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.

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 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.

 

Fabiano Papaiz | Computational Neuroscience | Best Researcher Award

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Prof. Fabiano Papaiz | Computational Neuroscience | Best Researcher Award

Prof. Fabiano Papaiz, IFRN, Brazil.

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

Profile

Orcid

 

📚 Early Academic Pursuits

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

💻 Professional Endeavors

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

🔬 Contributions and Research Focus

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

🏆 Accolades and Recognition

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

🌍 Impact and Influence

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

Publication

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

 

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

 

Conclusion

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

 

Peishun Ye | Image Classification | Best Researcher Award

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Prof. Peishun Ye | Image Classification | Best Researcher Award

Prof. Peishun Ye, Yulin University, China.

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

Profile

Scopus

🎓 Early Academic Pursuits

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

🏛️ Professional Endeavors

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

💡 Contributions and Research Focus

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

🎯 Accolades and Recognition

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

🌐 Impact and Influence

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

 

Publication

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

  • Author: Ye, Peishun

  • Year: 2010​

🎨 Conclusion

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


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Kiran Solingapuram Sai | Neuroimaging | Best Researcher Award

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Dr. Kiran Solingapuram Sai | Neuroimaging | Best Researcher Award

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

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

Profile

Orcid

 

✨ Early Academic Pursuits

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

🌐 Professional Endeavors

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

⚛️ Contributions and Research Focus

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

🏆 Accolades and Recognition

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

🔬 Impact and Influence

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

💡 Legacy and Future Contributions

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

 

Publication

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

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

 

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

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

 

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

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

 

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

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

 

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

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

 

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

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

 

Conclusion

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

Maria Habib | Optimization | Best Researcher Award

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Ms. Maria Habib | Optimization | Best Researcher Award

Ms. Maria Habib, Granada University/ Samsung R&D (SRJO), Jordan.

Maria Habib is a distinguished researcher and AI engineer whose journey spans academia and industry. With a strong foundation in Computer Engineering, she advanced her expertise through a Master’s in Web Intelligence and is currently pursuing a Ph.D. in Information Technology and Communication. Maria’s professional endeavors include leading AI projects at Samsung R&D, transforming telehealth services at Altibbi, and contributing to bioinformatics at McGill University. Her research focuses on artificial intelligence, machine learning, evolutionary algorithms, and NLP, producing innovative solutions and influential publications. Her work has significantly impacted telemedicine, educational data mining, and speech technologies, establishing her as a transformative force in AI.

Profile

Scholar

Early Academic Pursuits 🎓

Maria Habib embarked on her academic journey with a robust foundation in Computer Engineering, earning her Bachelor’s degree from the University of Jordan in 2014. Demonstrating early promise, she excelled in her Master’s program in Web Intelligence at the prestigious King Abdullah II School for Information Technology, attaining an outstanding GPA of 3.91/4. Her passion for leveraging technology to address real-world challenges was evident from the outset, as she explored advanced concepts in information systems and web technologies. Maria is currently pursuing her Ph.D. in Information Technology and Communication at Granada University, Spain, where she continues to delve into cutting-edge AI research.

Professional Endeavors 💼

Maria’s career trajectory reflects a seamless blend of academic rigor and industry innovation. At Samsung R&D Institute in Jordan, she leads AI projects focusing on speech recognition and natural language processing, showcasing her prowess in automation and advanced search systems. Prior to this, Maria honed her skills at Altibbi, where she developed machine learning and deep learning models to revolutionize telehealth services. Her expertise spans diverse roles, from Python development for logistics platforms at Polares LLC to teaching Computer Science at ADS School. Each position has deepened her technical acumen and solidified her reputation as a versatile problem-solver.

Contributions and Research Focus 🔬

Maria’s research centers on artificial intelligence, machine learning, and evolutionary algorithms, emphasizing their transformative potential in healthcare, education, and NLP. Her collaborations with renowned academics like Prof. Hossam Faris and Dr. Ghaith Rabadi have resulted in influential publications in prestigious journals. Her work extends to bioinformatics, where she contributed to microbiome data visualization during her tenure as a Graduate Research Trainee at McGill University. As a member of the Evo-ML research group, Maria explores innovative solutions that bridge academia and industry, reinforcing her commitment to advancing AI for societal benefit.

Accolades and Recognition 🏆

Maria’s dedication to excellence has not gone unnoticed. Her stellar academic performance earned her accolades throughout her educational journey, culminating in a Master’s GPA of 3.91/4.0. Her professional roles have been marked by commendations for innovation and leadership, particularly at Samsung R&D and Altibbi. References from distinguished mentors like Prof. Ibrahim Aljarah and Prof. Jiangou Xia underscore the high regard in which she is held within the academic and professional communities.

