Abdullah Alghamdi | Emerging Areas in Neuroscience | Best Researcher Award

Mr. Abdullah Alghamdi | Emerging Areas in Neuroscience | Best Researcher Award

Mr. Abdullah Alghamdi, University of Birmingham (UK) and Taibah University (Saudi Arabia),  United Kingdom.

Eng. Abdullah A. Zohaid (SMIEEE, SMIET) is an accomplished electrical engineer and academic with a specialization in Smart Power Systems, focusing on electric vehicles, AI-integrated transportation systems, and sustainable smart city infrastructure. With a solid educational foundation—earning distinctions at every academic level—he has seamlessly merged academic excellence with real-world engineering experience. From his early career at Saudi Aramco to his dual lecturing roles at Taibah University and the University of Birmingham, Abdullah has built a reputation as a forward-thinking researcher, educator, and strategist. His work bridges technical innovation with societal needs, aiming to optimize power grids and energy systems for a sustainable future.

Profile

Google Scholar

🎓 Early Academic Pursuits

From the historic city of Medina, Saudi Arabia, Eng. Abdullah A. Zohaid embarked on his academic journey in Electrical Engineering at Taibah University, where his talent and determination earned him distinction in his final project. His academic passion soon carried him to the United Kingdom, where he pursued an MSc in Electrical Power Systems at the University of Birmingham, graduating with First-Class Honors and distinction. Abdullah’s unwavering commitment to academic excellence continued as he embarked on a Ph.D. in Smart Power Systems at the same institution. Excelling in all areas, he has distinguished himself through both research prowess and scholastic achievement.

⚡ Professional Endeavors

Eng. Alghamdi has established himself as a dynamic professional straddling the worlds of academia and industry. His journey began with Saudi Aramco’s Dodsal Company, contributing to the vital 56″ Gas Pipeline project as an assistant electrical engineer. He transitioned into academia with his role as a Lecturer at Taibah University in Yanbu and later joined the University of Birmingham as a faculty member. Balancing dual academic roles in Saudi Arabia and the UK, Abdullah has developed a unique global perspective, blending practical engineering insight with cutting-edge educational delivery. His presence as an educator underscores his belief in empowering future engineers with real-world readiness.

🔬 Contributions and Research Focus

A scholar deeply embedded in the future of sustainable power, Eng. Alghamdi’s research focuses on Smart Power Systems, electric vehicles, smart charging infrastructures, and the integration of AI in intelligent transportation systems. Through his ongoing Ph.D. research, he explores how emerging technologies can enhance smart grid resilience and contribute to the development of smart cities. He utilizes advanced simulation and optimization tools such as MATLAB/SIMULINK, Python, and Gurobi, combined with machine learning techniques (ANN/CNN), to propose innovative solutions that address pressing energy challenges. His passion for sustainability is evident in his contributions to the global energy discourse, especially in urban mobility and decarbonization.

🏆 Accolades and Recognition

Eng. Zohaid’s career is adorned with recognition and academic milestones. His consistent distinction in every academic phase, including honors during both his MSc and Ph.D. studies, reflects a sustained trajectory of excellence. As a senior member of prestigious engineering bodies like IEEE and IET, and a certified Professional Engineer by the Saudi Council of Engineers, his credentials are a testament to his standing in the professional community. Furthermore, his publications in Q1 journals and contributions to leading international conferences validate the depth of his research and the quality of his scholarly communication.

🌍 Impact and Influence

With affiliations across IEEE working groups and university research circles, Eng. Alghamdi’s influence spans global academic and professional spheres. As a presenter and contributor at numerous high-level conferences — from the IEEE Power & Energy Society to Net Zero Futures and Saudi Innovation events — he has played a key role in shaping conversations on smart energy. His multidisciplinary expertise allows him to drive collaborations across AI, optimization, and power systems, impacting both policy and practice. His ability to simplify complex engineering concepts and communicate them effectively has enabled him to become a trusted voice among peers and students alike.

💡 Innovation and Strategic Vision

Abdullah’s strength lies in visionary thinking and strategic problem-solving. He doesn’t merely research problems—he crafts systems and strategies that reflect future-forward thinking. His approach to sustainable urban infrastructure blends technological acumen with strategic planning, leadership, and innovation. As an educator and researcher, he fosters environments that promote critical thinking and team-based innovation, cultivating the next generation of engineers equipped to face tomorrow’s challenges. His work on smart charging and intelligent transportation embodies the essence of transformative impact through design thinking and systems innovation.

🚀 Legacy and Future Contributions

Looking ahead, Eng. Abdullah A. Zohaid is poised to leave a lasting legacy in the realm of smart power systems and urban sustainability. His dual role as a lecturer and researcher gives him a powerful platform to shape both academic knowledge and real-world applications. With his continued focus on electrification, smart mobility, and AI-driven infrastructure, he is on track to influence policy, inspire innovation, and expand the boundaries of what is possible in modern power systems. His legacy will be defined not only by the technologies he helps build but also by the students and professionals he inspires along the way.

Publication

  • Innovative Prepositioning and Dispatching Schemes of Electric Vehicles for Smart Distribution Network Resiliency and Restoration
    AAM Alghamdi, D. Jayaweera, 2022

 

  • Resilience of Modern Power Distribution Networks with Active Coordination of EVs and Smart Restoration
    AAM Alghamdi, D. Jayaweera, 2023

 

  • Modelling Frameworks Applied in Smart Distribution Network Resiliency and Restoration
    AAM Alghamdi, D. Jayaweera, 2022

 

  • Resilience-Oriented Restoration in Modern Power Distribution Networks with Smart Electric Vehicles Coordination Framework
    A. Alghamdi, D. Jayaweera, 2023

 

  • Risk and Resilience Based Residential Electric Vehicle Integration Framework for Restoration of Modern Power Distribution Networks
    A. Alghamdi, D. Jayaweera, 2025

 

  • Electric Boats and Electric Vehicles Data-Driven Approach for Enhanced Resilience in Power Distribution Networks
    AAM Alghamdi, D. Jayaweera, 2025

 

✅ Conclusion

Eng. Alghamdi stands at the forefront of energy transformation, using research, innovation, and teaching as tools to drive meaningful change. His contributions reflect a blend of technical mastery and visionary leadership, enabling progress in smart mobility, clean energy, and intelligent infrastructure. With a growing portfolio of Q1 publications, prestigious memberships, and impactful conference roles, he continues to influence the field of electrical engineering on a global scale. As he advances in his career, his legacy will be marked by both technological advancements and the future minds he mentors—solidifying his role as a transformative figure in the evolution of smart power systems.

VIKRAM SINGH KARDAM | Neuroinformatics | Best Researcher Award

Mr. VIKRAM SINGH KARDAM | Neuroinformatics | Best Researcher Award

Mr. VIKRAM SINGH KARDAM, DTU DELHI, India.

Vikram Singh Kardam is a dedicated researcher and academician specializing in signal processing, currently pursuing his Ph.D. at Delhi Technological University (DTU). With a strong educational foundation, including an M.Tech in Signal Processing and Digital Design, and a B.Tech in Electronics and Communication Engineering, he has consistently demonstrated academic excellence. Vikram has diverse professional experience, having worked both in industry and academia, including roles as a Project Engineer and Assistant Professor. His innovative M.Tech thesis on real-time iris recognition highlights his ability to apply advanced concepts to practical challenges in biometric security. Proficient in multiple programming languages and known for his problem-solving attitude, he blends technical skill with teaching acumen, influencing students and peers alike. His GATE rank and contributions to student development further underscore his commitment to excellence in engineering and education.

