Mihir Parekh | Machine Learning | Best Researcher Award

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Mr. Mihir Parekh | Machine Learning | Best Researcher Award

Research Scholar at Nirma University, India

Mihir Parekh is a passionate and dynamic cybersecurity enthusiast with a strong foundation in computer science, data analytics, and secure system design. With a proven track record of combining machine learning, blockchain, and cybersecurity for impactful solutions, he brings a multidisciplinary approach to solving complex technological challenges. Mihir has demonstrated excellence in both academic and industrial settings, contributing to innovative research in secure systems and earning accolades through peer-reviewed publications.

Publication Profile 

Google Scholar

Educational Background 🎓

  • M.Tech in Computer Science and Engineering (Cyber Security)
    Nirma University, Ahmedabad
    08/2022 – 06/2024 | CGPA: 9.21
    Focus: Cybersecurity, Blockchain, Data Analysis, Machine Learning

  • Bachelor of Engineering in Information Technology
    G.H. Patel College of Engineering and Technology, Vallabh Vidyanagar
    07/2018 – 05/2022 | CGPA: 8.22

Professional Experience 💼

  • Data Analyst
    Contrado Imaging India Pvt. Ltd., Ahmedabad
    06/2023 – 10/2023

    • Performed data cleaning and preprocessing using Python.

    • Developed SQL queries to fetch and analyze data.

    • Used Kibana and Elasticsearch for data visualization.

  • Business Process Analyst
    Kevit Technologies, Rajkot
    12/2021 – 07/2022

    • Designed chatbot workflows and managed client-specific SRS and change requests.

    • Handled software testing, project planning, and requirement gathering for custom chatbot solutions.

Research Interests 🔬

  • Cybersecurity and Digital Forensics

  • Blockchain Applications and Cryptographic Protocols

  • Machine Learning and Deep Learning

  • Federated Learning & Secure Data Sharing

  • Anomaly Detection and Fraud Prevention

  • Secure Industrial IoT Systems

Awards and Honors🏆✨

  • 🏆 Published Journal Paper:
    Blockchain Forensics to Prevent Cryptocurrency Scams
    Computers & Electrical Engineering (Impact Factor: 5.5)

  • 🏆 Conference Presentation:
    Federated Learning-based Secure Data Dissemination Framework for IIoT Systems
    IEEE ICBDS 2024

  • 🏆 Journal Publication:
    Decentralized Data-Driven Analytical Framework for Ship Fuel Oil Consumption
    Ain Shams Engineering Journal

  • 🎖️ Infineon Hackathon Finalist – AES-128 Cryptanalysis Challenge

Conclusion🌟

Mihir Parekh exemplifies the qualities of a modern-day technologist with a passion for innovation, research, and real-world problem solving. His academic rigor, hands-on experience in cybersecurity and AI, and commitment to continuous learning position him as a promising contributor to the field of secure intelligent systems. Eager to collaborate and make an impact, Mihir is actively seeking opportunities that align with his vision of building secure, intelligent, and efficient digital ecosystems.

Publications 📚

📘 Parekh, M., Jadav, N. K., Tanwar, S., Pau, G., Alqahtani, F., & Tolba, A. (2025). ANN and blockchain-orchestrated decentralized data-driven analytical framework for ship fuel oil consumption. Applied Ocean Research, 158, 104553.
🔗 https://doi.org/10.xxxxx/aor.2025.104553
📊 Keywords: Artificial Neural Networks, Blockchain, Maritime Fuel Analytics

📕 Parekh, M., Jadav, N. K., Pathak, L., Tanwar, S., & Yamsani, N. (2024). Federated Learning-based Secure Data Dissemination Framework for IIoT Systems Underlying 5G. In 2024 IEEE International Conference on Blockchain and Distributed Systems (pp. xx–xx). IEEE.
📡 Keywords: Federated Learning, 5G, IIoT, Cybersecurity
📍 Conference Paper

📄 Parekh, M. (2024). Decentralized Data-Driven Analytical Framework for Ship Fuel Oil Consumption. Institute of Technology.
🏛️ Institutional publication / Thesis
🌐 Focus: Data Analytics, Maritime Efficiency

Sushil Kumar | Machine Learning | Best Researcher Award

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Dr. Sushil Kumar | Machine Learning | Best Researcher Award

Assistant Professor at Central University of Haryana, India

Dr. Sushil Kumar is an Assistant Professor in the Department of Computer Science and Engineering at the Central University of Haryana, having joined on December 2, 2022. With a rich experience of 19 years in teaching, he specializes in Information Retrieval, Machine Learning, and Distributed Computing. Dr. Kumar holds a B.Tech, M.Tech, and Ph.D. in Computer Science and Engineering. He has published 7 papers in international journals and 1 book chapter, and has guided 16 Master’s students in their research. He has actively participated in 25 seminars and conferences, and organized 5 academic events. In addition, he has been recognized with the Youth Red Cross Award from the Honorable Governor of Haryana for 2016-17 and 2019-20. Currently, he also serves as the NBA Co-ordinator and NAAC Co-ordinator at the university.

