Congbo Cai | Neurotechnology | Best Researcher Award

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

Prof. Dr. Congbo Cai | Xiamen University | China

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

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

Featured publications

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

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

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

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

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

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

Soheila Hosseinzadeh | Cognitive Neuroscience | Best Researcher Award

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Assoc. Prof. Dr. Soheila Hosseinzadeh | Cognitive Neuroscience | Best Researcher Award

Assist. Prof. Dr. Soheila Hosseinzadeh, Tehran University of Medical Sciences, Iran.

Dr. Soheila Hosseinzadeh is a distinguished Assistant Professor of Neuroscience at the Tehran University of Medical Sciences, with a rich academic background that spans nursing, physiology, and neuroscience. Over the years, she has made substantial contributions to neuroscience education and research, particularly in the fields of cognitive neurophysiology and addiction studies. Her expertise includes a wide range of advanced techniques such as event-related potential analysis, EEG-based neurofeedback, behavioral studies, and molecular tools like RT-PCR and ELISA. She has played a pivotal role in training students and developing neuroscience programs at multiple academic institutions, demonstrating a balanced commitment to both teaching and scientific innovation.

Academic Profile

Google Scholar

Early Academic Pursuits

Dr. Soheila Hosseinzadeh’s academic foundation is deeply rooted in an interdisciplinary understanding of human physiology and neurological sciences. Her early career began with a Bachelor of Science in Nursing in 2000, which was soon followed by a Master’s degree in Physiology in 2003. Demonstrating a keen interest in the mechanisms underlying brain function and behavior, she further advanced her expertise by earning a Ph.D. in Neuroscience in 2013. These academic milestones laid a solid groundwork for her future in teaching and cutting-edge neurophysiological research.

Professional Endeavors in Neuroscience

After completing her Ph.D., Dr. Hosseinzadeh embarked on an academic and research-oriented career that has spanned over a decade. From 2014 to April 2022, she served as a neurophysiology course instructor at Babol University of Medical Sciences, nurturing future scientists with her in-depth understanding of brain physiology. Since April 2022, she has continued her academic contributions at the Tehran University of Medical Sciences, where she teaches courses in Neuroscience and Addiction Studies. Her dual role as educator and researcher places her at the forefront of neuroscience education in Iran.

Contributions and Research Focus

Dr. Hosseinzadeh’s research is focused on the interface of cognitive neuroscience and addiction studies. Her technical proficiency includes advanced neurophysiological techniques such as event-related potential (ERP) recording and analysis, quantitative EEG (QEEG)-based neurofeedback, and behavioral assessments in animal models. She is also experienced in molecular biology tools including real-time RT-PCR and ELISA, alongside rodent stereotaxic surgeries and flow cytometry. Her work often explores neural mechanisms underlying cognitive functions, brain plasticity, and responses to addictive substances—bridging lab findings with clinical relevance.

Accolades and Recognition

Throughout her academic journey, Dr. Hosseinzadeh has earned recognition for her expertise in neurophysiological and behavioral science. Her dual roles at prestigious institutions such as Tehran University of Medical Sciences reflect her trusted authority in the field. While her accolades are more rooted in impact and mentorship than in public awards, her consistent engagement in neuroscience education and translational research is a clear indicator of peer acknowledgment and professional respect.

Impact and Influence

Dr. Hosseinzadeh’s influence extends beyond academic teaching. By integrating theoretical neuroscience with hands-on technical applications like neurofeedback and EEG-based cognitive training, she fosters a research culture that promotes both clinical innovation and scientific discovery. Her guidance has shaped students and young researchers in multiple universities, many of whom continue to advance the fields of neurophysiology and cognitive rehabilitation across the country.

Legacy in Neurotechnology and Cognitive Health

Her pioneering efforts in cognitive task design and ERP analysis have significantly contributed to Iran’s growing reputation in brain research. As one of the few experts integrating neurofeedback with behavioral science and electrophysiology, Dr. Hosseinzadeh has helped establish a platform for neurotechnological interventions in addiction and mental health studies. Her legacy lies in creating an interdisciplinary approach that merges neuroscientific inquiry with practical healthcare applications.

