    Cited by: 6
    Year: 2024
  • Generalized Lerch polynomials: application in fractional model of CAR-T cells for T-cell leukemia
    Cited by: 3
    Year: 2023
  • An efficient algorithm for solving the fractional hepatitis b treatment model using generalized Bessel polynomial
    Cited by: 7
    Year: 2023
  • A study on fractional tumor-immune interaction model related to lung cancer via generalized Laguerre polynomials
    Cited by: 14
    Year: 2023

Beatriz Veiga | Neuroscience | Best Researcher Award

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Dr. Beatriz Veiga | Neuroscience | Best Researcher Award

Dr. Beatriz Veiga, Universidade Federal de São Paulo, Brazil

Dr. Beatriz Azevedo dos Anjos Godke Veiga is a Brazilian neurologist with a focus on movement disorders. She completed her medical degree in 2001 at Universidade Estadual de Londrina, followed by a Master’s and Doctorate in Neurology/Neurosciences at Universidade Federal de São Paulo (UNIFESP). Her doctoral research, completed in 2023, examined the association between compulsive behaviors and levodopa-induced dyskinesias in Parkinson’s disease patients. Dr. Veiga is currently a neurologist at Hospital Ipiranga and a faculty member at Universidade Nove de Julho. Her research interests include impulsive behaviors, dyskinesias, and Parkinson’s disease. She has received multiple awards, including the International Congress Travel Grant Award from the Movement Disorders Society in 2019 and 2022. Her published work includes articles on depression in Parkinson’s disease and fatigue in geriatric patients. Dr. Veiga is actively involved in several research projects, particularly those exploring the relationship between early-onset Parkinson’s disease and dopamine agonists.

Publication Profile

Orcid

Awards and Titles 🏆

Dr. Beatriz Veiga has earned significant recognition in the field of movement disorders. In 2022, she was awarded the International Congress Travel Grant Award by the Movement Disorders Society 🌍, highlighting her contributions and research in this specialized area. This prestigious honor was preceded by another International Congress Travel Grant Award in 2019, further solidifying her standing within the international scientific community. Dr. Veiga’s continuous dedication to advancing the understanding of movement disorders has positioned her as a prominent figure in the field, earning accolades for her expertise and commitment to research. 🌟

 

Academic Background 🎓

Dr. Beatriz Veiga’s academic journey has been marked by excellence in the field of Neurology and Neurosciences. She completed her PhD in Neurology/Neurosciences at the Federal University of São Paulo (UNIFESP), Brazil, in 2023, with a thesis on the association between compulsive impulsive behaviors and levodopa-induced dyskinesias in Parkinson’s disease patients 🧠. Dr. Veiga also holds a Master’s degree from UNIFESP (2008), focusing on depression in Parkinson’s disease. Her medical residency in Neurology was completed at the State University of Londrina (UEL), Brazil, where she was a CNPq scholar. She holds a degree in Medicine from UEL (2001). 🎓

 

Complementary Education 📚

Dr. Beatriz Veiga has enhanced her expertise in Neurology through specialized training. In 2019, she completed a short course in Deep Brain Stimulation (DBS) at the International Academy, gaining 25 hours of focused learning on this advanced therapy for movement disorders 🧠. She also participated in an Observership program at the Movement Disorders Clinic, University of Toronto, with a focus on DBS, accumulating 160 hours of hands-on experience. Dr. Veiga is a Neurologist and Preceptor at Hospital Ipiranga, and a faculty member at the University of Nove de Julho, specializing in movement disorders. 💡

 

Professional Experience 🏥

Dr. Beatriz Veiga has extensive professional experience in Neurology and academia. Since 2008, she has been a Full Member of the Academia Brasileira de Neurologia (ABN). She is also an active member of the Movement Disorder Society (MDS) since 2017. Dr. Veiga is a Faculty Member at the University of Nove de Julho (UNINOVE) since 2012, where she teaches in the Medicine program 🩺. Additionally, she has served as a Neurologist and Preceptor at Hospital Ipiranga since 2010, training the next generation of neurologists. Her expertise has been pivotal in the field of movement disorders. 🌟

 

Research Focus

Dr. Beatriz A. Anjos G. Veiga’s research primarily focuses on neurology and movement disorders, specifically the relationship between impulsive-compulsive behaviors (ICBs) and Levodopa-induced dyskinesia (LID) in Parkinson’s disease. Her work, demonstrated in the study “Are Impulsive Compulsive Behaviors Associated with Levodopa-Induced Dyskinesia?”, explores how these behaviors contribute to the clinical presentation of Parkinson’s disease and its treatment. She investigates the neurophysiological mechanisms behind these effects, aiming to improve therapeutic strategies. Her research contributes significantly to understanding the cognitive and motor complications of Parkinson’s disease and optimizing management strategies. 🩺🔬

 

Publication Top Notes

Are Impulsive Compulsive Behaviors Associated with Levodopa-Induced Dyskinesia? A Brazilian Cross-Sectional Study

Farimah Beheshti | Neuroscience | Best Researcher Award

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Assist. Prof. Dr. Farimah Beheshti | Neuroscience | Best Researcher Award

Assist. Prof. Dr. Farimah Beheshti, Torbat Heydriyeh University of Medical Sciiences, Iran

