Mansoor Showkat | Computational Neuroscience | Best Researcher Award

Mr. Mansoor Showkat | Computational Neuroscience | Best Researcher Award

Mr. Mansoor Showkat | SKUAT-Kashmir | India

Mansoor Showkat is a researcher in Plant Biotechnology with an M.Sc. from the University of Agricultural Sciences, Bangalore, and a B.Sc. (Hons.) in Horticulture from Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir. His research expertise spans molecular biology, computational biology, bioinformatics, and tissue culture, with particular emphasis on antifungal compound analysis, gene transformation, and plant-pathogen interactions. Mansoor has contributed to several peer-reviewed publications and book chapters, focusing on the in-silico and in-vitro evaluation of bioactive compounds such as cordycepin, molecular mechanisms of stress responses, and secondary metabolite profiling in plants. His research projects include genetic transformation studies, metabolomics-based investigations, and the use of omics tools for crop improvement. He has actively participated in numerous international workshops, conferences, and webinars related to biotechnology, bioinformatics, and genomics. Mansoor has achieved significant academic recognition, including national rankings in competitive examinations by the Indian Council of Agricultural Research. His scientific impact is reflected by a citation count of 15, an h-index of 2, and an i10-index of 0, highlighting his growing contribution to molecular and agricultural biotechnology research.

Featured Publications

  1. Showkat, M., Narayanappa, N., Umashankar, N., & Saraswathy, B. P., et al. (2024). Optimization of fermentation conditions of Cordyceps militaris and in silico analysis of antifungal property of cordycepin against plant pathogens. Journal of Basic Microbiology, 64(10), e2400409.

  2. Fatimah, N., Ashraf, S., R. U., K. N., Anju, P. B., Showkat, M., Perveen, K., Bukhari, N. A., et al. (2024). Evaluation of suitability and biodegradability of the organophosphate insecticides to mitigate insecticide pollution in onion farming. Heliyon, 10(12).

  3. Margay, K. A. A. A. R., Ashraf, S., Fatimah, N., Jabeen, S. G., & Showkat, M., et al. (2024). Plant circadian clocks: Unravelling the molecular rhythms of nature. International Journal of Plant and Soil Science, 36(8), 596–617.

  4. Margay, A. R., Ashraf, S., Fatimah, N., Jabeen, S. G., Showkat, M., R. U., K. N., Gani, A., et al. (2024). Harnessing brassinosteroids for heat resilience in wheat: A comprehensive study.

  5. Showkat, M., Nagesha, N., Ashraf, S., Nayana, K., Bashir, S., Nair, A. S., et al. (2024). Cordycepin: A molecular Trojan horse against Fusarium oxysporum f. sp. cubense—A computational perspective.

Ged Smith | Systems Neuroscience | Outstanding Educator Award

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.

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.

 

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.