Future Contributions and Vision

Looking ahead, Dr. Soheila Hosseinzadeh is poised to make even greater strides in neuroscience, particularly in the domains of addiction neurobiology, cognitive rehabilitation, and neurofeedback therapy. With continuous advancements in brain-monitoring tools and behavioral modeling, she aims to lead research projects that offer deeper insights into brain-behavior relationships and provide innovative treatments for neuropsychiatric disorders. Her vision includes developing collaborative research networks that connect Iranian neuroscience to global scientific conversations.

Publication

Piperine restores streptozotocin-induced cognitive impairments: Insights into oxidative balance in cerebrospinal fluid and hippocampus
M Khalili-Fomeshi, MG Azizi, MR Esmaeili, M Gol, S Kazemi, …
2018

Plasma microparticles in Alzheimer’s disease: The role of vascular dysfunction
S Hosseinzadeh, M Noroozian, E Mortaz, K Mousavizadeh
2018

Elevated CSF and plasma microparticles in a rat model of streptozotocin-induced cognitive impairment
S Hosseinzadeh, M Zahmatkesh, MR Zarrindast, GR Hassanzadeh, …
2013

Effect of methamphetamine exposure on the plasma levels of endothelial-derived microparticles
A Nazari, M Zahmatkesh, E Mortaz, S Hosseinzadeh
2018

Hippocampal DHCR24 down regulation in a rat model of streptozotocin-induced cognitive decline
S Hosseinzadeh, M Zahmatkesh, M Heidari, GR Hassanzadeh, …
2015

Increment of CSF fractalkine-positive microvesicles preceded the spatial memory impairment in amyloid beta neurotoxicity
L Karimi-Zandi, M Zahmatkesh, G Hassanzadeh, S Hosseinzadeh
2022

Arbutin intervention ameliorates memory impairment in a rat model of lysolecethin induced demyelination: Neuroprotective and anti-inflammatory effects
S Ashrafpour, MJ Nasr-Taherabadi, A Sabouri-Rad, S Hosseinzadeh, …
2024

Conclusion

Dr. Hosseinzadeh’s career reflects an exemplary blend of academic excellence, technical expertise, and visionary research in neuroscience. Her efforts have significantly advanced the understanding of brain function, particularly in the context of addiction and cognitive health. As a leader in her field, she continues to inspire the next generation of neuroscientists while actively contributing to translational research that bridges laboratory findings with clinical solutions. With her ongoing work and future vision, Dr. Hosseinzadeh stands out as a key figure in shaping the future of neuroscience in Iran and beyond.

Ged Smith | Systems Neuroscience | Outstanding Educator Award

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Dr. Ged Smith | Systems Neuroscience | Outstanding Educator Award

Dr. Ged Smith,  UK AFT, United Kingdom.

Dr. Ged Smith is a highly esteemed Consultant Systemic/Family and Couples Psychotherapist with over 25 years of experience in clinical practice, academic teaching, and international consultation. His early academic journey began with a B.Ed from Liverpool University, followed by advanced degrees culminating in a Professional Doctorate from Birkbeck University and the Institute of Family Therapy. Throughout his career, Dr. Smith has made influential contributions through clinical supervision, research publication, and educational leadership. He is widely published in top-tier journals and is the longstanding Editor of “Context,” the UK’s principal family therapy journal. He also holds senior roles in professional organizations such as the Association for Family Therapy (AFT) and the European Family Therapy Association (EFTA). Dr. Smith’s work bridges therapeutic practice with systemic theory, making significant impact on the field both nationally and internationally.

Profile

Orcid

🎓 Early Academic Pursuits

Dr. Ged Smith began his academic journey at Liverpool University, where he earned his Bachelor of Education (B.Ed) in 1980, laying the foundation for a lifelong dedication to learning and teaching. His growing interest in social care and mental health led him to pursue a Certificate of Qualification in Social Work (CQSW) at the University of Cardiff, which he completed in 1988. Deepening his expertise in systemic practices, Dr. Smith undertook a Master of Science (MSc) in collaboration with the Institute of Family Therapy (IFT) and Birkbeck University, London in 1996. His academic excellence culminated in the attainment of a Professional Doctorate from the same institutions in 2011, solidifying his scholarly contributions to systemic and family therapy.