Profile

Scopus

 

🎓 Early Academic Pursuits

Vikram Singh Kardam’s academic journey began with a solid foundation in science and technology. He completed his 10th and 12th education from Government Inter College, Agra, achieving commendable marks that laid the groundwork for his future in engineering. His higher education commenced at the University Institute of Engineering and Technology, CSJM University, Kanpur, where he earned his Bachelor of Technology in Electronics and Communication Engineering in 2007 with a respectable score of 73.2%. Driven by a passion for advanced studies, he pursued a Master of Technology in Signal Processing and Digital Design from Delhi Technological University (DTU), securing a CGPA of 8.06 in 2017. His academic path reflects not only consistent effort but also a dedication to the field of signal processing.

🧑‍🏫 Professional Endeavors

Vikram embarked on his professional career with diverse roles that bridged academia and industry. He served as a Project Engineer at ITI Limited, Delhi, and as a Lab Engineer at Dayalbagh Engineering College, Agra, gaining hands-on experience in real-world engineering environments. His passion for teaching led him to academia, where he worked as an Assistant Professor in reputed institutions such as Galgotias College of Engineering and Technology, Greater Noida, and HMR Institute of Technology and Management, Delhi. With around three years of cumulative teaching experience, he has imparted theoretical knowledge and practical insights in Electronics and Communication Engineering, contributing to the academic development of numerous students.

🔬 Contributions and Research Focus

Currently pursuing his Ph.D. in Signal Processing at Delhi Technological University, Vikram Singh Kardam’s research delves into the intricacies of digital signal processing with real-world applications. His M.Tech thesis, titled “Real Time Iris Recognition”, showcases his innovation in biometric security systems. By integrating iris recognition with eye-blinking detection using a basic webcam, he proposed a novel, low-cost, and more secure method for identity verification. The system’s robustness and its resistance to hacking highlight his ability to merge theoretical concepts with practical utility. His fluency in programming languages such as MATLAB, C, C++, and Python3 supports his technical versatility in algorithm development and simulation.

🏅 Accolades and Recognition

A noteworthy milestone in Vikram’s academic journey is securing an All India Rank of 5334 in the GATE 2021 examination in Electronics and Communication Engineering. This national-level achievement is a testament to his strong grasp of core concepts and problem-solving acumen. Additionally, his academic performances during B.Tech and M.Tech reflect sustained excellence. His thesis project, recognized for its practical application and innovative approach, further enhances his academic reputation.

📚 Impact and Influence

In his role as an Assistant Professor, Vikram Singh Kardam has significantly influenced his students’ academic and professional growth. His commitment to regularly conducting lectures, his focus on ensuring student understanding, and his hands-on approach to lab sessions highlight his dedication to holistic teaching. Beyond knowledge delivery, his empathetic and analytical mindset enables him to mentor students, offer academic guidance, and solve problems effectively. His ability to integrate teaching with research creates an inspiring learning environment.

🌐 Legacy and Future Contributions

Looking forward, Vikram aspires to contribute to both academia and industry through innovative research in signal processing, embedded systems, and biometric technology. His current Ph.D. pursuits are expected to yield impactful contributions to the scientific community, particularly in the areas of real-time data analysis and secure identification systems. With a forward-thinking vision, he aims to blend educational excellence with technological advancement, fostering a new generation of engineers equipped with both critical thinking and creative problem-solving skills.

🧠 Vision and Intellect

At the core of Vikram Singh Kardam’s career is a mindset defined by curiosity, dedication, and the pursuit of knowledge. A quick learner and an effective communicator, he embodies the spirit of modern engineering – adaptive, analytical, and collaborative. His ability to learn and implement complex systems, along with his respect for students and colleagues, reflects not just technical competence but also emotional intelligence. As a lifelong learner and educator, he is poised to make enduring contributions in signal processing and beyond.

Publication

  • Title: BSPKTM-SIFE-WST: Bispectrum based channel selection using set-based-integer-coded fuzzy granular evolutionary algorithm and wavelet scattering transform for motor imagery EEG classification

  • Authors: V.S. Kardam, S. Taran, A. Pandey

  • Year: 2025

 

 

Conclusion

Vikram Singh Kardam stands out as a promising scholar and educator in the field of signal processing. His journey reflects a balance of theoretical rigor, practical implementation, and a passion for continuous learning. With a future-oriented mindset, he is poised to make meaningful contributions to biometric systems, digital design, and the broader engineering community. As he advances through his doctoral research and professional engagements, Vikram’s legacy is one of innovation, dedication, and impactful mentorship in the evolving landscape of technology and education.

Alex Armstrong | Systems Neuroscience | Young Scientist Award

Mr. Alex Armstrong | Systems Neuroscience | Young Scientist Award

Mr. Alex Armstrong, University of Illinois, Urbana-Champaign, United States.

Alex Armstrong is an emerging leader in the field of systems neuroscience with a rich academic background and a global research footprint. Starting with a strong foundation in pharmacology from the University of Manchester and early research experience in China, he has built an interdisciplinary career that bridges experimental, computational, and translational neuroscience. His Ph.D. work at the University of Illinois Urbana-Champaign, under the guidance of Prof. Yurii Vlasov, focuses on the neural mechanisms of perceptual decision-making using innovative tools like tactile virtual reality and localized lesioning techniques. He has also played integral roles in teaching, mentoring, and collaborative NIH-funded research involving cutting-edge neural probes. His contributions span from fundamental neuroscience to neuroengineering, with multiple international presentations and a growing reputation in both academic and applied research communities.

Profile

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🎓 Early Academic Pursuits

Alex Armstrong’s journey into the world of neuroscience began with a strong academic foundation in Pharmacology at the University of Manchester, where he earned a BSc (Honors) degree in 2017. During his undergraduate studies, he delved into the neural effects of psychoactive substances, leading a research project examining the influence of various drugs on receptive fields in the rat lateral geniculate nucleus. His academic curiosity was not confined to the lab; Alex actively mentored disadvantaged youth in science and mathematics through the CityWise charity, demonstrating an early commitment to both education and societal impact. His academic appetite took a global turn when he received a competitive scholarship to Nanjing Medical University in China. There, he shadowed urologists and contributed to prostate cancer research by processing tumor samples and supporting manuscript preparation under the mentorship of Dr. Jian Lin. This early immersion into translational research laid the groundwork for his future endeavors in systems neuroscience.

🧠 Research Focus and Innovation

Currently pursuing his Ph.D. at the University of Illinois Urbana-Champaign, Alex Armstrong is at the forefront of neuroscience research under the mentorship of Professor Yurii Vlasov, a member of the National Academy of Engineering. His research seeks to unravel the neural underpinnings of perceptual decision-making using advanced technologies. Alex has pioneered the development of a novel tactile virtual reality system tailored for mice, enabling precise behavioral and neural investigations in ecologically valid scenarios. His contributions also include designing a localized lesioning technique to dissect the causal roles of specific cortical regions with unmatched spatial and temporal resolution. This work reflects his deep integration of behavior, electrophysiology, histology, and computational modeling — a rare confluence of skills that pushes the boundaries of systems neuroscience.

