Sara Amjad | Computer Science | Innovative Research Award

Published on by Computer Scientists Awards

Innovative Research Award

Sara Amjad
Aligarh Muslim University, India

Sara Amjad
Affiliation Aligarh Muslim University
Country India
Scopus ID 57222341800
Documents 2
Citations 483
h-index 2
Subject Area Computer Science
Event Computer Scientists Awards
Google Scholar ID MCnRe20AAAAJ&hl

Sara Amjad is a researcher associated with Aligarh Muslim University whose scholarly record includes work spanning cellular metabolism, molecular signaling, genetics, neuroscience, and computationally relevant biomedical research. Her documented publications include collaborative review research examining NAD+-dependent cellular processes and the genetics of glutamate signaling in autism spectrum disorder. These works provide evidence of interdisciplinary engagement across molecular biology, health sciences, and data-informed research.

Abstract

Sara Amjad’s research profile is represented by collaborative publications addressing biological signaling, metabolism, genetics, and neurodevelopment. Her work on NAD+ reviews its importance in energy metabolism, DNA repair, gene expression, cellular stress, aging, cancer, and neurodegeneration. [1] A second publication examines genetic alterations involving glutamate and its receptors in autism spectrum disorder, connecting molecular genetics with neuroscience and non-invasive imaging. [2]

Keywords

  • Computer Science
  • NAD+ metabolism
  • Cellular signaling
  • Genetics
  • Neuroscience
  • Autism spectrum disorder

Introduction

The supplied publication record indicates an interdisciplinary research orientation. In the NAD+ review, the authors describe NAD+ as a critical coenzyme involved in bioenergetics and cellular signaling, while discussing its relationship with aging, metabolic disorders, cancer, and neurodegeneration. [1] The autism spectrum disorder review evaluates genetic changes affecting glutamate and glutamate receptors and considers imaging approaches for investigating altered glutamatergic pathways. [2]

Research Profile

The provided Scopus information lists two documents, 483 citations, and an h-index of 2. These supplied metrics should be interpreted as a profile snapshot because citation databases can change over time. The publications also demonstrate collaboration across institutions and disciplines, including molecular medicine, genetics, neuroscience, imaging, and biomedical research.

Research Contributions

Amjad’s documented contribution includes participation in research that synthesizes evidence across complex biological systems. The NAD+ article identifies cellular energy metabolism, DNA damage repair, gene expression, and stress response as major areas influenced by NAD+ biology. [1] The genetics review addresses glutamatergic signaling and receptor biology in relation to autism spectrum disorder, emphasizing interactions among genetics, neuronal function, and imaging. [2]

Publications

  • Role of NAD+ in regulating cellular and metabolic signaling pathways, Molecular Metabolism, 2021, 49:101195.. [1]
  • Genetics of glutamate and its receptors in autism spectrum disorder, Molecular Psychiatry, 2022, 27:2380–2392. . [2]

Research Impact

The supplied citation count of 483 indicates that the documented publication set has received substantial scholarly attention relative to its size. The cited research addresses topics with broad biomedical relevance, including metabolism, cellular signaling, genetics, and neurodevelopment. The Nature publication also records citation and access metrics on its publisher page, illustrating continuing visibility of the research area. [2]

Award Suitability

Based on the supplied profile and publication evidence, Sara Amjad can be considered for an Innovative Research Award in recognition of interdisciplinary scholarly participation and research addressing contemporary questions in cellular metabolism, molecular genetics, neuroscience, and biomedical science. The assessment should remain subject to the award committee’s independent verification of affiliation, authorship, bibliographic records, and current research metrics.

Conclusion

Sara Amjad’s documented research contributions demonstrate engagement with interdisciplinary biomedical questions and collaborative scientific scholarship. Her publications on NAD+ signaling and glutamate genetics provide a foundation for evaluating her research profile within an innovation-focused academic recognition framework.