Dr. Farimah Beheshti is an Assistant Professor in Medical Physiology at Torbat Heydariyeh University of Medical Sciences, Iran. She holds a PhD in Medical Physiology from Mashhad University of Medical Sciences (2018). Her research focuses on learning and memory impairment, cognitive disorders, and brain developmental disorders. Dr. Beheshti has authored numerous publications and presented at various national and international conferences. She is a skilled neuroscientist with expertise in rodent behavioral assessments, stereotaxic surgery, and scientific writing. Among her honors are Top Researcher awards from Mashhad and Torbat Heydariyeh Universities. 🏆📚

 

Publication Profile

Google Scholar

Academic Background

Dr. Beheshti has a strong academic foundation in Medical Physiology, with an M.Sc. and PhD from Mashhad University of Medical Sciences. Her education, spanning from biological sciences to specialized neuroscience, underscores her deep knowledge in the field. Her research focuses on mechanisms of cognitive disorders, particularly in relation to learning and memory impairments, which is central to advancing neuroscience.

Research Skills

Dr. Beheshti’s practical experience in neuroscience is extensive, including advanced techniques like in vivo extracellular single unit recording, stereotaxic surgery, and behavioral assessments. These skills demonstrate her proficiency in experimental research and her ability to handle complex laboratory procedures, which significantly contribute to her research accomplishments.

Recognition

With an H-index of 30 on Scopus, Dr. Beheshti has published extensively in reputable journals. Her research contributions are backed by a significant amount of peer-reviewed work and substantial impact in the field, as evidenced by her Web of Science Researcher ID and contributions to over 24 peer reviews in journals like Scientific Reports and Brain Research Bulletin. Her ability to influence the scientific community through publications and peer reviews is notable.

Teaching

Dr. Beheshti’s involvement in teaching neuroscience at the MSc level reflects her commitment to advancing the next generation of researchers and healthcare professionals. Her MSc thesis and PhD dissertation titles indicate a keen interest in cognitive health, particularly in the context of neurodegenerative diseases.

Awards and Honors

Dr. Beheshti’s recognition as a Top Researcher at Torbat Heydariyeh University of Medical Sciences for multiple years (2020 and 2021) speaks volumes about her sustained excellence and contributions to the field. Such recognition further solidifies her standing as an impactful researcher.

Research Focus

Assist. Prof. Dr. Farimah Beheshti’s research primarily focuses on neuropharmacology, neuroinflammation, and memory impairment. She investigates the effects of various plant-based compounds, such as Nigella sativa (black seed) and thymoquinone, on brain health, particularly in relation to oxidative stress and neuroinflammation in animal models. Her studies often explore neuroprotective agents in conditions like hypothyroidism, lipopolysaccharide-induced memory deficits, and neurodegenerative diseases. Dr. Beheshti’s work also delves into oxidative stress, cytokine regulation, and learning and memory functions, making significant contributions to understanding neuroprotection and therapeutic strategies for cognitive dysfunction. 🧠🌿💡🔬

 

Conclusion

Dr. Farimah Beheshti’s exceptional research achievements, combined with her teaching contributions, awards, and peer-reviewed work, make her an excellent candidate for the Research for Best Researcher Award. Her cutting-edge research, extensive presentation history, and consistent academic performance demonstrate her dedication to advancing the field of neuroscience, particularly in memory and cognitive health.

 

Publication Top Notes

  • The effects of thymoquinone on hippocampal cytokine level, brain oxidative stress status, and memory deficits induced by lipopolysaccharide in rats – Cited by: 107, Year: 2017 🧠💊
  • The effects of Nigella sativa extract on hypothyroidism-associated learning and memory impairment during neonatal and juvenile growth in rats – Cited by: 89, Year: 2017 🌱🧠
  • Neuropharmacological effects of Nigella sativa – Cited by: 89, Year: 2016 🌿💊
  • Inducible nitric oxide inhibitor aminoguanidine ameliorates deleterious effects of lipopolysaccharide on memory and long term potentiation in rat – Cited by: 71, Year: 2016 ⚡🧠
  • Neuronal nitric oxide synthase has a role in the detrimental effects of lipopolysaccharide on spatial memory and synaptic plasticity in rats – Cited by: 62, Year: 2016 🧠💡
  • The Effect of Allium cepa Extract on Lung Oxidant, Antioxidant, and Immunological Biomarkers in Ovalbumin-Sensitized Rats – Cited by: 61, Year: 2018 🧄🌬️
  • Beneficial effects of Urtica dioica on scopolamine-induced memory impairment in rats: protection against acetylcholinesterase activity and neuronal oxidative damage – Cited by: 60, Year: 2019 🌿🧠
  • Aminoguanidine affects systemic and lung inflammation induced by lipopolysaccharide in rats – Cited by: 59, Year: 2019 💊🌬️
  • The effects of PPAR-γ agonist pioglitazone on hippocampal cytokines, brain-derived neurotrophic factor, memory impairment, and oxidative stress status in lipopolysaccharide – Cited by: 56, Year: 2019 💊🧠
  • Thymoquinone reverses learning and memory impairments and brain tissue oxidative damage in hypothyroid juvenile rats – Cited by: 55, Year: 2018 🧠💊