🔬 Professional Endeavors and Laboratory Leadership

Alex’s career includes impactful positions across globally renowned institutions. Prior to his doctoral studies, he served as a Research Technician at University College London, working in auditory neuroscience labs with PIs Jennifer Linden and Nicholas Lesica. There, he independently managed experiments related to auditory perception and hearing aid technology, leading both behavioral training and neural recordings. At UIUC, his laboratory involvement extends beyond individual research: he performs surgeries, manages mouse colonies, trains new graduate and undergraduate researchers, and leads collaborative NIH-funded projects investigating simultaneous electrical and chemical neural activity during seizures. Alex is a dependable pillar in the lab, bridging experiment and innovation through hands-on mentorship and project leadership.

🏆 Accolades and Recognition

Alex’s academic and scientific contributions have been recognized at multiple levels. He has presented his work through nine conference talks and poster presentations at premier forums including Barrels, the Society for Neuroscience, and AREADNE between 2021 and 2024. His visibility within the academic community extends to teaching, where he was entrusted as a Teaching Assistant for the competitive Neural Interface Engineering course (ECE421) in 2024 and 2025, guiding over 50 students through workshops, lessons, and exam reviews. His role on the UIUC neuroscience seminar committee in 2022 further demonstrated his leadership in promoting interdisciplinary dialogue, as he invited top neuroscientists from across the world to contribute to the university’s vibrant intellectual atmosphere.

🧪 Scientific Contributions and Methodological Advancements

One of Alex Armstrong’s most significant contributions lies in his ability to blend experimental neuroscience with computational modeling. His proficiency spans advanced analytical methods including Generalized Linear Models (GLM), Drift Diffusion Models (DDM), Dimensionality Reduction, and DyNetCP, positioning him at the intersection of theory and practice. His work not only provides high-resolution insights into brain function but also informs the design of next-generation neural interface devices. His leadership in testing novel neural probes capable of simultaneously recording both electrical and chemical signals underlines his commitment to tool development in neuroscience — a field critical to brain–machine interface technologies and precision neuromodulation.

🌍 Impact and Influence

Alex Armstrong’s research has both immediate and long-term scientific value. By enhancing our understanding of the cortical mechanisms underlying decision-making, his work informs the broader fields of psychology, cognitive science, and artificial intelligence. His contributions to probe testing during seizure dynamics have implications for epilepsy research, potentially opening doors for better diagnostics and treatment strategies. Furthermore, his global academic experience — spanning the U.K., U.S., and China — contributes to his inclusive scientific perspective and ability to work across cultural and institutional boundaries. He has not only advanced science but also nurtured future researchers through consistent mentoring and training roles.

🚀 Legacy and Future Contributions

Looking ahead, Alex Armstrong is poised to become a leading figure in systems neuroscience, particularly in decoding the neural basis of cognition and behavior. With a solid foundation in experimentation, programming, and tool development, he is uniquely equipped to tackle the grand challenges of brain science in the 21st century. His efforts are steadily laying a legacy of open, interdisciplinary research, bridging the biological and engineering aspects of neuroscience. Whether through innovative VR paradigms for animal behavior, high-density probe validation, or collaborative research across continents, Alex continues to pave the way for future breakthroughs in understanding the human brain.

Publication

  • Title: Targeting AXL overcomes resistance to docetaxel therapy in advanced prostate cancer
    Authors: JZ Lin, ZJ Wang, W De, M Zheng, WZ Xu, HF Wu, A Armstrong, JG Zhu
    Year: 2017

 

  • Title: Compression and amplification algorithms in hearing aids impair the selectivity of neural responses to speech
    Authors: AG Armstrong, CC Lam, S Sabesan, NA Lesica
    Year: 2022

 

  • Title: The hearing aid dilemma: amplification, compression, and distortion of the neural code
    Authors: A Armstrong, CC Lam, S Sabesan, NA Lesica
    Year: 2020

 

  • Title: Nonlinear sensitivity to acoustic context is a stable feature of neuronal responses to complex sounds in auditory cortex of awake mice
    Authors: M Akritas, AG Armstrong, JM Lebert, AF Meyer, M Sahani, JF Linden
    Year: 2024

 

  • Title: Contextual modulation is a stable feature of the neural code in auditory cortex of awake mice
    Authors: M Akritas, AG Armstrong, JM Lebert, AF Meyer, M Sahani, JF Linden
    Year: 2023

 

  • Title: Neuropeptides in the Extracellular Space of the Mouse Cortex Measured by Nanodialysis Probe Coupled with LC-MS
    Authors: K Li, W Shi, Y Tan, Y Ding, A Armstrong, Y Vlasov, J Sweedler
    Year: 2025

 

  • Title: Neural correlates of perceptual decision making in primary somatosensory cortex
    Authors: A Armstrong, Y Vlasov
    Year: 2025

 

  • Title: Perceptual decision-making during whisker-guided navigation causally depends on a single cortical barrel column
    Authors: AG Armstrong, Y Vlasov
    Year: 2025

 

 

Conclusion

Alex Armstrong exemplifies the next generation of neuroscientists—technically skilled, globally experienced, and intellectually versatile. His ability to merge behavioral neuroscience with advanced computational tools and engineering innovations positions him at the forefront of brain research. As he continues to contribute to our understanding of neural dynamics and brain–machine interfaces, Alex is set to leave a lasting impact on neuroscience and its applications in medicine and technology. His trajectory reflects not just scientific excellence, but also a commitment to mentorship, interdisciplinary collaboration, and innovation-driven discovery.

Aiying Zhang | Computational Neuroscience | Best Researcher Award

Assist. Prof. Dr. Aiying Zhang | Computational Neuroscience | Best Researcher Award

Assist. Prof. Dr. Aiying Zhang, University of Virginia, United States.

Dr. Aiying Zhang is a rising scholar in the field of mental health data science, currently serving as an Assistant Professor at the University of Virginia and a Faculty Member at the UVA Brain Institute. Her academic foundation spans statistics, biomedical engineering, and clinical biostatistics, acquired from esteemed institutions including USTC, Tulane University, and Columbia University. Her research focuses on developing advanced computational and statistical tools—such as graphical models and multimodal fusion—to decode complex brain data from imaging and genetics. She applies these innovations to better understand and predict psychiatric conditions such as schizophrenia and Alzheimer’s disease. Her work is distinguished by its interdisciplinary nature, translational relevance, and potential to reshape clinical approaches to mental health.

Profile

Google Scholar

 

🎓 Early Academic Pursuits

Aiying Zhang’s journey into the realm of data science and mental health research began with a strong foundation in quantitative sciences. She earned her Bachelor of Science degree in Statistics from the prestigious School for the Gifted Young at the University of Science and Technology of China (USTC) in 2014. Driven by a passion for biomedical innovation and its intersection with human health, she pursued a Ph.D. in Biomedical Engineering from Tulane University, which she completed in 2021. Her graduate years were marked by deep inquiry into statistical modeling and neuroimaging, laying the groundwork for her later interdisciplinary research. She further honed her expertise through postdoctoral training in Clinical Biostatistics and Psychiatry at Columbia University Irving Medical Center, where she blended statistical rigor with clinical insight.

💼 Professional Endeavors

Dr. Zhang is currently an Assistant Professor of Data Science at the University of Virginia, where she has been on the tenure-track faculty since August 2023. She also holds a concurrent position as a Faculty Member at the UVA Brain Institute, underscoring her active role in advancing brain research across institutional boundaries. Prior to her academic appointment at UVA, she served as a Research Scientist II at the New York State Psychiatric Institute, contributing to high-impact psychiatric research. Her professional journey also includes research assistantships at Tulane University and the University of Florida, roles in which she cultivated strong collaborative and translational research skills.