🧠 Professional Endeavors in Systemic Therapy

Dr. Smith’s career spans over 25 years of clinical experience in both Merseyside and London, where he has provided systemic and family therapy across diverse communities. As a UKCP Registered Systemic Psychotherapist and AFT Accredited Supervisor, he currently supervises more than 30 mental health and social care professionals. His professional influence extends across clinical settings, educational platforms, and governmental agencies, making him a sought-after consultant for Social Services and Care Agencies in the North West of England. His dedication to systemic thinking is evident in his role as a Live Supervisor on the Manchester Family Therapy Qualifying Course, where he brings practical and ethical insight to emerging therapists.

📝 Contributions and Research Focus

Dr. Smith has been an unwavering contributor to the dissemination of systemic knowledge, both as a prolific writer and respected editor. As the long-standing Editor of “Context,” the UK’s leading Family Therapy Journal, he has significantly influenced the field’s intellectual discourse. His research focus centers on transformative and relational practices in systemic therapy, engaging with contemporary themes in mental health. His published work appears in globally respected journals such as the Journal of Family Therapy, Family Process (USA), Human Systems, and the Australian and New Zealand Journal of Family Therapy. Notably, he contributed chapters to Systemic Therapy as Transformative Practice (2017), reflecting his commitment to therapeutic innovation and social justice.

📚 Academic Leadership and Teaching Excellence

Dr. Smith has played a vital role in academic mentorship and systemic education. A revered Visiting Lecturer at the Tavistock Clinic London, and universities including Manchester, Exeter, and Hull, he continues to influence systemic thinking across academic and clinical boundaries. In his role as an External Doctoral Supervisor at the University of Bedfordshire, he nurtures the next generation of systemic scholars. His expertise in integrating theory with practice has made him a preferred speaker and educator at family therapy training courses throughout the UK.

🏆 Accolades and Recognition

Dr. Smith’s long-standing contributions to systemic therapy have earned him national and international recognition. As Chair of AFT Publishing for over 20 years, he has guided the ethical and academic standards of family therapy literature in the UK. He also represents the UK at the European Family Therapy Association (EFTA) meetings, further elevating the UK’s presence on the global systemic stage. His respected status in the field is not only a result of his academic output but also his unwavering dedication to supervision, teaching, and ethical therapeutic practice.

🌍 Global Engagement and Influence

A distinguished conference speaker and workshop presenter, Dr. Smith has shared his insights on systemic and psychological approaches to mental health at international platforms. His presentations emphasize both clinical depth and sociocultural relevance, addressing topics like family systems, relational ethics, and collaborative practices in therapy. By integrating global perspectives into his work, Dr. Smith continues to expand the reach and relevance of systemic psychotherapy.

🧬 Legacy and Future Contributions

Dr. Ged Smith’s career represents a profound legacy of relational practice, scholarly excellence, and ethical leadership. As systemic therapy continues to evolve in response to modern challenges, his work sets a benchmark for future generations. With his continued supervision of doctoral candidates, editorial leadership, and international teaching, he remains at the forefront of shaping the future of family therapy. His vision is clear: to maintain systemic practice as not only a clinical method but a transformative social discourse that can empower families, communities, and practitioners alike.

Publication

  • Title: So, You’re Doing a Family Therapy Course……
    Author: Ged Smith
    Year: 2025

 

  • Title: A 1.5‐Order Therapy: Between Knowing and Not‐Knowing
    Author: Ged Smith
    Year: 2023

 

✅ Conclusion

Dr. Ged Smith exemplifies excellence in systemic and family psychotherapy through a unique blend of scholarly depth, clinical wisdom, and passionate teaching. His enduring influence on the development of family therapy—through publications, supervision, and organizational leadership—makes him a key figure in shaping contemporary mental health practices. As a researcher, educator, and clinician, he has created a meaningful legacy grounded in relational ethics and transformative therapeutic approaches. Dr. Smith’s continued contributions will undoubtedly inspire future practitioners and scholars committed to holistic, systemic care.

