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Ms. Sheenam Naaz

Ms. Sheenam Naaz

Assistant Professor , Computer Science & Engineering (CSE)

sheenamn.naaz@sharda.ac.in

About

Ms. Sheenam Naaz is an Assistant Professor in the Department of Computer Science and Engineering, SSCSE, Sharda University, Greater Noida. Currently, she is pursuing her PhD at Jamia Hamdard University, with a research focus on emerging technologies such as blockchain, artificial intelligence and machine learning (AI/ML), and the Internet of Things (IoT) for smart city security enhancement. She holds a Masters degree (M.Tech) in Computer Science and Engineering with specialization in Cyber Forensics and Information Security and a Bachelors degree (B.Tech) in Computer Science and Engineering. Her research aims to develop secure and intelligent frameworks addressing real-world challenges in urban safety, data security, and resilient infrastructures. She has published over 30 research articles in national and international conferences, Scopus-indexed journals, and top-tier SCI journal, and holds three patents. She has served as a reviewer for more than 65 international conferences and reputed journals and has also acted as a session chair at international conferences. With a strong passion for teaching and research, Ms. Naaz is dedicated to mentoring students and contributing meaningfully to the academic community.

Experience
  • 4+ Years
Qualification
  • PhD (Pursuing- Thesis submitted), Jamia Hamdard University, New Delhi
  • M. Tech CSE With Specialization in Cyber Forensics and Information Security, Jamia Hamdard University, New Delhi
  • B. Tech CSE, Teerthanker Mahaveer University, Moradabad, UP
  • Diploma in CSE, Teerthanker Mahaveer University, Moradabad, UP
Award & Recognition

  • Reviewer and Meta-Reviewer at 60+ International Conferences
  • Session chair at 2 international conferences

Research

  • Naaz, S., Parveen, S., Tanweer, S., & Khan, I. R. (2025). EKMRS: Elliptic Key Modified Rivest Shamir Adleman Scheme for Secure Data Sharing and Authentication in Smart City Applications. Transactions on Emerging Telecommunications Technologies36(10), e70265.
  • Naaz, S., Parveen, S., Tanweer, S., & Khan, I. R. (2026). Blockchain-Driven Scalable Authentication for Urban IoT Applications. In Social Internet of Things (SIoT) and Machine Learning—Enhancing Interconnectivity and Intelligence (pp. 65-80). Cham: Springer Nature Switzerland.
  • Naaz, S., Parveen, S., Khan, I. R., & Tanweer, S. (2025, March). Empowering Smart Cities Through IoT and AI: Enhancing Decision-Making for a Data-Driven Future. In 2025 3rd International Conference on Disruptive Technologies (ICDT) (pp. 99-103). IEEE.
  • Anil Khatak, Sheenam Naaz. (2024). Real-Time Multi-Mode Hand Gesture Recognition Using MediaPipe and Deep Learning for Human-Computer Interaction . Journal of Computational Analysis and Applications (JoCAAA)33(08), 6610–6621. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/3848
  • Anil Khatak, Sheenam Naaz. (2024). Data-Driven Prediction of Earthquake Parameters Using Historical Seismic Records and Machine Learning . Journal of Computational Analysis and Applications (JoCAAA)33(08), 6599–6609. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/3847

Total: 32+ articles

Certifications

  • NPTEL-AICTE course on Accreditation and Outcome Based Learning, 2025
  • Optimizing Machine Learning Performance an online non-credit course authorized by Alberta Machine Intelligence Institute and offered through Coursera.
  • Supervised Machine Learning: Classification an online non-credit course authorized by IBM and offered through Coursera
  • UnSupervised Machine Learning: Classification an online non-credit course authorized by IBM and offered through Coursera.
  • Building AI Powered Chatbots Without Programming an online non-credit course authorized by IBM and offered through Coursera.

AROUND 30 COURSES WITH CERTIFICATION AND MORE THAN 20 FACULTY DEVELOPMENT PROGRAMS.

Area of Interest

  • BlockChain
  • Cyber Forensics and Information Security
  • Artificial Intelligence
  • Machine Learning
  • Internet of Things, Smart Cities