Impact and Influence 🌍

Through her work in AI, Maria has significantly impacted fields such as telemedicine, educational data mining, and speech understanding. Her contributions to Altibbi transformed telehealth services, making them more accessible and efficient. Her teaching and mentorship roles have inspired students and peers alike, fostering a new generation of tech enthusiasts. Her initiatives in AI automation and optimization continue to resonate within the global technology landscape.

Legacy and Future Contributions 🌟

Maria’s journey is far from over. As an AI Project Lead and researcher, she is poised to shape the future of speech and language technologies. Her ongoing Ph.D. research promises groundbreaking insights into AI and communication systems. With a clear vision for the future, Maria aspires to bridge the gap between research and real-world applications, ensuring her legacy as a pioneer in computational innovation.

📚 Publications

  1. Title: Intelligent detection of hate speech in Arabic social network: A machine learning approach
    Authors: I. Aljarah, M. Habib, N. Hijazi, H. Faris, R. Qaddoura, B. Hammo, …
    Year: 2021

 

  1. Title: A dynamic locality multi-objective salp swarm algorithm for feature selection
    Authors: I. Aljarah, M. Habib, H. Faris, N. Al-Madi, A.A. Heidari, M. Mafarja, …
    Year: 2020

 

  1. Title: Augmented whale feature selection for IoT attacks: Structure, analysis, and applications
    Authors: M. Mafarja, A.A. Heidari, M. Habib, H. Faris, T. Thaher, I. Aljarah
    Year: 2020

 

  1. Title: Android ransomware detection based on a hybrid evolutionary approach in the context of highly imbalanced data
    Authors: I. Almomani, R. Qaddoura, M. Habib, S. Alsoghyer, A. Al Khayer, I. Aljarah, …
    Year: 2021

 

  1. Title: Evolutionary inspired approach for mental stress detection using EEG signal
    Authors: L.D. Sharma, V.K. Bohat, M. Habib, A.Z. Ala’M, H. Faris, I. Aljarah
    Year: 2022

 

  1. Title: Hate Speech Detection using Word Embedding and Deep Learning in the Arabic Language Context
    Authors: H. Faris, I. Aljarah, M. Habib, P.A. Castillo
    Year: 2020

 

  1. Title: An intelligent evolutionary extreme gradient boosting algorithm development for modeling scour depths under submerged weir
    Authors: H. Tao, M. Habib, I. Aljarah, H. Faris, H.A. Afan, Z.M. Yaseen
    Year: 2021

 

  1. Title: Optimizing extreme learning machines using chains of salps for efficient android ransomware detection
    Authors: H. Faris, M. Habib, I. Almomani, M. Eshtay, I. Aljarah
    Year: 2020

 

  1. Title: Salp chain-based optimization of support vector machines and feature weighting for medical diagnostic information systems
    Authors: A.M. Al-Zoubi, A.A. Heidari, M. Habib, H. Faris, I. Aljarah, M.A. Hassonah
    Year: 2020

 

 

Conclusion

Maria Habib’s career exemplifies the intersection of technical expertise and societal impact. Through her leadership and innovative research, she has contributed to advancements in healthcare, communication, and education. Her commitment to bridging research and application ensures her legacy as a pioneer in AI. Maria’s inspiring journey underscores the power of determination and innovation, positioning her as a role model in the global technology community.

Sunday Aboyeji | Feature selection | Best Researcher Award

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Mr. Sunday Aboyeji | Feature selection | Best Researcher Award

Mr. Sunday Aboyeji, Shenzhen Institutes of Advanced Technology, China.

Sunday Timothy Aboyeji is an accomplished researcher in computational science and biomedical signal processing. With an impressive academic foundation in physics and communication science, he has pursued groundbreaking research in patient-independent seizure classification using EEG data. His work combines advanced algorithms, deep learning, and explainable AI to enhance the accuracy and interpretability of diagnostic tools for epilepsy and other neurological disorders. His dedication to interdisciplinary collaboration and his contributions to high-impact publications reflect his influence in the field.

 

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Scholar

📚 Early academic pursuits

Sunday Timothy Aboyeji began his academic journey with an unwavering passion for physical and computational sciences. Earning his Bachelor of Technology in Physics/Electronics from the Federal University of Technology, Minna, Nigeria, he graduated with first-class honors and a stellar GPA of 4.61/5.00. His undergraduate thesis, which explored the simulation of radiofrequency radiation effects on the brain, laid the foundation for his future endeavors in biomedical signal processing. He further honed his expertise by completing a Master’s degree in Communication Physics at the Federal University of Technology, Akure, Nigeria, achieving an outstanding GPA of 4.86/5.00. His master’s research on radioclimatic variables and refractivity modeling highlighted his ability to blend theoretical knowledge with practical applications.

