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

 

šŸŽ“ Early Academic Pursuits

Vikram Singh Kardamā€™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.

šŸ§‘ā€šŸ« 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.

šŸ”¬ Contributions and Research Focus

Currently pursuing his Ph.D. in Signal Processing at Delhi Technological University, Vikram Singh Kardamā€™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 systemā€™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.

šŸ… Accolades and Recognition

A noteworthy milestone in Vikramā€™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.

šŸ“š Impact and Influence

In his role as an Assistant Professor, Vikram Singh Kardam has significantly influenced his studentsā€™ 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.

šŸŒ 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.

šŸ§  Vision and Intellect

At the core of Vikram Singh Kardamā€™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 ā€“ 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

 

 

āœ… 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, Vikramā€™s legacy is one of innovation, dedication, and impactful mentorship in the evolving landscape of technology and education.

Aiying Zhang | Computational Neuroscience | Best Researcher Award

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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 toolsā€”such as graphical models and multimodal fusionā€”to decode complex brain data from imaging and genetics. She applies these innovations to better understand and predict psychiatric conditions such as schizophrenia and Alzheimerā€™s disease. Her work is distinguished by its interdisciplinary nature, translational relevance, and potential to reshape clinical approaches to mental health.

Profile

Google Scholar

 

šŸŽ“ Early Academic Pursuits

Aiying Zhangā€™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.

šŸ’¼ 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.

šŸ§  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 modelsā€”both directed and undirectedā€”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, Alzheimerā€™s disease, obsessive-compulsive disorder, and anxiety disorders, through the lens of multimodal data fusion and integrative neurogenetics.

šŸ§Ŗ 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.

šŸ… 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.

šŸŒ Impact and Influence

Dr. Zhangā€™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.

šŸ”® 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 ā€” 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 ā€” 2025

 

  • Altered hierarchical rank in intrinsic neural time-scales in autism spectrum disorder
    A Solomon, W Yu, J Rasero, A Zhang ā€” 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, … ā€” 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 ā€” 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 ā€” 2024

 

  • Exploring hierarchical gradients of intrinsic neural timescales in mild cognitive impairment and Alzheimerā€™s disease
    A Zhang, K Wengler, X Zhu, G Horga, TE Goldberg, S Lee ā€” 2024

 

  • Timeā€varying dynamic Bayesian network learning for an fMRI study of emotion processing
    L Sun, A Zhang, F Liang ā€” 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, … ā€” 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 ā€” 2024

 

šŸ§¾ Conclusion

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

 

Fabiano Papaiz | Computational Neuroscience | Best Researcher Award

Published on by Neuroscientists

Prof. Fabiano Papaiz | Computational Neuroscience | Best Researcher Award

Prof. Fabiano Papaiz, IFRN, Brazil.

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

Profile

Orcid

 

šŸ“š Early Academic Pursuits

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

šŸ’» Professional Endeavors

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

šŸ”¬ Contributions and Research Focus

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

šŸ† Accolades and Recognition

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

šŸŒ Impact and Influence

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

Publication

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

 

  • Title: RR3D: Uma soluĆ§Ć£o para renderizaĆ§Ć£o remota de imagens mĆ©dicas tridimensionais
    Author: Fabiano Papaiz
    Year: 2013

 

Conclusion

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