Abdullah Alghamdi | Emerging Areas in Neuroscience | Best Researcher Award

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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

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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

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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

Google Scholar

🎓 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

Published on by Neuroscientists

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 Zhang — 2025

 

  • Integrated brain connectivity analysis with fmri, dti, and smri powered by interpretable graph neural networks
    G Qu, Z Zhou, VD Calhoun, A Zhang, YP Wang — 2025

 

  • Altered hierarchical rank in intrinsic neural time-scales in autism spectrum disorder
    A Solomon, W Yu, J Rasero, A Zhang — 2025

 

  • 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 Zhang — 2025

 

  • 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 Wang — 2024

 

  • 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 Lee — 2024

 

  • Time‐varying dynamic Bayesian network learning for an fMRI study of emotion processing
    L Sun, A Zhang, F Liang — 2024

 

  • 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 Zhang — 2024

 

🧾 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.

 

Jiwei Nie | Emerging Areas in Neuroscience | Best Researcher Award

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Dr. Jiwei Nie | Emerging Areas in Neuroscience | Best Researcher Award

Dr. Jiwei Nie, Haier Group, China.

Jiwei Nie is an accomplished Chinese researcher specializing in Artificial Intelligence-based Pattern Recognition and Intelligent Detection, with a strong focus on AI large models. His academic journey began with a Bachelor’s in Mechanical Design and Automation and evolved into a deeply integrated path through a Master’s and Ph.D. in Control Science and Engineering at Northeastern University. Throughout his doctoral research, he has made notable contributions to the field of Visual Place Recognition (VPR) for autonomous systems, publishing in prestigious journals such as IEEE Transactions on Intelligent Transportation Systems and IEEE Robotics and Automation Letters. Jiwei’s innovations—especially in lightweight, training-free image descriptors and adaptive texture fusion—have positioned him at the forefront of applied AI in robotics and automation. He has also presented at major international conferences and holds multiple patents.

Profile

Google Scholar

🎓 Early Academic Pursuits

 Jiwei Nie displayed a deep interest in engineering and innovation from an early age. His academic journey began at Hebei University of Science and Technology, where he pursued a Bachelor’s degree in Mechanical Design, Manufacturing, and Automation. His strong academic performance earned him first-class honors, and he graduated in July 2018. Motivated to delve deeper into the fusion of machinery and intelligence, he advanced to Northeastern University, completing his Master’s degree in Mechanical and Electronic Engineering by July 2020. Driven by a vision to integrate control systems with intelligent technologies, he enrolled in a PhD program in Control Science and Engineering under a prestigious Integrated Master-PhD track, further solidifying his expertise in the intelligent automation domain.

💼 Professional Endeavors

Jiwei’s professional development has been tightly interwoven with his academic path, where he has continuously applied theoretical insights to practical problems in Artificial Intelligence and Control Systems. As a member of the Communist Party of China, he approaches his work with a strong sense of discipline and public responsibility. His fluency in English, proven by his CET-6 certification, has enabled him to actively contribute to the global research community, engaging in international collaborations and conferences. Alongside his research, Jiwei has contributed to academic circles through mentorship roles and cross-institutional projects, making a significant impact both inside and outside his university.

🤖 Contributions and Research Focus

Jiwei Nie’s research is at the forefront of Artificial Intelligence-based Pattern Recognition and Intelligent Detection, with a special emphasis on AI Large Models. His work focuses on developing lightweight, efficient algorithms for Visual Place Recognition (VPR)—a critical capability for autonomous vehicles and robotic systems. He has pioneered new methods in saliency encoding, feature mixing, and texture fusion, leading to more robust and adaptive AI systems. Through these contributions, he has addressed real-world challenges in long-term navigation and intelligent perception, pushing the boundaries of control science and machine intelligence.

🏆 Accolades and Recognition

During his PhD, Jiwei published multiple high-impact articles in leading SCI-indexed journals. His paper in the IEEE Transactions on Intelligent Transportation Systems, titled “A Training-Free, Lightweight Global Image Descriptor for Long-Term Visual Place Recognition Toward Autonomous Vehicles”, has been particularly well-received and is ranked in Q1. Additional works in IEEE Robotics and Automation Letters have been ranked in Q2, highlighting his innovations such as MixVPR++ and Efficient Saliency Encoding. Furthermore, Jiwei’s presence has been notable at world-class conferences like ICPR, ICRA, and IROS, where he presented his work to a global audience of peers and experts. He also holds several patents, including an invention patent, and continues to submit further manuscripts to top-tier venues.