🔬 Professional endeavors

Sunday is currently pursuing a Ph.D. in Pattern Recognition and Intelligent Systems at the University of Chinese Academy of Sciences, Shenzhen Institute of Advanced Technology, China. His doctoral dissertation focuses on developing patient-independent EEG-based seizure classification algorithms. Over the course of his research, he has designed cutting-edge solutions integrating signal processing, feature engineering, and deep learning. His projects include unsupervised seizure detection, feature fusion of Gramian angular fields, and domain adaptation frameworks, all aimed at revolutionizing epilepsy diagnosis. Beyond his academic achievements, he is an active member of IEEE and serves as a certified first-aider in Shenzhen, demonstrating his dedication to community service and professional growth.

🧠 Contributions and research focus

Sunday’s research has profoundly impacted computational science and biomedical signal processing. He specializes in the analysis of EEG, EMG, and other complex biomedical signals using advanced algorithms and explainable AI techniques. His groundbreaking work emphasizes the interpretability of deep learning models, enabling better diagnostic tools for epilepsy and other neurological disorders. By transforming biomedical signals into visual spectrograms and leveraging hybrid feature selection frameworks, he has created highly accurate and reliable classification models that support patient care and advance brain-computer interface technology.

🏆 Accolades and recognition

Sunday’s academic excellence has been recognized through multiple awards, including the prestigious Chinese Government Scholarship for his Ph.D. studies. His undergraduate achievements earned him commendations from his university dean. These accolades reflect his dedication to academic rigor and his ability to excel in highly competitive environments. He has also been invited to serve as a peer reviewer for leading journals, further solidifying his reputation as a rising star in his field.

🌍 Impact and influence

Through collaborative efforts with international scholars and researchers, Sunday has contributed to several high-impact publications in journals such as Computers in Biology and Medicine and the IEEE Journal of Biomedical and Health Informatics. His work on robust seizure detection and interpretable machine learning models has set a benchmark for researchers in biomedical signal processing. These contributions not only enhance patient diagnostics but also pave the way for more accessible healthcare technologies.

🌟 Legacy and future contributions

Sunday aspires to leave a legacy as a trailblazer in biomedical signal processing and computational sciences. His ongoing research on domain adaptation frameworks promises to address patient-specific challenges, making diagnostic systems more generalized and inclusive. He envisions leveraging his expertise to develop innovative solutions that enhance the quality of life for individuals with neurological disorders, ensuring his work continues to inspire and benefit the global scientific community.

💡 Dedication to innovation

Sunday’s career exemplifies a commitment to innovation, interdisciplinary collaboration, and societal impact. With his technical skills in Python, TensorFlow, and Pytorch, coupled with a deep understanding of signal processing and pattern recognition, he remains at the forefront of research in his field. His dedication to integrating advanced technology with real-world applications underscores his role as a visionary researcher and advocate for progress in medical diagnostics.

📚 Publications

  • Title: Robust Epileptic Seizure Detection Based on Biomedical Signals Using an Advanced Multi-View Deep Feature Learning Approach
    Authors: Ijaz Ahmad, Zhenzhen Liu, Lin Li, Inam Ullah, Sunday Timothy Aboyeji, Xin Wang, Oluwarotimi Williams Samuel, Guanglin Li, Yuan Tao, Yan Chen, et al.
    Year: 2024

 

  • Title: Automatic Detection of Epileptic Seizure Based on One Dimensional Cascaded Convolutional Autoencoder with Adaptive Window-Thresholding
    Authors: Sunday Timothy Aboyeji, Xin Wang, Yan Chen, Ijaz Ahmad, Lin Li, Zhenzhen Liu, Chen Yao, Guoru Zhao, Yu Zhang, Guanglin Li, et al.
    Year: 2024

 

  • Title: Feature Fusion of Gramian Angular Field Deep Learning EEG-Based Epileptic Seizure Classification
    Authors: Sunday Timothy Aboyeji, Xin Wang, Yan Chen, Ijaz Ahmad, Lin Li, Zhenzhen Liu, Chen Yao, Yu Zhang, Guoru Zhao, Guanglin Li, et al.
    Year: 2024

 

  • Title: Modeling of Atmospheric Primary Radioclimatic Variables in Nigeria for Microwave Radio Propagation Applications
    Authors: Falodun, S.E., Ojo, J.S., Aboyeji, S.T.
    Year: 2021

 

Conclusion

Sunday’s journey exemplifies a relentless pursuit of knowledge and innovation. From his academic excellence in Nigeria to his impactful research at the Shenzhen Institute of Advanced Technology, he has made meaningful strides in advancing patient care through computational science. With a clear vision for the future, his contributions promise to continue shaping the landscape of biomedical signal processing and inspire further advancements in medical diagnostics.

