Ms. Raghi K R | Federated Learning | Research Excellence Award

Ms. Raghi K R | Federated Learning | Research Excellence Award 

Ms. Raghi K R | Federated Learning | Sathyabama Institute of Science and Technology | India

Mrs. Raghi K.R. is a dedicated computer science educator and researcher with strong experience in both teaching and applied research. She holds a B.E. in Computer Science and Engineering (Anna University), an M.E. in Computer Science and Engineering (PSN Engineering College / Anna University), and has submitted her Ph.D. synopsis in Computer Science and Engineering at College of Engineering, Guindy, Anna University. Her professional journey includes roles as Assistant Professor and Teaching Fellow across several institutions: PSN Engineering College (CSE), College of Engineering Guindy, and currently at St. Joseph’s College of Engineering, Chennai giving her over a decade of teaching experience, spanning undergraduate and postgraduate courses. Her research interests lie in Artificial Intelligence, Deep Learning, Machine Learning, Cloud Security, and Web Mining. She possesses robust technical skills including programming in Python, Java, C, C++, web technologies (HTML), and experience with simulation platforms such as NS2 and MATLAB, as well as familiarity with open-source operating systems. Through her career she has mentored and guided multiple innovative and funded projects — for example leading a seed-research project titled “StepSmart: Design and Development of an Affordable IoT and Deep Learning Based Footwear for Diabetic Health Monitoring,” and supervising award-winning student projects such as “Trash Triage: Trailblazing Waste Management with Real-Time Street Waste Monitoring” and “Identification of Fake Medicinal Raw Materials Using Machine Learning.” These recognitions reflect her commitment to practical, socially relevant research. Her academic repertoire includes teaching diverse subjects like Artificial Intelligence, Mobile Computing, Information Security, Web Programming, Soft Computing, Software Project Management, Cyber Security, Web Technology, and more. She has also supervised substantial academic work: a Ph.D. thesis on “Privacy-Preserving Deep NN Classification over Signature Cryptosystem in Cloud Environments,” a secure payment-scheme design in multihop networks, and semantic similarity computation for natural language. As a scholar and mentor, Mrs. Raghi combines strong theoretical foundations with hands-on applied research, striving to develop secure, intelligent, and socially impactful computing solutions. Her involvement in both education and research along with project funding, awards, and diverse technical competencies — positions her as a proactive and forward-looking professional in the fields of AI, cybersecurity, and data-driven intelligent systems, committed to nurturing student talent and contributing to technological advancement.

Professional Profiles: ORCID | Google Scholar 

Selected Publications

  1. Thomas, R. K. L., Sanjay, G. J., Pandeeswaran, C., & Raghi, K. R. (2024). Advanced CCTV Surveillance Anomaly Detection, Alert Generation and Crowd Management using Deep Learning Algorithm.

  2. Vethavikashini, A. M., Jamal, S. M., & Raghi, K. R. (2024). Huntington’s Disease Prediction Using Xception CNN.

  3. Devi, S. R., Geetha Priya, S., Sathi, G., Naveen Kumar, S., Dinesh, M., & Raghi, K. R. (2024). Design and Development of a Touch Free Smart Home Controlling System Based on Virtual Reality (VR) Technology.

  4. Raghi, K. R., Sudha, K., Sreeram, A. M., Steve Joshua, S. (2024). Software Development Automation Using Generative AI.

  5. Raghi, K. R. (2023). Privacy-Preserving Deep NN Classification over Signature Cryptosystem in Cloud Environments.

  6. Anitha, T., Sai Srihitha, G. R. P. Lakshmi Aiswarya, & Raghi, K. R. (2025). Predictive Modeling of Social Media Data Using Machine Learning Techniques.

  7. (As mentor) StepSmart: Design and Development of an Affordable IoT and Deep Learning Based Footwear for Diabetic Health Monitoring.