References

  1. Amjad, S. et al. (2021). Role of NAD+ in regulating cellular and metabolic signaling pathways. Molecular Metabolism, 49, 101195.
    https://doi.org/10.1016/j.molmet.2021.101195
  2. Nisar, S. et al. (2022). Genetics of glutamate and its receptors in autism spectrum disorder. Molecular Psychiatry, 27, 2380–2392.
    https://doi.org/10.1038/s41380-022-01506-w
  3. PubMed. (2021). Role of NAD+ in regulating cellular and metabolic signaling pathways. PMID 33609766.
    https://pubmed.ncbi.nlm.nih.gov/33609766/
  4. PubMed. (2022). Genetics of glutamate and its receptors in autism spectrum disorder. PMID 35296811.
    https://pubmed.ncbi.nlm.nih.gov/35296811/
  5. Elsevier. (n.d.). Role of NAD+ in regulating cellular and metabolic signaling pathways. Molecular Metabolism.
    https://www.sciencedirect.com/science/article/pii/S2212877821000351
  6. Springer Nature. (2022). Genetics of glutamate and its receptors in autism spectrum disorder. Molecular Psychiatry.
    https://www.nature.com/articles/s41380-022-01506-w

Dr. Ehsan Adibnia | Computer Science | Editorial Board Member

Published on by Computer Scientists Awards

Dr. Ehsan Adibnia | Computer Science | Editorial Board Member

University of Sistan and Baluchestan | Iran

Dr. Ehsan Adibnia is a dedicated researcher in Electrical Engineering with a strong interdisciplinary focus spanning artificial intelligence, machine learning, deep learning, nanophotonics, optics, plasmonics, and photonic device engineering. His research primarily explores the integration of AI-driven approaches in nanophotonic design, optical switching, and biosensing applications, enabling significant advancements in optical computing and sensing technologies. He has made notable contributions to the fields of photonics and deep learning-based optical system design through innovative studies on inverse design, nonlinear plasmonic structures, and photonic crystal encoders. His expertise extends to advanced simulation tools such as Lumerical, COMSOL, and RSoft, as well as programming in MATLAB and Python for modeling and data analysis. Dr. Adibnia has actively contributed to scientific research through multiple peer-reviewed publications in prestigious international journals. According to Google Scholar, he has accumulated 6,540 citations, an h-index of 45, and an i10-index of 156, reflecting his significant academic influence. His Scopus profile records 70 citations across 53 documents with an h-index of 5, highlighting his growing global research impact.

Profiles

Scopus | ORCID | Google Scholar

Featured Publications

Adibnia, E., Mansouri-Birjandi, M. A., & Ghadrdan, M. (2024). A deep learning method for empirical spectral prediction and inverse design of all-optical nonlinear plasmonic ring resonator switches. Scientific Reports, 14, 5787.

Adibnia, E., Ghadrdan, M., & Mansouri-Birjandi, M. A. (2024). Nanophotonic structure inverse design for switching application using deep learning. Scientific Reports, 14, 21094.

Adibnia, E., Ghadrdan, M., & Mansouri-Birjandi, M. A. (2025). Chirped apodized fiber Bragg gratings inverse design via deep learning. Optics & Laser Technology, 181, 111766.

Jafari, B., Gholizadeh, E., Jafari, B., & Adibnia, E. (2023). Highly sensitive label-free biosensor: graphene/CaF2 multilayer for gas, cancer, virus, and diabetes detection. Scientific Reports, 13, 16184.

Soroosh, M., Al-Shammri, F. K., Maleki, M. J., Balaji, V. R., & Adibnia, E. (2025). A compact and fast resonant cavity-based encoder in photonic crystal platform. Crystals, 15, 24.

Hsin-Yuan Chen | Computer Science | Best Researcher Award

Published on by Computer Scientists Awards

Prof. Hsin-Yuan Chen | Computer Science | Best Researcher Award

Zhejiang University | China

Prof. Hsin-Yuan Chen is a distinguished scholar and technology leader known for his extensive contributions to artificial intelligence, robotics, and digital technology innovation. He currently serves as the Changjiang Scholar Professor and Director at Zhejiang University’s Institute of Wenzhou, Center of Digital Technology Entrepreneurship and Innovation in China, as well as Adjunct Distinguished Professor at Patil University in India. With an academic and professional journey spanning universities, research institutes, and top technology companies, Prof. Chen has built a reputation for pioneering research, impactful industry collaborations, and leadership in advancing global technology ecosystems.