🌍 Impact and Influence

Jiwei’s research has had a significant influence on the future of intelligent transportation and autonomous systems. His development of training-free VPR models has contributed to making autonomous navigation more scalable and cost-effective, especially in dynamic environments where traditional AI systems fail. His proposed methods are not only academically rigorous but are also computationally efficient, paving the way for real-world deployment. Through his innovation and academic collaborations, he has helped bridge the gap between theoretical AI models and practical engineering applications, which is vital for industries moving toward Industry 4.0 and smart mobility solutions.

🧠 Legacy and Future Contributions

Looking ahead, Jiwei Nie aspires to deepen his research in generalized large AI models, expanding the scalability and generalization abilities of pattern recognition systems across domains beyond transportation—such as smart surveillance, industrial robotics, and medical imaging. His planned future publications and continued patent filings reflect a strong ambition to lead the next generation of intelligent systems research. Jiwei is committed to fostering innovation that aligns with both academic excellence and societal needs, aiming to establish himself as a pioneering researcher and mentor in the evolving field of intelligent detection and AI integration.

🔬 Vision in AI and Control Engineering

Jiwei Nie stands as a rising expert in the convergence of Artificial Intelligence, Control Science, and Robotic Vision, a field essential for the future of smart systems and automation. His deep technical knowledge, coupled with a strategic vision, positions him to contribute not only as a researcher but also as a thought leader in AI-driven engineering. With a career rooted in innovation and societal benefit, his trajectory points toward a legacy of breakthroughs that will influence smart cities, autonomous systems, and global AI research landscapes for years to come.

Publication

  • Title: A survey of extrinsic parameters calibration techniques for autonomous devices
    Authors: J Nie, F Pan, D Xue, L Luo
    Year: 2021

 

  • Title: A training-free, lightweight global image descriptor for long-term visual place recognition toward autonomous vehicles
    Authors: J Nie, JM Feng, D Xue, F Pan, W Liu, J Hu, S Cheng
    Year: 2023

 

  • Title: Forest: A lightweight semantic image descriptor for robust visual place recognition
    Authors: P Hou, J Chen, J Nie, Y Liu, J Zhao
    Year: 2022

 

  • Title: A novel image descriptor with aggregated semantic skeleton representation for long-term visual place recognition
    Authors: J Nie, JM Feng, D Xue, F Pan, W Liu, J Hu, S Cheng
    Year: 2022

 

  • Title: Efficient saliency encoding for visual place recognition: Introducing the lightweight pooling-centric saliency-aware VPR method
    Authors: J Nie, D Xue, F Pan, Z Ning, W Liu, J Hu, S Cheng
    Year: 2024

 

  • Title: 3D semantic scene completion and occupancy prediction for autonomous driving: A survey
    Authors: G Xu, W Liu, Z Ning, Q Zhao, S Cheng, J Nie
    Year: 2023

 

  • Title: A Novel Image Descriptor with Aggregated Semantic Skeleton Representation for Long-term Visual Place Recognition
    Authors: N Jiwei, F Joe-Mei, X Dingyu, P Feng, L Wei, H Jun, C Shuai
    Year: 2022

 

  • Title: Optic Disc and Fovea Localization based on Anatomical Constraints and Heatmaps Regression
    Authors: L Luo, F Pan, D Xue, X Feng, J Nie
    Year: 2021

 

  • Title: A Novel Fractional-Order Discrete Grey Model with Initial Condition Optimization and Its Application
    Authors: Y Liu, F Pan, D Xue, J Nie
    Year: 2021

 

  • Title: EPSA-VPR: A lightweight visual place recognition method with an Efficient Patch Saliency-weighted Aggregator
    Authors: J Nie, Q Zhào, D Xue, F Pan, W Liu
    Year: 2025

 

🔚 Conclusion

With a solid foundation in engineering and control systems and an innovative mindset in artificial intelligence, Jiwei Nie is poised to become a key figure in the evolution of intelligent automation technologies. His work contributes not only to academic theory but also to practical applications that influence the development of autonomous vehicles, intelligent detection systems, and large AI model architectures. As he approaches the completion of his Ph.D. in early 2025, Jiwei is expected to continue pushing technological boundaries, inspiring future advancements in AI research and real-world intelligent systems deployment.