🧠 Contributions and Research Focus

Dr. Zhang’s research lies at the intersection of data science, neuroscience, and mental health. She specializes in developing advanced statistical and computational methodologies to investigate the biological underpinnings of psychiatric and neurodevelopmental disorders. Her work prominently features the use of graphical models—both directed and undirected—and machine learning techniques to analyze complex datasets, such as MRI, DTI, fMRI, MEG, and various genomic modalities including SNP and DNA methylation. Her research has contributed to a deeper understanding of conditions like schizophrenia, Alzheimer’s disease, obsessive-compulsive disorder, and anxiety disorders, through the lens of multimodal data fusion and integrative neurogenetics.

🧪 Innovation in Mental Health Data Science

A distinctive hallmark of Dr. Zhang’s scholarship is her innovative application of multimodal fusion techniques to disentangle the complexities of typical and atypical brain development. Her work leverages high-dimensional neuroimaging and genetic data to draw meaningful inferences about mental health trajectories. She is particularly focused on building interpretable models that bridge the gap between data and clinical insight, thereby enabling earlier and more precise diagnostics. By combining machine learning with biomedical expertise, her contributions pave the way for next-generation tools in psychiatry and neuroscience.

🏅 Accolades and Recognition

Throughout her academic and professional trajectory, Dr. Zhang has earned widespread respect for her analytical acumen and interdisciplinary collaborations. Her postdoctoral role at Columbia, a hub for clinical psychiatry and biostatistics, positioned her among leaders in the field and enriched her research portfolio with translational applications. Her selection as faculty at a leading institution like UVA further reflects recognition of her scholarly excellence and her potential to drive future innovations in mental health data science.

🌍 Impact and Influence

Dr. Zhang’s work has significant implications for both the scientific community and clinical practice. Her methods empower researchers and clinicians alike to draw meaningful patterns from multimodal datasets, thereby advancing precision psychiatry. Moreover, her collaborative efforts across biomedical engineering, statistics, and clinical disciplines have fostered integrative frameworks that extend beyond academic settings into real-world applications. Her contributions are helping to shape a more data-driven and personalized future in mental health care.

🔮 Legacy and Future Contributions

As she continues her academic journey, Dr. Zhang aims to expand her research frontiers by exploring dynamic brain-behavior associations and improving the interpretability of AI models in clinical contexts. With a commitment to mentorship and open science, she is building a legacy rooted in intellectual rigor, innovation, and societal relevance. Her future contributions are expected to not only deepen our understanding of mental health disorders but also inspire a new generation of data scientists dedicated to neuroscience and human well-being.

Publication

  • Leverage multimodal neuro-imaging and genetics to identify causal relationship between structural and functional connectivity and ADHD with Mendelian randomization
    C Ji, S Lee, S Sequeira, J Jin, A Zhang2025

 

  • Integrated brain connectivity analysis with fmri, dti, and smri powered by interpretable graph neural networks
    G Qu, Z Zhou, VD Calhoun, A Zhang, YP Wang2025

 

  • Altered hierarchical rank in intrinsic neural time-scales in autism spectrum disorder
    A Solomon, W Yu, J Rasero, A Zhang2025

 

  • A Privacy-Preserving Domain Adversarial Federated learning for multi-site brain functional connectivity analysis
    Y Zhang, L Wang, KJ Su, A Zhang, H Zhu, X Liu, H Shen, VD Calhoun, …2025

 

  • A Novel GNN Framework Integrating Neuroimaging and Behavioral Information to Understand Adolescent Psychiatric Disorders
    W Yu, G Qu, Y Kim, L Xu, A Zhang2025

 

  • A Bayesian incorporated linear non-Gaussian acyclic model for multiple directed graph estimation to study brain emotion circuit development in adolescence
    A Zhang, G Zhang, B Cai, TW Wilson, JM Stephen, VD Calhoun, YP Wang2024

 

  • Exploring hierarchical gradients of intrinsic neural timescales in mild cognitive impairment and Alzheimer’s disease
    A Zhang, K Wengler, X Zhu, G Horga, TE Goldberg, S Lee2024

 

  • Time‐varying dynamic Bayesian network learning for an fMRI study of emotion processing
    L Sun, A Zhang, F Liang2024

 

  • Altered hierarchical gradients of intrinsic neural timescales in mild cognitive impairment and Alzheimer’s disease
    A Zhang, K Wengler, X Zhu, G Horga, TE Goldberg, S Lee, …2024

 

  • Associations Between Brain Connectivity and Psychiatric Symptoms in Children: Insights into Adolescent Mental Health
    D Mutu, K Ji, X He, S Lee, S Sequeira, A Zhang2024

 

🧾 Conclusion

Dr. Zhang’s journey exemplifies a seamless integration of data science and neuroscience to address pressing mental health challenges. Her innovative use of multimodal data and machine learning not only contributes to scientific advancement but also enhances real-world clinical decision-making. As she continues to pioneer research at the intersection of computation and psychiatry, her influence is poised to grow, shaping the future of precision mental health care and empowering both academia and clinical practice through data-driven insights.

 

Fabiano Papaiz | Computational Neuroscience | Best Researcher Award

Prof. Fabiano Papaiz | Computational Neuroscience | Best Researcher Award

Prof. Fabiano Papaiz, IFRN, Brazil.

Fabiano Papaiz is a dedicated academic and professional in the field of education and technology, affiliated with the Federal Institute of Education, Science, and Technology of Rio Grande do Norte (IFRN) in Brazil. With a strong foundation in the intersection of education and technology, his work focuses on integrating modern technological innovations into educational practices. Through his research and professional endeavors, Papaiz has contributed significantly to advancing educational methods and improving learning environments. His accolades reflect his influence both within Brazil and internationally. His research aims to enhance educational outcomes by leveraging digital tools and resources, benefiting the academic community and shaping the future of learning.

Profile

Orcid

 

📚 Early Academic Pursuits

Fabiano Papaiz began his academic journey in Brazil, where he cultivated a strong foundation in the field of education and technology. His early academic pursuits were centered around exploring the intersections of education and technological advancements. With a keen interest in applied sciences, he honed his knowledge and skills through his academic experiences, leading him to a path of lifelong learning and research. Papaiz’s commitment to education in Brazil is evident, and his passion for technology-driven academic progress is one of the key pillars of his professional career.

💻 Professional Endeavors

Currently affiliated with the Federal Institute of Education, Science, and Technology of Rio Grande do Norte (IFRN), Fabiano Papaiz plays a pivotal role in shaping the future of education and technology. At IFRN, he is part of the DATINF (Department of Information Technology), where he works on integrating modern technological solutions with academic practices. His professional journey reflects his dedication to advancing educational methodologies and bridging the gap between technology and learning. As part of the institution, Papaiz has contributed to a wide range of educational initiatives that aim to enhance the learning experience in Brazil, especially in the field of information technology.

🔬 Contributions and Research Focus

Papaiz’s research interests lie in the dynamic field of information technology and its application to educational contexts. His research focuses on leveraging technological innovations to improve educational outcomes, develop new learning tools, and address contemporary challenges in the digital age. Fabiano’s academic contributions have been significant, with a strong emphasis on the role of technology in shaping modern education. His work not only influences the academic community but also helps to create a more tech-savvy generation of students who can navigate and thrive in a rapidly evolving digital world.

🏆 Accolades and Recognition

Throughout his career, Fabiano Papaiz has received numerous accolades for his contributions to education and technology. His work at IFRN has been recognized not only within Brazil but also internationally, as he continues to share his expertise with global academic and technological communities. His dedication to advancing the integration of information technology into education has earned him admiration from peers, students, and academic institutions alike. His reputation as a thought leader in the intersection of education and technology is well-established, marking him as an influential figure in his field.