Publication Profile

Scopus

ORCID

Education Background

Prof. Hsin-Yuan Chen pursued his academic studies at National Cheng Kung University, where he earned both his Bachelor’s and Ph.D. degrees in Aerospace Engineering, completing his doctoral program directly after undergraduate study. His rigorous academic foundation combined with a strong focus on applied research shaped his career path, enabling him to bridge advanced engineering knowledge with emerging fields like artificial intelligence and big data. His educational achievements not only established him as a capable researcher but also laid the groundwork for his future endeavors in academia, technology innovation, and international collaborations across multiple institutions and disciplines.

Professional Experience

Prof. Hsin-Yuan Chen has held numerous leadership and academic roles across diverse sectors. He served as Dean and Professor at Fujian Normal University’s School of Big Data and Artificial Intelligence, and also held CTO positions at GEOSAT Technology and Mobiletron Electronics, leading artificial intelligence applications in industry. His early career included academic appointments at Feng Chia University and National Taiwan Ocean University, alongside international experience as Visiting Professor at Washington University in St. Louis. Additionally, he contributed to public service as a Patent Examiner at the Intellectual Property Office and worked with Delta Electronics as Technical Advisor, balancing academia with industrial innovation.

Awards and Honors

Prof. Hsin-Yuan Chen has been widely recognized with prestigious national and international awards. His accolades include the ScienceFather International Outstanding Scientist Award, the Electronics Best Paper Award, and fellowship honors from IET and ASEAN. He has also received multiple innovation and creativity awards for projects in virtual reality, artificial intelligence, and cloud technology, particularly in digital cultural heritage applications. Earlier distinctions include the Global Top Hundred Engineers Medal, Youth Medal of the Republic of China, and recognition as one of the Top Ten Outstanding Young Women in the Republic of China. His achievements highlight his dedication to research, teaching, and technological innovation.

Research Focus

Prof. Hsin-Yuan Chen’s research primarily spans artificial intelligence, robotics, big data, digital innovation, and human-centered computing. He has extensively explored AI applications in fields such as healthcare, education, and cultural heritage digitalization. His work includes developing hybrid positioning systems, AI-driven recognition technologies, and bibliometric studies in AI applications. He has also focused on advancing industry-academia collaboration and integrating emerging technologies like VR, AR, and IoT into practical solutions. Through his contributions, Prof. Chen has advanced both theoretical research and applied science, strengthening connections between innovation, entrepreneurship, and real-world societal impact in the digital era.

Publication Notes

  1. Evaluating Machine Learning Algorithms for Alzheimer’s Detection: A Comprehensive Analysis
    Published Year: 2025
    Citation: 1

  2. Impact of Industry-Academia Collaboration in Engineering Education: A Case Study
    Published Year: 2025
    Citation: 3

  3. Recursive Queried Frequent Patterns Algorithm: Determining Frequent Pattern Sets from Database
    Published Year: 2025
    Citation: 2

  4. Mapping the Evolution: A Bibliometric Analysis of Employee Engagement and Performance in the Age of AI-Based Solutions
    Published Year: 2025
    Citation: 1

  5. Advancements in Handwritten Devanagari Character Recognition: A Study on Transfer Learning and VGG16 Algorithm
    Published Year: 2024
    Citation: 1

Conclusion

Prof. Hsin-Yuan Chen’s career exemplifies the synergy between academic excellence and industrial innovation. With a solid foundation in aerospace engineering, he has consistently expanded his expertise into artificial intelligence, robotics, and digital transformation. His leadership roles across universities, research institutions, and technology enterprises demonstrate his global influence, while his awards reflect recognition for outstanding achievements in both research and practice. As an educator, innovator, and scientist, Prof. Chen continues to inspire through his contributions to emerging technologies and his efforts in building bridges between academia and industry to shape the future of digital transformation.