Jun Liu | Neuroimaging | Best Researcher Award

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Prof.Dr. Jun Liu | Neuroimaging | Best Researcher Award

Prof. Dr. Jun Liu,  Department of Radiology, Second Xiangya Hospital of Central South University, China.

Professor Jun Liu is a highly accomplished radiologist and academic leader, serving as the Chief Radiologist and Director of the Radiology Department at the Second Xiangya Hospital, Central South University. With a strong foundation in medical sciences and an early passion for radiology, he has emerged as a national figure in neuroimaging and neuroregeneration research. His professional journey is marked by impactful roles in academic mentorship, hospital administration, and national medical organizations. His research excellence is evident through his leadership in multiple prestigious committees and his contributions to scientific review and innovation. Recognized by both government and medical associations, Professor Liu is a decorated figure, celebrated for his medical service during COVID-19 and his scientific leadership in Hunan Province and beyond.

Profile

Orcid 

Scopus

 

Professor Jun Liu is a highly accomplished radiologist and academic leader, serving as the Chief Radiologist and Director of the Radiology Department at the Second Xiangya Hospital, Central South University. With a strong foundation in medical sciences and an early passion for radiology, he has emerged as a national figure in neuroimaging and neuroregeneration research. His professional journey is marked by impactful roles in academic mentorship, hospital administration, and national medical organizations. His research excellence is evident through his leadership in multiple prestigious committees and his contributions to scientific review and innovation. Recognized by both government and medical associations, Professor Liu is a decorated figure, celebrated for his medical service during COVID-19 and his scientific leadership in Hunan Province and beyond.

Profile

Orcid
Scopus

 

🎓 Early Academic Pursuits


From the very beginning of his academic journey, Professor Jun Liu demonstrated exceptional dedication to the medical sciences. He earned his M.D. and laid a solid foundation in radiology, developing a keen interest in diagnostic imaging and neurological disorders. His academic commitment and intellectual curiosity propelled him toward advanced studies and laid the groundwork for a distinguished career in radiology. As a student and early-career academic, he was recognized for his strong analytical skills and leadership potential, setting the stage for the impactful roles he would later assume in both clinical and academic spheres.

🏥 Professional Endeavors


Professor Jun Liu currently serves as the Chief Radiologist and Director of the Radiology Department at the prestigious Second Xiangya Hospital of Central South University. In this role, he oversees cutting-edge radiological practices while also guiding clinical decision-making with expertise and precision. As a Doctoral Supervisor and Professor, he mentors a new generation of radiologists, integrating academic knowledge with clinical excellence. His influence also extends into organizational leadership as the Secretary of the First Party Branch, showcasing his commitment to institutional development and medical governance.

🔬 Contributions and Research Focus


A pivotal force in radiology, Professor Liu has devoted much of his research to neuroimaging and neuroregeneration. His work as the headman of the Neuroregeneration and Neuroimaging Group under the Chinese Research Hospital Association reflects his influence in shaping national research priorities. As a peer review expert for the National Natural Science Foundation of China, he contributes to the advancement of scientific standards and research integrity. His projects often intersect clinical imaging with neuroscience, allowing for better diagnosis and understanding of neurological diseases.

🏅 Accolades and Recognition


Professor Liu’s contributions have earned him numerous national honors. Notably, he was awarded the Advanced Individual against COVID-19 by the Ministry of Science and Technology of the People’s Republic of China, acknowledging his dedication during a critical period in global health. He received the Outstanding Style Award at the 5th People’s Famous Doctor Ceremony, and has been recognized as a leading talent in the Science and Technology Innovation Program of Hunan Province. His role as leader of 225 subjects in the province showcases his broad expertise and leadership in medical research and education.

🌐 Impact and Influence


Nationally, Professor Liu plays a vital role in shaping radiological standards and neurology practices. As a member of the Neurology Group under the Chinese Society of Radiology and the Chinese Medical Association, his insights influence nationwide healthcare policies and training programs. In Hunan, he is the Director of the Diagnostic Radiology Quality Control Center and President of the Radiologists Branch of the Hunan Medical Doctor Association, where he continues to elevate diagnostic standards and ensure quality in radiological services.