🌍 Impact and Influence

Fabiano Papaiz’s work has made a profound impact on both the academic and technological landscapes of Brazil. His influence extends beyond the classroom, as his research and professional endeavors have shaped the way information technology is applied in education. Through his leadership and innovation, he has fostered the growth of more effective learning environments, enhanced by the use of digital tools and resources. His contributions have not only benefited his institution but also contributed to the wider educational community by offering solutions that address modern teaching and learning needs.

Publication

  • Title: Predicting ALS progression using Autoregressive deep learning models
    Authors: Fabiano Papaiz, Mario Emílio Teixeira Dourado, Jr, Ricardo Alexsandro de Medeiros Valentim, Felipe Ricardo dos Santos Fernandes, João Paulo Queiroz dos Santos, Antonio Higor Freire de Morais, Fernanda Brito Correia, Joel Perdiz Arrais
    Year: 2025

 

  • Title: RR3D: Uma solução para renderização remota de imagens médicas tridimensionais
    Author: Fabiano Papaiz
    Year: 2013

 

Conclusion

Fabiano Papaiz’s career exemplifies the transformative power of technology in education. His contributions, ranging from research to institutional leadership, have made a lasting impact on the integration of technology in educational settings. As he continues to innovate and lead, Papaiz’s legacy will undoubtedly shape the future of education, paving the way for more inclusive and effective learning environments. His ongoing work ensures that technology will remain a key driver in educational progress, with the potential to benefit generations of students and educators worldwide.

 

Francisco Mena | Computational Neuroscience | Best Researcher Award

Mr. Francisco Mena | Computational Neuroscience | Best Researcher Award

Mr. Francisco Mena, University of Kaiserslautern-Landau, Germany.

Francisco Mena is a dynamic researcher in the field of machine learning, currently pursuing a PhD at the University of Kaiserslautern-Landau (RPTU), Germany. His academic roots trace back to Federico Santa María Technical University (UTFSM) in Chile, where he developed a strong foundation in computer engineering and data science. With a specialization in unsupervised learning, deep learning, and multi-view data fusion, his work focuses on building robust and scalable models that minimize human intervention and adapt to incomplete or noisy datasets—particularly in the context of Earth observation and crowdsourced data. He has worked across international research institutes like DFKI in Germany and Inria in France, contributing to global advancements in AI and data science. His teaching and mentoring roles, combined with his innovative research, mark him as a rising contributor to the future of intelligent systems.

Profile

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🎓 Early Academic Pursuits

Francisco Mena’s academic journey began with a strong foundation in computer engineering at Federico Santa María Technical University (UTFSM) in Chile. Demonstrating exceptional academic performance, he ranked in the top 10% of his class, securing the 4th position among 66 students. He pursued an integrated path that led him to obtain a Bachelor of Science, a Licenciado, and later the Ingeniería Civil en Informática degree. Driven by curiosity and a passion for machine learning, he transitioned seamlessly into postgraduate studies, earning a Magíster en Ciencias de la Ingeniería Informática at UTFSM. His master’s thesis, focused on mixture models in crowdsourcing scenarios, set the stage for his growing interest in unsupervised learning and probabilistic models.

💼 Professional Endeavors

Alongside his studies, Francisco actively engaged in diverse professional roles that enriched his technical and academic expertise. He served as a research assistant at the Chilean Virtual Observatory (CHIVO), contributing to astroinformatics projects by processing and organizing astronomical datasets from ALMA and ESO observatories. His early professional stint as a front-end and back-end developer provided him with hands-on industry experience. In academia, he held several teaching roles, progressing from laboratory assistant to lecturer in key courses such as computational statistics, artificial neural networks, and machine learning. Currently, as a Student Research Assistant at the German Research Centre for Artificial Intelligence (DFKI), he contributes to Earth observation projects, enhancing models for crop yield prediction using multi-view data.

🔬 Contributions and Research Focus

Francisco’s research is anchored in machine learning with a special emphasis on unsupervised learning, deep neural architectures, multi-view learning, and data fusion. His doctoral work at University of Kaiserslautern-Landau (RPTU) focuses on handling missing views in Earth observation data, an increasingly important issue in remote sensing. He explores innovative methods that challenge traditional domain-specific models by advocating for approaches that minimize human intervention and labeling. His core research areas include autoencoders, deep clustering, dimensionality reduction, and latent variable modeling, with applications extending to vegetation monitoring, neural information retrieval, and crowdsourcing.

🌍 Global Collaborations

Francisco’s commitment to impactful research is evident in his international collaborations. In addition to his work in Germany, he undertook a research visit to Inria in Montpellier, France, where he explored cutting-edge topics such as multi-modal co-learning, multi-task learning, and mutual distillation. These collaborations allow him to expand the practical relevance of his research across geographical and disciplinary boundaries, contributing to global discussions in artificial intelligence and data science.

🧠 Impact and Influence

Through his extensive academic involvement, Francisco has shaped the understanding of machine learning models that are both scalable and adaptable to real-world challenges. His contributions in crowdsourcing, particularly the use of latent group variable models for large-scale annotations, reflect his commitment to developing resource-efficient models. His influence extends into education, where he has mentored students and shaped curriculum delivery in machine learning-related subjects. By leveraging tools like PyTorch, QGIS, and Slurm, he ensures his work remains at the cutting edge of technological advancement.

🏆 Recognition and Growth

Francisco’s academic excellence is evident from his consistent achievements and recognition. His GPA of 94% during his master’s program stands as a testament to his dedication and intellect. Being ranked #4 in his undergraduate program highlights his sustained academic brilliance. His teaching roles at UTFSM and lecturing at RPTU further underscore the trust institutions place in his knowledge and teaching abilities.

🚀 Legacy and Future Contributions

With a clear research vision and a strong international presence, Francisco Mena is poised to leave a lasting impact in the field of artificial intelligence, particularly in unsupervised learning and Earth observation. His focus on reducing dependency on human intervention, increasing model generalizability, and handling incomplete or noisy data reflects a future-forward approach. As his doctoral journey progresses, he is expected to continue influencing how machine learning models are conceptualized, designed, and deployed in real-world applications—especially those that require scalable, domain-agnostic solutions.

Publication

 

  • Harnessing the power of CNNs for unevenly-sampled light-curves using Markov Transition Field – M Bugueño, G Molina, F Mena, P Olivares, M Araya – 2021

 

  • Common practices and taxonomy in deep multiview fusion for remote sensing applications – F Mena, D Arenas, M Nuske, A Dengel – 2024

 

  • A binary variational autoencoder for hashing – F Mena, R Ñanculef – 2019

 

  • Refining exoplanet detection using supervised learning and feature engineering – M Bugueño, F Mena, M Araya – 2018

 

  • Predicting crop yield with machine learning: An extensive analysis of input modalities and models on a field and sub-field level – D Pathak, M Miranda, F Mena, C Sanchez, P Helber, B Bischke, … – 2023

 

  • Adaptive fusion of multi-modal remote sensing data for optimal sub-field crop yield prediction – F Mena, D Pathak, H Najjar, C Sanchez, P Helber, B Bischke, P Habelitz, … – 2025

 

  • A comparative assessment of multi-view fusion learning for crop classification – F Mena, D Arenas, M Nuske, A Dengel – 2023

 

  • Self-supervised Bernoulli autoencoders for semi-supervised hashing – R Ñanculef, F Mena, A Macaluso, S Lodi, C Sartori – 2021

 

  • Impact assessment of missing data in model predictions for Earth observation applications – F Mena, D Arenas, M Charfuelan, M Nuske, A Dengel – 2024

 

  • Increasing the robustness of model predictions to missing sensors in Earth observation – F Mena, D Arenas, A Dengel – 2024

 

🧩 Conclusion

Driven by curiosity and innovation, Francisco Mena is reshaping the landscape of machine learning through his pursuit of generalizable, efficient, and human-independent models. His research not only addresses technical limitations but also responds to the growing need for AI systems that are adaptable across domains and disciplines. With a solid academic background, global collaborations, and a clear research vision, he is set to make lasting contributions to unsupervised learning and its applications in critical areas like Earth observation and neural information retrieval. As he continues to build on his expertise, his work promises to influence both the academic world and the practical deployment of intelligent systems in complex, real-world scenarios.