Assist. Prof. Dr. Nastooh Taheri Javan | Federated Learning | Best Researcher Award

Assist. Prof. Dr. Nastooh Taheri Javan | Federated Learning | Best Researcher Award

Assist. Prof. Dr. Nastooh Taheri Javan, IKIU, Iran

Dr. Nastooh Taheri Javan is an Assistant Professor in the Computer Engineering Department at Imam Khomeini International University (IKIU), Qazvin, Iran. He holds a Ph.D. and M.Sc. in Computer Networks and Architecture from Amirkabir University of Technology (Tehran Polytechnic), where he also completed a postdoctoral fellowship. His research focuses on wireless networks, network coding theory, IoT, mobile ad-hoc networks, network security, game theory, and machine learning. Dr. Taheri Javan is a Senior Member of IEEE (SMIEEE) and has over a decade of experience in academia and industry. He is the co-founder and CEO of BARBOD, a knowledge-based company specializing in hardware design and electronic product development, and formerly led SAMANE_FANAVARAN, a software solutions firm. His academic career includes teaching roles at multiple Iranian universities, and he actively serves as a reviewer and committee member in international journals and conferences. Dr. Taheri Javan is recognized for his interdisciplinary collaborations and leadership in IT R&D.

Professional Profile:

GOOGLE SCHOLAR

ORCID

Summary of Suitability for Best Researcher Award

Dr. Nastooh Taheri Javan, Ph.D., is an accomplished researcher and academic leader with a robust track record in wireless networks, IoT, network coding theory, and applied machine learning. Currently serving as an Assistant Professor in the Computer Engineering Department at Imam Khomeini International University (IKIU), Iran, Dr. Taheri Javan exemplifies the qualities of a distinguished researcher through his academic, industrial, and entrepreneurial contributions.

🎓 Education

  • 📚 Postdoctoral Fellow in Computer Networks Engineering
    Amirkabir University of Technology, Tehran, Iran (2018 – 2020)

  • 🎓 Ph.D. in Computer Networks Engineering
    Amirkabir University of Technology, Tehran, Iran (2011 – 2017)

  • 🧠 M.Sc. in Computer Architecture Engineering
    Amirkabir University of Technology, Tehran, Iran (2004 – 2007)

  • 💻 B.Sc. in Computer Software Engineering
    Iran Azad University, Mahshahr, Iran (1999 – 2003)

💼 Work Experience

  • 👨‍🏫 Assistant Professor
    Imam Khomeini International University, Qazvin, Iran (2020 – Present)

  • 🧑‍🏫 Faculty Member
    Iran Azad University, Tehran, Iran (2009 – 2011)

  • 📚 Lecturer
    University of Applied Science and Technology, Tehran, Iran (2004 – Present)

  • 👨‍🏫 Lecturer
    Iran Azad University, Tehran, Iran (2008 – Present)

  • 👨‍🏫 Lecturer
    Amirkabir University of Technology, Tehran, Iran (2013 – Present)

  • 🧑‍💼 CEO & Co-FounderBARBOD
    A knowledge-based hardware & electronics company (Present)

  • 🧑‍💼 Former CEOSAMANE_FANAVARAN
    Focused on software solutions

🏆 Achievements & Honors

  • 🌐 Over 10 years of experience in R&D leadership and technical problem-solving in the IT industry

  • 🤝 Active collaborator across various computer science disciplines

  • 📡 Strong contributions to wireless networks, network coding, and IoT technologies

  • 🧠 Founder of multiple tech companies, with expertise in both hardware and software innovation

  • ✍️ Manuscript Reviewer for:

    • Soft Computing Journal

    • Tabriz Journal of Electrical Engineering

  • 🧾 Scientific & Program Committee Member for:

    • 7th Intl. Conference on Internet of Things (2023)

    • 6th Intl. Conference on Smart Cities & IoT (2022)

    • 5th Intl. Conference on Web Research (2019)

🥇 Awards & Honors

  • 🎖️ Senior Member of IEEE (Since 2020)
    Recognized for outstanding contributions to the field of Computer Networks

Publication Top Notes:

An energy-efficient decentralized federated learning framework for mobile-IoT networks

Enhancing Malicious Code Detection With Boosted N-Gram Analysis and Efficient Feature Selection

To Code or Not to Code: When and How to Use Network Coding in Energy Harvesting Wireless Multi-Hop Networks

Consensus tracking for a class of fractional-order non-linear multi-agent systems via an adaptive dynamic surface controller

Q-learning-based algorithms for dynamic transmission control in IoT equipment

ENCODE an Efficient Framework for using Network Coding in Multi-hop Wireless Networks

Adaptive Channel Hopping for IEEE 802.15.4 TSCH-Based Networks: A Dynamic Bernoulli Bandit Approach