🚀 Innovation and Leadership


Professor Liu stands as a prime example of a “Double Leaders” Party Branch Secretary, a title awarded by the Ministry of Education, symbolizing excellence in both administrative and academic leadership. His involvement in technology-driven projects, particularly those that integrate AI and neuroimaging, highlights his forward-thinking approach to medical diagnostics. He champions the evolution of radiology into a more dynamic and precision-focused discipline, blending traditional expertise with technological innovations.

📘 Legacy and Future Contributions


As Professor Liu continues to mentor doctoral candidates and lead national research groups, his legacy is already visible in the improved radiological practices across China. His work in neuroregeneration and imaging not only enhances clinical outcomes but also pushes the boundaries of what medical imaging can achieve. In the years to come, his continued dedication to education, research, and innovation will undoubtedly shape the future of radiology and contribute to better neurological healthcare nationwide and beyond.

Publication

  • Title: Insulinoma detection on low-dose pancreatic CT perfusion: comparing with conventional contrast-enhanced CT and MRI
    Authors: S. Luo, X. Mei, Y. Shang, … W. Yang, J. Liu
    Year: 2025

 

  • Title: Functions and application of circRNAs in vascular aging and aging-related vascular diseases
    Authors: S. He, B. Huang, F. Xu, … X. Lin, J. Liu
    Year: 2025

 

  • Title: Persistent alterations in gray matter in COVID-19 patients experiencing sleep disturbances: a 3-month longitudinal study
    Authors: K. Zhou, G. Duan, Y. Liu, … J. Yang, D. Deng
    Year: 2025

 

  • Title: Multimodal radiopathological integration for prognosis and prediction of adjuvant chemotherapy benefit in resectable lung adenocarcinoma: A multicentre study
    Authors: H. Lin, J. Hua, Z. Gong, … C. Lu, Z. Liu
    Year: 2025

 

  • Title: Prognostic and predictive values of a multimodal nomogram incorporating tumor and peritumor morphology with immune status in resectable lung adenocarcinoma
    Authors: H. Lin, J. Hua, Y. Wang, … J. Liu, Z. Liu
    Year: 2025

 

  • Title: White matter microstructural alterations are associated with cognitive decline in benzodiazepine use disorders: a multi-shell diffusion magnetic resonance imaging study
    Authors: M. Yi, T. Wang, X. Li, … J. Liu, H. Zhou
    Year: 2025

 

  • Title: Unveiling causal relationships between addiction phenotypes and inflammatory cytokines: insights from bidirectional mendelian randomization and bibliometric analysis
    Authors: S. Cao, L. Yang, X. Wang, … S. Tang, J. Liu
    Year: 2025

 

  • Title: Microstructure changes of the brain preceded glymphatic function changes in young obesity with and without food addiction
    Authors: M. Yi, Z. Yule, W. Song, … J. Liu, H. Zhou
    Year: 2025

 

  • Title: Distinct insula subdivisions of resting-state functional connectivity in individuals with opioid and methamphetamine use disorders
    Authors: W. Yang, X. Wen, Z. Du, … K. Yuan, J. Liu
    Year: 2025

 

  • Title: Unraveling the Diffusion MRI-Based Glymphatic System Alterations in Children with Rolandic Epilepsy
    Authors: Y. Yin, M. Ma, F. Wang, … J. Liu, H. Liu
    Year: 2025

 

✅ Conclusion


Professor Jun Liu’s career embodies the intersection of clinical expertise, scientific innovation, and compassionate leadership. Through decades of dedication, he has transformed radiological practice and training in China, especially in neurological diagnostics. As a scholar, mentor, and administrator, his legacy continues to inspire the next generation of medical professionals. With a focus on advancing neuroimaging techniques and quality standards, Professor Liu stands as a beacon of excellence in modern radiology, with his future contributions set to further shape the landscape of medical diagnostics and research.

Yuchun Wang | Neurotechnology | Best Researcher Award

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Ms. Yuchun Wang | Neurotechnology | Best Researcher Award

Ms. Yuchun Wang, Fudan University, China.

Yu Chun Wang is an emerging scholar from the Department of Rehabilitation Medicine at Huashan Hospital, Fudan University, with a strong academic foundation and a clear research direction. Their work revolves around neurological rehabilitation and the rapidly evolving field of brain-computer interfaces (BCI). With a multidisciplinary approach, Yu Chun integrates neuroscience, rehabilitation techniques, and cutting-edge technology to address the needs of individuals recovering from neurological impairments. Though still early in their academic journey, Yu Chun is already contributing to high-quality research, fostering collaborations, and preparing to lead innovative projects that bridge clinical rehabilitation and intelligent systems.