 

Chen Wang | neural network application | Best Researcher Award

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Prof Dr.Chen Wang | neural network application | Best Researcher Award

Prof Dr Chen Wang School of Mining, Guizhou University China

Wang Chen is a distinguished professor at Guizhou University, specializing in mining engineering and resources and environment. He holds a PhD from the China University of Mining and Technology and has significant expertise in mining methods, rock mechanics, mining system engineering, and the kinematic behavior of rock layers in karst regions.

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📚 Recruitment Discipline Direction

Mining Engineering, Resources and Environment

🔬 Main Research Fields and Directions

Mining Methods,Rock Mechanics,Mining System Engineering,Roadway Support,Kinematic Mechanisms of Rock Layers in Karst Mountainous Areas.

💼 Key Research Projects (2018 – Present)

National Natural Science Foundation General Project (52174072)“Study on the Mechanisms of Rock Layer Movement under Repeated Mining in Karst Mountainous Areas,” 2022.01-2025.12, 580,000 RMB, Principal Investigator, ongoing. 💰National Natural Science Foundation Youth Science Fund Project (51904081)“Study on the Mechanisms of Instability Induced by Mining in Shallowly Buried Coal Layers in Karst Terrain,” 2020.01-2022.12, 240,000 RMB, Principal Investigator, ongoing. 🔍

✍️ Journal Articles:

Wang Chen et al. “An Expert System for Equipment Selection of Thin Coal Seam Mining.” (2019) .Wang Chen et al. “Optimal Selection of a Longwall Mining Method for a Thin Coal Seam Working Face.” (2016) .Wang Chen, Zhou Jie. “New Advances in Automatic Shearer Cutting Technology.” (2021) ⚙️

🥇 Achievements

Patents: 5 granted invention patents related to coal mining technology. Awards: Multiple research awards for contributions to mining technology. 🏆

📚 Publications

  1. Title: Study on strength prediction and strength change of Phosphogypsum-based composite cementitious backfill based on BP neural network
    Authors: Wu, M., Wang, C., Zuo, Y., Zhang, J., Luo, Y.
    Year: 2024
    Journal: Materials Today Communications
    Volume: 41
    Article Number: 110331

 

  1. Title: Correction: Determination of working resistance of support parameter variation of large mining height support: the case of Caojiatan coal mine
    Authors: Xue, B., Zhang, W., Wang, C.
    Year: 2024
    Journal: Geomechanics and Geophysics for Geo-Energy and Geo-Resources
    Volume: 10
    Issue: 1
    Pages: 14

 

  1. Title: Determination of working resistance of support parameter variation of large mining height support: the case of Caojiatan coal mine
    Authors: Xue, B., Zhang, W., Wang, C.
    Year: 2024
    Journal: Geomechanics and Geophysics for Geo-Energy and Geo-Resources
    Volume: 10
    Issue: 1
    Pages: 1

 

  1. Title: Evolution of Broken Coal’s Permeability Characteristics under Cyclic Loading–Unloading Conditions
    Authors: Luo, L., Zhang, L., Pan, J., Wang, C., Li, S.
    Year: 2024
    Journal: Natural Resources Research
    Volume: 33
    Issue: 5
    Pages: 2279–2297

 

  1. Title: Preparation and characterization of green lignin modified mineral cementitious firefighting materials based on uncalcined coal gangue and coal fly ash
    Authors: Dou, G., Wang, C., Zhong, X., Qin, B.
    Year: 2024
    Journal: Construction and Building Materials
    Volume: 435
    Article Number: 136799

 

  1. Title: Mining Technology Evaluation for Steep Coal Seams Based on a GA-BP Neural Network
    Authors: Li, X., Wang, C., Li, C., Luo, Y., Jiang, S.
    Year: 2024
    Journal: ACS Omega
    Volume: 9
    Issue: 23
    Pages: 25309–25321

 

  1. Title: Capturing rate- and temperature-dependent behavior of concrete using a thermodynamically consistent viscoplastic-damage model
    Authors: Tao, J., Yang, X.-G., Lei, Y., Wang, C.
    Year: 2024
    Journal: Construction and Building Materials
    Volume: 422
    Article Number: 135791

Conclusion

Wang Chen’s extensive research and numerous publications significantly contribute to the field of mining engineering. His focus on the complexities of karst geology and the development of intelligent mining technologies positions him as a leader in advancing mining safety and efficiency. His ongoing projects reflect a commitment to addressing contemporary challenges in the mining sector, particularly in relation to environmental sustainability and resource management.