Publication Profile : 

Google Scholar

Education 🎓

Dr. Sushil Kumar holds a B.Tech, M.Tech, and Ph.D. in Computer Science and Engineering, equipping him with a solid foundation in the field of technology and research.

Professional Experience💼

Assistant Professor at Central University of Haryana since 02-12-2022
With 19 years of teaching experience, Dr. Sushil Kumar has been dedicated to nurturing young minds in the area of computer science. His expertise in Information Retrieval, Machine Learning, and Distributed Computing has shaped his teaching methodology. While his focus remains on academia, he has not been involved in industry work yet. He has also taken up additional responsibilities as NBA Co-ordinator and NAAC Co-ordinator, ensuring quality assurance and accreditation standards in the department.

Research Interests 🔬

🔍 Information Retrieval
🤖 Machine Learning
🌐 Distributed Computing

Dr. Sushil Kumar’s research interests are focused on the areas of Information Retrieval, where he aims to improve search and data retrieval systems, Machine Learning, and the development of efficient algorithms for Distributed Computing systems.

Publications Top Notes 📚

  1. Kumar, S., Aggarwal, M., Khullar, V., Goyal, N., Singh, A., & Tolba, A. (2023). Pre-Trained Deep Neural Network-Based Features Selection Supported Machine Learning for Rice Leaf Disease Classification. Agriculture, 13(5), 23.
  2. Kumar, S., & Bhatia, K. K. (2020). Semantic similarity and text summarization-based novelty detection. SN Applied Sciences, 2(3), 332.
  3. Kumar, S., & Chauhan, N. (2012). A context model for focused web search. International Journal of Computer Technology, 2(3).
  4. Gupta, C., Khullar, V., Goyal, N., Saini, K., Baniwal, R., Kumar, S., & Rastogi, R. (2023). Cross-Silo, Privacy-Preserving, and Lightweight Federated Multimodal System for the Identification of Major Depressive Disorder Using Audio and Electroencephalogram. Diagnostics, 14(1), 43.
  5. Kumar, S., & Bhatia, K. K. (2019). Clustering-based approach for novelty detection in text documents. Asian Journal of Computer Science and Technology, 8(2), 116-121.
  6. Dasari, K., Srikanth, V., Veramallu, B., Kumar, S. S., & Srinivasulu, K. (2014). A novelty approach of symmetric encryption algorithm. Proceedings of the International Conference on Information Communication and Embedded Systems (ICICES).
  7. Kumar, S., & Anand, S. (2006). Implementing Shared Data Services (SDS): A Proposed Approach. 2006 IEEE International Conference on Services Computing (SCC’06), 365-372.
  8. Singh, S., Kundra, H., Kundra, S., Pratima, P. V., Devi, M. V. A., Kumar, S., & Hassan, M. (2024). Optimal trained ensemble of classification model for satellite image classification. Multimedia Tools and Applications, 1-22.
  9. Kumar, S., & Bhatia, K. K. (2018). Document-to-Sentence Level Technique for Novelty Detection. In Speech and Language Processing for Human-Machine Communications: Proceedings (pp. xx-xx).
  10. Chawla, M., Panda, S. N., Khullar, V., Kumar, S., & Bhattacharjee, S. B. (2024). A lightweight and privacy-preserved federated learning ecosystem for analyzing verbal communication emotions in identical and non-identical databases. Measurement: Sensors, 34, 101268.
  11. Kumar, S. S. (2023). System Oriented Social Scrutinizer: Centered Upon Mutual Profile Erudition. International Journal on Recent and Innovation Trends in Computing and Communication, 11(9), 2007–2017.
  12. Kumar, S. (2021). Design of novelty detection techniques for optimized search engine results. JC Bose University.
  13. Ishuka, S. K., & Bhatia, K. K. (2019). A Novel Approach for Novelty Detection Using Extractive Text Summarization. Journal of Emerging Technologies and Innovative Research, 6(6), 141-154.
  14. Pooja, K. K. B., & Kumar, S. (2019). Hashing and Clustering Based Novelty Detection. SSRG International Journal of Computer Science and Engineering, 6(6), 1-9.
  15. Kumar, S., & Bhatia, K. K. (2019). Clustering Based Approach for Novelty Detection in Text Documents. Asian Journal of Computer Science and Technology, 8(2), 121-126.