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.

Prof. Dr. Xingguo Li | Network Security | Best Researcher Award

Prof. Dr. Xingguo Li | Network Security | Best Researcher Award 

Prof. Dr. Xingguo Li, Sichuan University, China

Xingguo Li is a Senior Engineer at Sichuan University, where he is affiliated with the College of Computer Science. He earned his M.S. degree from the School of Computer Science and Engineering at the University of Electronic and Technology of China (UESTC) in Chengdu in 2004 and later completed his Ph.D. in Computer Science at Sichuan University. With a strong foundation in computer science, Dr. Li’s research interests focus on network and information security, big data, and cloud computing. Throughout his career, he has made significant contributions to advancing technologies in these fields, particularly in securing networks and leveraging the power of big data for innovative solutions. His expertise continues to shape developments in these critical areas of computing.

Professional Profile:

SCOPUS

🏆 Summary of Suitability for Best Researcher Award: Xingguo Li

Xingguo Li, a Senior Engineer at Sichuan University, is an exceptionally qualified candidate for the Best Researcher Award. With extensive academic and professional experience in the fields of network and information security, big data, and cloud computing, Dr. Li has made significant contributions to both academia and industry, solidifying his reputation as a leader in these transformative fields.

Education 🎓

  • Ph.D. in Computer Science
    Sichuan University, P.R. China
    Graduated: [Year not specified]

  • M.S. in Computer Science and Engineering
    University of Electronic and Technology of China (UESTC), Chengdu, China
    Graduated: 2004

Work Experience 💼

  • Senior Engineer
    College of Computer Science, Sichuan University, China
    Current Position: [Since unspecified year]

    • Focuses on research and development in the fields of network and information security, big data, and cloud computing.

  • [Other previous roles not mentioned in detail]

Research Interests 🔍

  • Network and Information Security

  • Big Data

  • Cloud Computing

Achievements 🏆

  • Extensive work in network security and cloud computing.

  • Significant contributions to the big data field with advanced research and developments.

  • Published multiple influential research papers and articles in high-impact journals.

Awards and Honors 🏅

  • Outstanding Researcher/Engineer

  • Contribution to Network Security Research

Publication Top Notes:

Network information security protection method based on additive Gaussian noise and mutual information neural network in cloud computing background

 

Mr. Abhijeet Thakare | Network Security | Best Researcher Award

Mr. Abhijeet Thakare | Network Security | Best Researcher Award 

Mr. Abhijeet Thakare, Industrial Engineering, South Korea

Abhijeet Thakare is an experienced AI and computer vision engineer specializing in the design and development of AI-powered applications. With expertise in NVIDIA solutions, Deep Learning, Machine Learning, and algorithm development, he has successfully implemented AI-based computer vision solutions for real-time analytics, public transportation monitoring, and logistics automation. Currently based in Seoul, South Korea, Abhijeet has led AI teams in projects for Rapid KL Bus Malaysia, NUS Singapore, and CJ Logistics, developing advanced AI models for passenger monitoring, driver allocation optimization, and parcel detection. Proficient in tools like NVIDIA DeepStream, YOLOv8, TensorRT, and Kafka, he excels in AI-driven automation, real-time data processing, and edge computing solutions. With a strong research aptitude and problem-solving skills, Abhijeet continues to drive innovation in AI and computer vision applications.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award

Abhijeet Thakare demonstrates a strong background in AI-based research and development, particularly in the fields of computer vision, deep learning, and real-time analytics. His extensive experience in implementing NVIDIA DeepStream solutions, AI-powered automation, and reinforcement learning techniques for real-world applications reflects a high level of research innovation and technical expertise. His contributions to AI-driven public transportation analytics, logistics optimization, and robotic automation highlight his ability to translate research into impactful industrial applications. Additionally, his leadership in multiple AI projects, collaborations with industry

📚 Education

🎓 Bachelor’s & Master’s Degree (Details Not Provided)

  • Specialized in Artificial Intelligence (AI), Computer Vision, and Deep Learning
  • Focused on Algorithm/Protocol Designing and Model Testing

💼 Work Experience

🚍 CTO & Team Leader | Vision Engineer Debang, Seoul, South Korea

📅 Aug 2024 – Oct 2024
📌 Project: Rapid KL Bus Malaysia + Paymentinapp

  • Developed AI-based computer vision solutions for bus analytics and passenger monitoring
  • Implemented drowsiness detection, violence detection, smoke detection, seatbelt compliance, and phone usage tracking
  • Led real-time streaming and analytics using NVIDIA DeepStream SDK
  • Designed interactive monitoring interfaces for bus safety & passenger management
  • The solution was successfully demonstrated and is under review for deployment

🗺️ Project Manager & AI Team Leader | Vision Engineer Debang, Seoul, South Korea

📅 July 2024 – Aug 2024
📌 Project: Rapid KL Malaysia + Paymentinapp

  • Implemented AI-based people tracking & heatmap generation for Singapore Conferences & Bus Analysis
  • Developed real-time monitoring for zone-based tracking and crowd management
  • Integrated DeepStream SDK to enhance visualization of occupancy heatmaps

🚎 Project Manager & AI Team Leader | Vision Engineer Debang, Seoul, South Korea

📅 Aug 2024 – Ongoing
📌 Project: Rapid KL Malaysia + NUS Singapore + Paymentinapp

  • Implemented Reinforcement Learning-based real-time analytics for driver allocation & bus optimization
  • Integrated Kafka, DeepStream, and FastAPI for backend data management & real-time insights
  • Developed AI-powered driver scheduling to reduce waiting times & improve efficiency

📦 AI Team Leader | Vision Engineer Debang, Seoul, South Korea

📅 June 2024 – Sep 2024
📌 Project: Paymentinapp + CJ Logistics

  • Led AI-based parcel management using YOLOv8 & DeepStream SDK
  • Designed real-time parcel detection systems on NVIDIA Jetson devices
  • Integrated segmentation models for precise parcel dimension estimation
  • The project was successfully demonstrated and received positive feedback from CJ Logistics

🏆 Achievements & Awards

🏅 Innovative AI Developer – Successfully led multiple AI-based projects in computer vision & deep learning
🚀 Pioneer in Real-time Analytics – Designed AI-powered public transport monitoring systems
📜 Recognized AI Team Leader – Delivered high-accuracy AI models for automated tracking & surveillance
📊 Expert in Deep Learning & NVIDIA Solutions – Implemented AI-powered automation for multiple industries

Publication Top Notes:

Secure and efficient authentication scheme in iot environments