Profile

Orcid

🎓 Early Academic Pursuits

Yu Chun Wang began their academic journey at the esteemed Fudan University, where they enrolled in the Department of Rehabilitation Medicine at Huashan Hospital. With a strong interest in human recovery and assistive technology, Yu Chun immersed themselves in foundational studies that emphasized neurophysiology, biomedical sciences, and rehabilitation techniques. From the outset, they demonstrated an analytical mind and a passion for exploring innovative solutions to neurological challenges, setting the stage for a research-focused career.

🧠 Professional Endeavors in Neurological Rehabilitation

Currently positioned as a student-researcher, Yu Chun Wang has dedicated their academic life to advancing the field of neurological rehabilitation. At Huashan Hospital, their role involves deep engagement with real-world clinical settings, working alongside experts in neurology and rehabilitation. Their work primarily focuses on enhancing patient recovery through the integration of modern therapeutic interventions and monitoring neuroplasticity in patients recovering from brain injuries.

🧬 Contributions and Research Focus

Yu Chun’s research journey centers around two compelling fields: neurological rehabilitation and brain-computer interface (BCI) systems. With a growing expertise in neuro-rehabilitation technologies, they aim to bridge the gap between cognitive recovery and artificial intelligence. Their innovative explorations delve into how BCI can transform therapeutic outcomes, empowering individuals with neuro-disorders through intelligent, responsive systems that adapt to brain activity and stimulate recovery.

📚 Academic Footprints and Publications

While Yu Chun is in the early stages of their scholarly journey, their commitment to publishing in high-impact journals indexed by SCI and Scopus is evident. Their academic work, though emerging, has begun making its mark in interdisciplinary forums focused on neural engineering and rehabilitation sciences. These publications are paving the way for greater academic discourse in merging digital systems with patient care strategies.

🤝 Collaborations and Industry Interaction

Yu Chun Wang actively seeks collaborative networks within the medical and engineering sectors. Their current projects involve interdisciplinary collaboration, including clinical therapists, software developers, and neuroscientists. Although industry consultancy and patents are still developing areas, Yu Chun’s research has laid the groundwork for future partnerships aimed at developing therapeutic technologies for real-time rehabilitation assessment.

🏅 Accolades and Recognition

As a young researcher, Yu Chun’s contributions have been recognized within their academic institution and by their peers in scientific circles. Participation in research competitions and early recognition for innovative proposals in brain-computer interface models speak volumes about their potential. The Department of Rehabilitation Medicine supports and acknowledges Yu Chun’s promising role in the field’s evolution.

🔭 Legacy and Future Contributions

With a vision to transform rehabilitation through intelligent systems, Yu Chun Wang aspires to lead groundbreaking research that improves the quality of life for patients with neurological impairments. They aim to contribute to the development of non-invasive BCI tools that integrate with clinical workflows, offering efficient and patient-centric recovery models. Their journey is just beginning, yet the foundation laid speaks of a future filled with impactful innovations and global collaborations.

Publication

  • Title: Advances in Brain Computer Interface for Amyotrophic Lateral Sclerosis Communication
    Author(s): Yuchun Wang
    Year: 2024 (assumed)

 

  • Title: Soft Magnetoelasticity for Mechanical Energy Harvesting
    Author(s): Yuchun Wang, Minyan Ge, Shumao Xu
    Year: 2024 (assumed)

 

  • Title: Water-responsive Contraction for Shape-adaptive Bioelectronics
    Author(s): Yuchun Wang, Minyan Ge, Shumao Xu
    Year: 2024 (assumed)

 

✅ Conclusion

Yu Chun Wang represents the next generation of medical researchers who combine scientific curiosity with technological vision. With a focus on patient-centered innovation and a drive to improve neurological rehabilitation outcomes through brain-computer interface research, their future in academic and applied science is bright. As they continue to grow in experience and scholarly achievement, Yu Chun is poised to make lasting contributions to the global healthcare and rehabilitation community.