Koagne Longpa Tamo Silas | Neuroinformatics | Pioneer Researcher Award

Mr. Koagne Longpa Tamo Silas | Neuroinformatics | Pioneer Researcher Award

Mr.  Koagne Longpa Tamo Silas, University of Dschang, Cameroon.

Koagne Longpa Tamo Silas is a dedicated researcher in the field of medical physics, specializing in automation, artificial intelligence, and electronic system design. His academic journey from Bamenda State University to Dschang State University reflects his continuous pursuit of knowledge and innovation. His contributions to circuit simulation, embedded systems, and artificial neural networks have established him as a promising figure in medical physics.

Profile

Google Scholar

🎓 Early Academic Pursuits

Born on July 12, 1998, in Mbouda, Cameroon, Koagne Longpa Tamo Silas displayed a keen interest in science and technology from a young age. His passion for physics and engineering led him to pursue higher education at Bamenda State University, where he embarked on an academic journey in Electrical and Power Engineering. His undergraduate studies, from November 2015 to August 2018, laid the foundation for his expertise in electrical systems, automation, and circuit design. Eager to expand his knowledge, he continued his postgraduate studies in the same field at Bamenda State University from September 2018 to July 2020, honing his skills in power engineering and applied electronics.

🚀 Professional Endeavors

Determined to deepen his expertise, Koagne Longpa Tamo Silas transitioned into the field of physics, enrolling as a Ph.D. student at Dschang State University in December 2022. His academic pursuits in the Department of Physics align with his interests in medical physics, where he integrates automation, applied computer science, and electronics to innovate in the field. As a dedicated researcher, he continues to engage with the Faculty of Science at Dschang State University, contributing to the academic and scientific community with his research in medical physics and embedded systems.

🤖 Contributions and Research Focus

Koagne Longpa Tamo Silas has dedicated his research efforts to the intersection of medical physics, automation, and artificial intelligence. His work encompasses Analog Artificial Neural Networks, Embedded Systems, Circuit Simulation, Digital and Analog Electronics, and Microcontroller Programming. His proficiency in tools like Spice Simulation, Cadence Virtuoso, and Electronic Design Automation allows him to design and optimize medical devices and automated systems. His research aims to enhance diagnostic and therapeutic tools in medical physics by leveraging artificial intelligence and embedded systems.

🏆 Accolades and Recognition

Throughout his academic and research career, Koagne Longpa Tamo Silas has garnered recognition for his contributions to medical physics and electronics. His innovative approach to circuit simulation and signal processing has positioned him as a promising researcher in his field. His dedication to advancing medical technologies has earned him the respect of his peers and mentors, as he continues to contribute valuable insights to the scientific community.

🌐 Impact and Influence

Through his academic journey and research, Koagne Longpa Tamo Silas has influenced the way automation and artificial intelligence are integrated into medical physics. His work in digital electronics and microcontroller programming is paving the way for innovative solutions in the medical field. His contributions extend beyond research, as he actively engages with students and researchers, fostering a culture of knowledge-sharing and scientific exploration.

 

Publication

  • A High-Resolution Non-Volatile Floating Gate Transistor Memory Cell for On-Chip Learning in Analog Artificial Neural Networks
    Authors: KLT Silas, DTA Bernard, FT Bernard, L Jean-Pierre, GW Ejuh
    Year: 2025

 

  • Breast Cancer Diagnosis with Machine Learning Using Feed-Forward Multilayer Perceptron Analog Artificial Neural Network
    Authors: B Djimeli-Tsajio Alain, KLT Silas, LT Jean-Pierre, N Thierry, GW Ejuh
    Year: 2024

 

  • Design and Implementation of a Digital Breath Alcohol Detection System with SMS Alert and Vehicle Tracking on Google Map
    Author: KLT Silas
    Year: 2020

 

  • Design and Realization of an Electronic Attendance System Based on RFID with an Automatic Door Unit
    Author: MK Jules
    Year: 2018

 

🎯 Conclusion

With a vision to transform medical physics through automation and AI-driven technologies, Koagne Longpa Tamo Silas is on a path to making significant contributions to healthcare innovation. His passion, dedication, and expertise ensure that his research will continue to shape the future of medical technology, leaving a lasting impact on both academia and practical applications in the field.

 

Peishun Ye | Image Classification | Best Researcher Award

Prof. Peishun Ye | Image Classification | Best Researcher Award

Prof. Peishun Ye, Yulin University, China.

Peishun Ye is a distinguished researcher and educator specializing in artificial intelligence and big data technology. His contributions to AI-driven image classification, particularly through the MobileTransNeXt model, have significantly enhanced remote sensing applications. With a strong academic background and extensive professional experience, he has led multiple research projects, published influential papers, and played a crucial role in advancing AI methodologies. His work continues to inspire and drive progress in the field.

Profile

Scopus

🎓 Early Academic Pursuits

Peishun Ye’s journey into the world of technology began with a strong academic foundation. He graduated from Shaanxi Normal University in 2005 with a degree in Computer Science and Technology. This formative education laid the groundwork for his expertise in computing, programming, and technological advancements. His passion for innovation and problem-solving led him to pursue further studies, culminating in a Master’s degree in Computer Technology Engineering from Northwestern Polytechnical University in 2016. These academic pursuits provided him with the knowledge and skills necessary to make groundbreaking contributions in the field of artificial intelligence and big data technology.

🏛️ Professional Endeavors

Upon completing his undergraduate degree, Peishun Ye embarked on a professional career at Yulin University. His dedication to research and teaching has made a significant impact on the institution. Over the years, he has been actively involved in scientific exploration and has contributed extensively to the field of computer science. With a focus on artificial intelligence and big data, he has been instrumental in developing new methodologies and refining existing technologies. His work has not only shaped the academic curriculum but also provided industry-driven solutions that address real-world challenges.

💡 Contributions and Research Focus

Peishun Ye’s research is centered on big data technology and artificial intelligence, with a particular emphasis on deep learning models. His latest work introduces MobileTransNeXt, an innovative hybrid deep learning architecture that integrates CNN, Transformer, and BiLSTM to enhance image classification performance in remote sensing applications. MobileTransNeXt has demonstrated exceptional results, achieving 96.90% test accuracy on the UC-MERCED dataset and 95.18% on NWPU-RESISC45. To further optimize these results, he developed the MobileTransNeXt-based DFE model, which extracts features from pretrained MobileTransNeXt and boosts classification accuracy to 98.81% and 95.29% on the respective datasets. His groundbreaking work has set new benchmarks in AI-driven image classification.

