Fareeha Anwar | Computer Science | Best Researcher Award

Best Researcher Award

Fareeha Anwar
Imam Mohammad Ibn Saud Islamic University, Saudi Arabia

Fareeha Anwar
Affiliation Imam Mohammad Ibn Saud Islamic University
Country Saudi Arabia
Scopus ID 36197820200
Documents 5
Citations 145
h-index 5
Subject Area Computer Science
Event Environmental Scientists
ORCID 0000-0002-6993-7761

Fareeha Anwar is a researcher affiliated with Imam Mohammad Ibn Saud Islamic University whose scholarly work contributes to the field of Computer Science. Her publication record, citation profile, and international research visibility demonstrate continuing academic engagement and provide a foundation for professional recognition within multidisciplinary scientific communities. reflecting a commitment to solving complex real-world challenges through innovative technologies. Her publication record, citation profile, and international research visibility demonstrate sustained academic engagement and an active contribution to multidisciplinary scientific research.[1]

Abstract

This article summarizes the academic profile of Fareeha Anwar and highlights her research achievements, scholarly publications, and citation performance. The profile reflects measurable scientific activity in Computer Science and recognizes contributions through internationally indexed research outputs.[2]

Keywords

Computer Science, Artificial Intelligence, Academic Research, Scopus, Scholarly Publications, Citation Analysis, Research Excellence, Best Researcher Award.

Introduction

Academic excellence is evaluated through research quality, publication impact, and continued scholarly engagement. International indexing services provide transparent indicators that support the recognition of researchers across scientific disciplines.[1]

Research Profile

Fareeha Anwar has established a research profile supported by indexed publications and growing citation metrics. Her academic activities demonstrate sustained participation in Computer Science research while contributing to collaborative scientific advancement.[3]

Research Contributions

Her publications address contemporary computational topics and reflect an emphasis on knowledge development within Computer Science. These contributions support the dissemination of research findings through peer-reviewed scholarly communication.[4]

Publications

The available publication record includes five Scopus-indexed documents with accumulated citations that demonstrate academic visibility. Persistent citation activity indicates continued relevance and accessibility within the international research community.[1]

Research Impact

With 145 citations and an h-index of 5, the available bibliometric indicators suggest measurable research influence. These metrics provide objective evidence of scholarly recognition and support broader academic evaluation processes.[2]

Award Suitability

Based on her documented publication history, citation performance, and institutional affiliation, Fareeha Anwar demonstrates characteristics commonly considered during research excellence evaluations. These achievements align with the objectives of the Environmental Scientists Best Researcher Award program.[5]

Conclusion

Fareeha Anwar’s academic profile reflects continued scholarly productivity and measurable research impact within Computer Science. Her documented achievements represent a solid foundation for academic recognition and future research development.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Fareeha Anwar, Author ID 36197820200. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=36197820200
  2. ORCID. (n.d.). Fareeha Anwar ORCID Record.
    https://orcid.org/0000-0002-6993-7761
  3. Google Scholar. (n.d.). Fareeha Anwar Citation Profile.
    https://scholar.google.com/citations?hl=en&user=7zlArcAAAAAJ
  4. Abdullah, S., Anwar, F., & Fatima, M. (2026). Spiking neural networks for real-time mapping of EBV-infected B cells in neuroinflammatory lesions. Annals of Medicine & Surgery. Advance online publication.
    https://doi.org/10.1097/MS9.0000000000005088
  5. Mohammad, U. G., Imtiaz, S., Shakya, M., Almadhor, A., & Anwar, F. (2022). An optimized feature selection method using ensemble classifiers in software defect prediction for healthcare systems. Wireless Communications and Mobile Computing, 2022, Article 1028175
    https://onlinelibrary.wiley.com/doi/10.1155/2022/1028175

Khalil Abdelnaby | Computer Science | Research Excellence Award

Mr. Vivek Dwivedi | Computer Science | Research Excellence Award

Al-Ahliyya Amman university | Jordan

Dr. Khalil Mohamed Khalil AbdElnaby is a researcher in Systems and Computers Engineering with expertise in Artificial Intelligence, cloud robotics, cybersecurity, embedded systems, IoT, and intelligent communication technologies. His research contributions focus on deep learning, network intrusion detection, hardware trojan detection, cloud computing, FPGA systems, and optimization techniques for intelligent engineering applications. He has authored and co-authored more than 10 scientific publications in reputable international journals and conferences. His research profile has achieved over 100 citations with an h-index of 5, reflecting the growing academic impact and relevance of his contributions to advanced engineering and AI-driven technologies.

