Smita Nirkhi | Computer Science | Research Excellence Award

Research Excellence Award

Smita Nirkhi

Symbiosis Institute of Technology, India

Smita Nirkhi
Affiliation Symbiosis Institute of Technology
Country India
Scopus ID 25927431900
Documents 45
Citations 79
h-index 5
Subject Area Computer Science
Event Top Teachers Awards
ORCID 0000-0002-1235-8865
Google Scholar VJxAP-wAAAAJ

Smita Nirkhi is an associate professor at Symbiosis Institute of Technology, Nagpur, India, working in artificial intelligence, machine learning, data mining, and digital forensics. Her Scopus record lists 45 documents, 79 citations, and an h-index of 5 within Computer Science [1]. This article reviews her research profile and suitability for the Research Excellence Award conferred through the Top Teachers Awards event [4].

Abstract

This article documents the scholarly record of Smita Nirkhi in computer science, emphasizing artificial intelligence, data mining, and digital forensics. Her indexed output and citation profile support a case for recognition in the Research Excellence Award category, evaluated here through verifiable bibliometric and professional evidence [2].

Keywords

  • Artificial Intelligence
  • Machine Learning
  • Data Mining
  • Digital Forensics
  • Cyber Security
  • Pattern Recognition

Introduction

Smita Nirkhi has more than two decades of teaching experience and a doctorate in Computer Science and Engineering from Nagpur University, awarded in 2017 for work on data mining techniques for digital forensics. Her research spans web mining, cyber security, pattern recognition, and machine learning, and she has held academic leadership roles including head of an artificial intelligence department and IQAC in-charge [1].

Research Profile

The Scopus author profile records 45 documents, 79 citations, and an h-index of 5, with Computer Science as the principal subject area [1]. The Google Scholar profile reports broader visibility, with 464 citations and an h-index of 10 across 112 documents [2]. Her ORCID record provides a persistent identifier for these outputs [3].

Research Contributions

Smita Nirkhi has published 87 research papers, including 25 international journal papers, 57 international conference papers, and 5 national conference papers. Her work includes a comparative study of authorship identification techniques for cyber forensics analysis and an early examination of artificial neural networks in data mining [5] [6]. She has also authored books on data mining in cyber forensics and machine learning.

Publications

Her publication record comprises journal and conference articles in data mining, forensics, and machine learning, indexed in Scopus and Google Scholar [1] [2]. Notable works include forensic authorship identification research and neural network applications in data mining, with DOIs available through the cited repositories [5].

Research Impact

Citation metrics indicate a developing international footprint, with Scopus reporting 79 citations and Google Scholar reporting 464 citations for the same author [1] [2]. Her funded projects include an AICTE research grant, and she has supervised numerous postgraduate and undergraduate projects, contributing to research capacity in her institution.

Award Suitability

The Research Excellence Award recognizes sustained scholarly contribution and measurable research impact. Smita Nirkhi’s indexed publication record, citation profile, funded research, and academic leadership collectively support her suitability for this recognition under the Top Teachers Awards event [4].

Conclusion

Smita Nirkhi presents a consistent record of research activity in computer science, supported by indexed publications, citation data, and professional service. Her profile aligns with the criteria of the Research Excellence Award, and her verified identifiers enable independent confirmation of the reported metrics [1] [2] [3].

References

  1. Elsevier. (n.d.). Scopus author details: Smita Nirkhi, Author ID 25927431900. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=25927431900
  2. Google Scholar. (n.d.). Citations profile: Smita Nirkhi. Google Scholar.
    https://scholar.google.com/citations?user=VJxAP-wAAAAJ&hl=en&oi=sra
  3. ORCID. (n.d.). ORCID record: Smita Nirkhi, 0000-0002-1235-8865. ORCID.
    https://orcid.org/0000-0002-1235-8865
  4. Top Teachers Awards. (n.d.). Award information and nomination details. Top Teachers.
    https://topteachers.net
  5. Nirkhi, S., & Dharaskar, R. V. (2013). Comparative study of authorship identification techniques for cyber forensics analysis. arXiv preprint arXiv:1401.6118.
    https://doi.org/10.48550/arXiv.1401.6118
  6. Nirkhi, S. (2010). Potential use of artificial neural network in data mining. Proceedings of the 2nd International Conference on Computer and Automation Engineering (ICCAE).
    https://doi.org/10.1109/ICCAE.2010.5451537

Abdalilah Alhalangy | Computer Science | Innovative Research Award

Assoc. Prof. Dr. Abdalilah Alhalangy | Computer Science | Innovative Research Award

Qassim university | Saudi Arabia

Assoc. Prof. Dr. Abdalilah Alhalangy, Ph.D., is an Associate Professor in Computer Engineering at Qassim University, Kingdom of Saudi Arabia, specializing in advanced areas of artificial intelligence, machine learning, intelligent systems, and cybersecurity. His research spans deep learning, ensemble methods, neural networks, computer vision, wireless networks, cloud computing, big data analytics, robotics, augmented reality, mobile applications, image and video analysis, GIS, and e-learning systems. He has a particular focus on artificial neural networks, wavelet neural networks, fuzzy logic, evolutionary algorithms, and computational intelligence, applied to enhancing the security and functional performance of intelligent systems. Dr. Al-Halangy has published 6 documents cited by 59 Scopus-indexed papers, achieving a Scopus h-index of 3 and an i10-index of 2 on Google Scholar, with a total of 131 citations. His work has earned recognition in fields ranging from Arabic speech emotion recognition and fake account detection in mobile networks to generative AI-driven cybersecurity systems and the evaluation of e-learning effectiveness. Dr. Al-Halangy’s research is characterized by its innovative integration of AI techniques to solve complex real-world problems, positioning him as a leading contributor to modern computing challenges. He has received accolades including the Innovative Research Award for his contributions to the development of secure, intelligent, and efficient computational systems. His work continues to impact both academic research and practical applications, advancing the state of intelligent and adaptive technologies globally.

Publication Profile

Scopus | Orcid | Google Scholar

Featured Publications

  • Alhalangy, A., & AbdAlgane, M. (2023). Exploring the impact of AI on the EFL context: A case study of Saudi universities.

  • Alhalangy, A. (2024). Deep learning, ensemble and supervised machine learning for Arabic speech emotion recognition. Engineering, Technology & Applied Science Research, 14, 1-10.

  • Hassan, A., & Alhalangy, G. I. A. (2023). Fake accounts identification in mobile communication networks based on machine learning. SSRN.

  • Alhalangy, A., Elhadi, O. A. M., & Mohamed, E. H. G. (2025). E-learning effectiveness and efficiency in Kassala and Gedaref universities: An IS-impact evaluation. UtilitasMathematica, 122(2), 1301-1317.

  • Alhalangy, A. (2025). Generative AI-driven information system for behavioral detection of zero-day cyber attacks. UtilitasMathematica, 122(2), 1194-1210.