🎯 Accolades and Recognition

Throughout his career, Peishun Ye has been recognized for his outstanding contributions to the field of computer science. He has successfully led and completed one key research and development project for the Shaanxi Provincial Department of Science and Technology, as well as two industry-university research projects under the Yulin Science and Technology Bureau—one completed and one still ongoing. His research findings have been widely acknowledged in the academic community, with over ten published papers, including three indexed in EI. These accomplishments underscore his commitment to advancing knowledge and fostering technological innovation.

🌐 Impact and Influence

Peishun Ye’s research has significantly influenced the fields of artificial intelligence and big data analytics. His work on MobileTransNeXt and its advanced DFE-based version has contributed to improving the efficiency and accuracy of remote sensing image classification. By integrating cutting-edge deep learning techniques, his models have opened new avenues for AI applications in environmental monitoring, urban planning, and geospatial analysis. His contributions continue to inspire fellow researchers, students, and industry professionals, driving progress in AI-driven solutions.

 

Publication

  • Title: “A Secure Routing Protocol for Wireless Sensor Networks”

  • Author: Ye, Peishun

  • Year: 2010

🎨 Conclusion

Peishun Ye’s journey in academia and research is a testament to his dedication and vision in artificial intelligence and big data. His innovations have set new standards in AI-driven image classification, and his commitment to knowledge dissemination ensures a lasting impact. As he continues to explore new frontiers in AI, his work will undoubtedly contribute to the evolution of technology, leaving a legacy of excellence and inspiration for future generations.


Kiran Solingapuram Sai | Neuroimaging | Best Researcher Award

Dr. Kiran Solingapuram Sai | Neuroimaging | Best Researcher Award

Dr. Kiran Solingapuram Sai, Wake Forest School of Medicine, United States.

Dr. Kiran K. Solingapuram Sai, PhD, is an Associate Professor with tenure in the Department of Radiology at Wake Forest School of Medicine. He holds a Ph.D. in Organic Chemistry from Northern Illinois University and has extensive research experience in radiopharmaceutical chemistry. His postdoctoral training at Washington University’s Mallinckrodt Institute of Radiology focused on radiotracer development.

Profile

Orcid

 

✨ Early Academic Pursuits

Dr. Kiran K. Solingapuram Sai embarked on his academic journey with a strong foundation in chemistry, earning a Bachelor of Science degree in Chemistry, Biochemistry, and Microbiology from Osmania University, Hyderabad, India, in 2001. His passion for organic chemistry led him to pursue a Master of Science in the same field at Osmania University, where he honed his expertise in chemical synthesis and molecular interactions. Determined to explore the depths of organic chemistry, he pursued his Ph.D. at Northern Illinois University, DeKalb, IL, under the mentorship of Dr. Douglas A. Klumpp. During this period, his research focused on synthetic methodologies and organic reaction mechanisms, paving the way for his future contributions to medicinal and radiopharmaceutical chemistry.

🌐 Professional Endeavors

Dr. Sai’s professional journey commenced with a prestigious postdoctoral research associate position at the Mallinckrodt Institute of Radiology at Washington University in St. Louis, MO, where he worked under the guidance of Dr. Robert H. Mach. During his tenure from 2010 to 2013, he delved into the complexities of radiochemistry, developing novel radiotracers and exploring their applications in medical imaging. This experience laid the groundwork for his career in radiopharmaceutical sciences. In 2014, he joined Wake Forest School of Medicine as a Research Instructor and Chief Radiochemist, marking the beginning of his significant contributions to translational imaging and radiopharmaceutical production.

⚛️ Contributions and Research Focus

At Wake Forest School of Medicine, Dr. Sai played a pivotal role in the Department of Radiology and the Clinical Translational Science Institute (CTSI). He specialized in managing clinical and research-based radiopharmaceutical production at the Wake Forest PET Research Center. As a cyclotron manager and coordinator, he oversaw the synthesis and quality control of radiotracers essential for PET imaging. His expertise extended to the development and implementation of cGMP-approved protocols for C-11 and F-18 radiopharmaceutical production, ensuring the highest standards of safety and efficacy. His research focuses on advancing PET imaging techniques, exploring new radiotracers for diagnostic and therapeutic applications, and improving imaging biomarker development.

🏆 Accolades and Recognition

Dr. Sai’s dedication to radiochemistry and molecular imaging has earned him recognition in the scientific community. His work has been instrumental in developing radiopharmaceuticals for neurological and oncological imaging, contributing significantly to early disease detection and targeted therapy. His contributions have been acknowledged through numerous research grants, collaborative projects, and publications in high-impact scientific journals. His commitment to excellence and innovation has positioned him as a leading figure in the field of radiopharmaceutical sciences.

🔬 Impact and Influence

Beyond his research and technical expertise, Dr. Sai has mentored budding scientists and researchers in the field of radiochemistry and imaging sciences. His guidance has helped shape the next generation of radiopharmaceutical experts, fostering a culture of innovation and scientific curiosity. His role in translational imaging programs has bridged the gap between basic research and clinical applications, directly impacting patient care by improving diagnostic imaging techniques.

💡 Legacy and Future Contributions

Dr. Sai’s work continues to inspire advancements in molecular imaging and radiopharmaceutical development. As an Associate Professor with tenure at Wake Forest School of Medicine, he remains dedicated to pushing the boundaries of radiochemistry, developing cutting-edge imaging agents, and enhancing the precision of diagnostic medicine. His legacy in the field is defined by his unwavering commitment to scientific discovery, translational research, and the continuous pursuit of excellence in radiopharmaceutical sciences.Dr. Kiran K. Solingapuram Sai’s contributions to the field of radiopharmaceutical chemistry stand as a testament to his dedication, innovation, and impact on medical imaging and healthcare. His journey from a passionate chemistry student to a distinguished professor and researcher highlights the transformative power of science in shaping the future of medicine.

 

Publication

  1. Radiation-induced brain injury in non-human primates: A dual tracer PET study with [11C]MPC-6827 and [11C]PiB

    • Authors: Naresh Damuka, George W. Schaaf, Mack Miller, Caleb Bradley, Bhuvanachandra Bhoopal, Ivan Krizan, Krishna K. Gollapelli, Christopher T. Whitlow, J. Mark Cline, Kiran K. Solingapuram Sai
    • Year: 2025

 

  1. The β-Secretase 1 Enzyme as a Novel Therapeutic Target for Prostate Cancer

    • Authors: Hilal A. Rather, Sameh Almousa, Ashish Kumar, Mitu Sharma, Isabel Pennington, Susy Kim, Yixin Su, Yangen He, Abdollah R. Ghara, Kiran Kumar Solingapuram Sai et al.
    • Year: 2023

 

  1. Development and Optimization of 11C-Labeled Radiotracers: A Review of the Modern Quality Control Design Process

    • Authors: Paul Josef Myburgh, Kiran Kumar Solingapuram Sai
    • Year: 2023

 

  1. Binding Parameters of [11C]MPC-6827, a Microtubule-Imaging PET Radiopharmaceutical in Rodents

    • Authors: Avinash H. Bansode, Bhuvanachandra Bhoopal, Krishna Kumar Gollapelli, Naresh Damuka, Ivan Krizan, Mack Miller, Suzanne Craft, Akiva Mintz, Kiran Kumar Solingapuram Sai
    • Year: 2023

 

  1. PET Imaging of [11C]MPC-6827, a Microtubule-Based Radiotracer in Non-Human Primate Brains

    • Authors: Naresh Damuka, Paul W. Czoty, Ashley T. Davis, Michael Nader, Susan H. Nader, Suzanne Craft, Shannon L. Macauley, Lindsey K. Galbo Thomma, Phillip M. Epperly, Christopher T. Whitlow et al.
    • Year: 2020

 

  1. One-pot synthesis of novel tert-butyl-4-substituted phenyl-1H-1,2,3-triazolo piperazine/piperidine carboxylates, potential GPR119 agonists

    • Authors: Nagaraju Bashetti, J.V. Shanmukha Kumar, Naresh Varma Seelam, B. Prasanna, Akiva Mintz, Naresh Damuka, Sriram Devanathan, Kiran Kumar Solingapuram Sai
    • Year: 2019

 

Conclusion

Dr. Kiran K. Solingapuram Sai has established himself as a leading expert in radiopharmaceutical sciences, contributing significantly to translational imaging research. His work in PET radiopharmaceutical production and quality assurance underscores his role in advancing medical imaging techniques. His academic and research contributions make him a valuable asset in the field of radiology and molecular imaging.