Professional Profiles 

Education Background

Moumita Ghosh | Computer Science | Best Researcher Award

Dr. Moumita Ghosh | Computer Science | Best Researcher Award

Assistant Professor, Heritage Institute of Technology, India

Dr. Moumita Ghosh (PhD, Engg.) is a passionate researcher from Kolkata, India 🇮🇳, currently working as an Assistant Professor in the Department of Computer Science and Engineering at the Heritage Institute of Technology. Her core research interests lie at the intersection of Data Science and Computational Biodiversity. With a deep commitment to innovation and academia, she integrates machine learning and data mining techniques to address biodiversity conservation and complex ecological data analysis. 👩‍🏫🌿📊

Profile

Orcid

Education 🎓

Dr. Ghosh holds a Ph.D. in Engineering (2019–2024) from Jadavpur University, Kolkata, with her thesis focusing on “Algorithms for Data Mining: Applications in Biodiversity” 🧠🌱. She earned her M.E. in Multimedia Development from the same university (2011–2013) and completed her B.Tech. in Info Technology from WBUT in 2011. She also achieved outstanding academic performance in both her higher secondary and secondary education at Ichapur Girls’ High School. 🎓

Experience 💼

With over a decade of academic experience, Dr. Ghosh has served in key teaching roles at several premier institutions. She currently teaches Data Structures at Heritage Institute of Technology (2024–Present). Previously, she worked at Narula Institute of Technology (2022–2024), Jadavpur University (as a guest faculty and later PI for a DST-funded project), and held Assistant Professor roles at Institute of Engineering and Management (2015–2017) and Bengal College of Engineering and Technology (2013–2015). 💻📚

Research Interest 🔍

Dr. Ghosh’s research bridges Data Science and Ecology through Computational Biodiversity 🌍🧬. Her work includes pattern mining, remote sensing data, complex networks, and biodiversity modeling using advanced machine learning algorithms. She explores how AI and statistical methods can help mitigate biodiversity loss, emphasizing ecological data interpretation and predictive modeling. Her interests extend to deep learning, natural language processing, and ecological network analysis. 📈🌐

Awards 🏆

Dr. Ghosh is a UGC NET qualifier (2017 & 2018) and was awarded the prestigious DST Women Scientists Fellowship (2019–2022), where she led a ₹22 lakh project on biodiversity data mining. She collaborates internationally with Universitas Islam Indonesia and has served as a reviewer and TPC member for various global conferences. She is a proud member of the Computer Society of India (CSI) since 2021. 🏅🌟

Publications 📄

📖 Ghosh et al. (2023). “An Irregular CLA-based Novel Frequent Pattern Mining Approach.” International Journal of Data Mining, Modelling and Management. DOI

📖 Ghosh et al. (2022). “Recognition of Coexistence Pattern of Salt Marshes and Mangroves.” Ecological Informatics. DOI

📖 Ghosh et al. (2022). “Frequent itemset mining using FP-tree.” Innovations in Systems and Software Engineering.

📖 Ghosh et al. (2021). “Knowledge Discovery of Sundarban Mangrove Species.” SN Computer Science. DOI

📖 Ghosh et al. (2021). “Prediction of Interaction between SARS-CoV-2 and Human Protein.” Journal of The Institution of Engineers (India): Series B. DOI

📖 Mondal, Ghosh et al. (2022). “Suffix forest for mining tri-clusters from time-series data.” Innovations in Systems and Software Engineering.

📖 Ghosh & Parekh (2013). “Fish shape recognition using multiple shape descriptors.” International Journal of Computer Applications.

Conclusion

Dr. Moumita Ghosh is a highly suitable candidate for the Best Researcher Award. Her innovative integration of machine learning and biodiversity studies, coupled with a solid record of publications, a granted patent, and a DST fellowship, reflects both depth and societal relevance in her research. With continued international exposure and independent research leadership, she is poised to make significant contributions to science and sustainability.