Sara Amjad | Computer Science | Innovative Research Award

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

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.

Jihyeon Ryu | Computer Science | Best Researcher Award

Assist Prof Dr. Jihyeon Ryu | Computer Science | Best Researcher Award

Professor, Kwangwoon University, South Korea

👩‍🏫 Jihyeon Ryu is an Assistant Professor at the School of Computer and Information Engineering, Kwangwoon University. She specializes in split learning, convolutional neural networks, and user authentication, contributing significantly to the field of computer science with her extensive research and numerous publications.

Profile

Google Scholar

 

Education

Ph.D. in Software (Integrated Master’s and Doctorate Course) from Sungkyunkwan University (Mar. 2018 – Feb. 2023), advised by Prof. Dongho Won and Prof. Hyoungshick Kim. B.S. in Mathematics and Computer Science and Engineering from Sungkyunkwan University (Mar. 2013 – Feb. 2018). Early Graduation from Sejong Science High School (Mar. 2011 – Feb. 2013).

 

Research Interests:

Split Learning. Convolutional Neural Networks. User Authentication

Awards

Family Company Workshop Lecture, Hoseo University (Feb. 2022). Invited Lecturer, Mental Women’s High School (Nov. 2021). Excellence Prize, Software Department Excellence Research Awards (Feb. 2021). Graduate Merit Scholarship, Sungkyunkwan University (Mar. 2018 – Feb. 2021). SimSan Scholarship, Multiple instances (Mar. 2018 – Sep. 2020). Excellence Award, 국가 암호기술 전문인력 양성과정 (Nov. 2019). Grand Prize, Software Department Excellence Research Awards (Feb. 2019). Samsung Science Scholarship (Mar. 2013 – Feb. 2018)

Publications

Lightweight Hash-Based Authentication Protocol for Smart Grids. Sensors, 2024. Sangjin Kook, Keunok Kim, Jihyeon Ryu, Youngsook Lee, Dongho Won.

Enhanced Lightweight Medical Sensor Networks Authentication Scheme Based on Blockchain. IEEE ACCESS, 2024. Taewoong Kang, Naryun Woo, Jihyeon Ryu.

Secure and Anonymous Authentication Scheme for Mobile Edge Computing Environments. IEEE Internet of Things Journal, 2024. Hakjun Lee, Jihyeon Ryu, Dongho Won.

Distributed and Federated Authentication Schemes Based on Updatable Smart Contracts. Electronics, 2023. Keunok Kim, Jihyeon Ryu, Hakjun Lee, Youngsook Lee, Dongho Won.

An Improved Lightweight User Authentication Scheme for the Internet of Medical Things. Sensors, 2023. Keunok Kim, Jihyeon Ryu, Youngsook Lee, Dongho Won.