Hiroshi Yamada | Neuroscience | Excellence in Innovation

Mr. Hiroshi Yamada | Neuroscience | Excellence in Innovation

Mr. Hiroshi Yamada, Medical/Tsukuba, Japan.

H. Yamada, born in Kasugai, Aichi, Japan, has built an impressive academic and professional career in neuroscience. After earning his Bachelor of Science from Tohoku University, he pursued a Master’s degree at Osaka University and later obtained his Ph.D. from Kyoto Prefectural University of Medicine. His research journey took him from postdoctoral studies in Japan to New York University, where he collaborated with renowned neuroscientist Paul W. Glimcher. Returning to Japan, he served as Section Chief at the National Center of Neurology and Psychiatry before joining the University of Tsukuba, where he progressed from Assistant Professor to Associate Professor. His research focuses on neural mechanisms, contributing significantly to neuroscience through both theoretical and practical advancements.

Profile

Google Scholar

🎓 Early Academic Pursuits

H. Yamada’s academic journey reflects a deep-rooted passion for science and medicine. Born on September 9, 1977, in Kasugai, Aichi, Japan, he pursued a Bachelor of Science degree from the Faculty of Science at Tohoku University, graduating in 2000. Driven by a desire to deepen his understanding of human biology, he earned his Master of Arts from the Faculty of Medicine at Osaka University in 2002. His academic pursuits culminated in a Ph.D. from the Graduate School of Kyoto Prefectural University of Medicine in 2005, where he laid the groundwork for his future research in neuroscience.

🧠 Professional Endeavors in Neuroscience

H. Yamada’s professional career began with postdoctoral research at Kyoto Prefectural University of Medicine under the mentorship of Minoru Kimura, focusing on advanced neurological studies. His pursuit of global scientific exposure led him to New York University in 2008, where he worked with renowned neuroscientist Paul W. Glimcher. Upon returning to Japan, Yamada took on a leadership role as Section Chief at the National Center of Neurology and Psychiatry, National Institute of Neuroscience, from 2011. This role was pivotal in shaping his expertise in neurological research, ultimately leading to his tenure as Assistant Professor at the University of Tsukuba in 2013, and later as Associate Professor in 2022.

🔬 Contributions and Research Focus

Throughout his career, H. Yamada has been dedicated to unraveling the complexities of the human brain. His research primarily focuses on neuroscience, exploring neural mechanisms underlying behavior and cognition. At the University of Tsukuba, he has contributed significantly to the understanding of brain functions, merging experimental data with theoretical models to advance the field. His collaborations with international experts have enriched his approach, making his work both diverse and impactful.

🏅 Accolades and Recognition

Yamada’s contributions to neuroscience have earned him recognition within the academic community. His leadership roles and tenured position at the University of Tsukuba reflect his outstanding research and teaching capabilities. His work at prestigious institutions like New York University and the National Center of Neurology and Psychiatry has further solidified his reputation as a respected neuroscientist, contributing to both national and international scientific advancements.

🌍 Impact and Influence

H. Yamada’s research has had a profound impact on the field of neuroscience, influencing both academic circles and clinical practices. His studies on neural behavior have provided insights that bridge the gap between theoretical neuroscience and practical applications, aiding in the development of treatments for neurological disorders. As an educator, he has mentored numerous students, fostering the next generation of neuroscientists.

🚀 Legacy and Future Contributions

Looking ahead, H. Yamada is committed to expanding the horizons of neuroscience through innovative research and global collaborations. His legacy is not only reflected in his published work but also in the students and researchers he has inspired. As he continues his journey at the University of Tsukuba, his focus remains on advancing scientific knowledge and contributing to the global understanding of the human brain.

💡 A Lifelong Dedication to Science

H. Yamada’s life is a testament to the power of curiosity and dedication. From his early academic days in Tohoku to his current role as an Associate Professor, he has consistently pursued excellence in neuroscience. His journey underscores the importance of interdisciplinary research, mentorship, and the relentless quest for knowledge, leaving a lasting mark on the scientific community.

Publication

  • Title: Tonically active neurons in the primate caudate nucleus and putamen differentially encode instructed motivational outcomes of action
    Authors: H. Yamada, N. Matsumoto, M. Kimura
    Year: 2004

 

  • Title: Roles of the lateral habenula and anterior cingulate cortex in negative outcome monitoring and behavioral adjustment in nonhuman primates
    Authors: T. Kawai, H. Yamada, N. Sato, M. Takada, M. Matsumoto
    Year: 2015

 

  • Title: Thirst-dependent risk preferences in monkeys identify a primitive form of wealth
    Authors: H. Yamada, A. Tymula, K. Louie, P.W. Glimcher
    Year: 2013

 

  • Title: Juxtacellular labeling of tonically active neurons and phasically active neurons in the rat striatum
    Authors: H. Inokawa, H. Yamada, N. Matsumoto, M. Muranishi, M. Kimura
    Year: 2010

 

  • Title: Free choice shapes normalized value signals in medial orbitofrontal cortex
    Authors: H. Yamada, K. Louie, A. Tymula, P.W. Glimcher
    Year: 2018

 

  • Title: Tonically active neurons in the striatum encode motivational contexts of action
    Authors: M. Kimura, H. Yamada, N. Matsumoto
    Year: 2003

 

  • Title: Tonic firing mode of midbrain dopamine neurons continuously tracks reward values changing moment-by-moment
    Authors: Y. Wang, O. Toyoshima, J. Kunimatsu, H. Yamada, M. Matsumoto
    Year: 2021

 

  • Title: Roles of centromedian parafascicular nuclei of thalamus and cholinergic interneurons in the dorsal striatum in associative learning of environmental events
    Authors: K. Yamanaka, Y. Hori, T. Minamimoto, H. Yamada, N. Matsumoto, et al.
    Year: 2018

 

  • Title: Inactivation of the putamen selectively impairs reward history-based action selection
    Authors: M. Muranishi, H. Inokawa, H. Yamada, Y. Ueda, N. Matsumoto, M. Nakagawa, et al.
    Year: 2011

 

  • Title: Goal-directed, serial and synchronous activation of neurons in the primate striatum
    Authors: M. Kimura, N. Matsumoto, K. Okahashi, Y. Ueda, T. Satoh, T. Minamimoto, et al.
    Year: 2003

 

Conclusion

H. Yamada’s career is a reflection of his dedication to advancing the understanding of the human brain. His academic achievements, leadership roles, and research contributions have left a lasting impact on the neuroscience community. As he continues his work at the University of Tsukuba, his legacy is defined not only by his scientific discoveries but also by his mentorship and influence on future generations of researchers. His journey stands as an inspiring example of the pursuit of knowledge and the transformative power of science.