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.

Mr. Omer Tariq | Artificial Intelligence Award | Best Researcher Award

Mr. Omer Tariq | Artificial Intelligence Award | Best Researcher Award 

Mr. Omer Tariq, Korea Advanced Institute of Science and Technology, KAIST, South Korea

Omer Tariq is a Ph.D. candidate at the Korea Advanced Institute of Science and Technology (KAIST), specializing in efficient and privacy-preserving deep learning for AIoT and autonomous systems. With a strong foundation in digital ASIC design, embedded systems, and hardware design, Omer has over seven years of experience in developing and deploying innovative machine learning solutions using TensorFlow, TensorRT, and PyTorch. His research includes advanced robotics software systems, autonomous navigation, and state-of-the-art motion planning algorithms. He has led teams in high-performance SoC/RTL design and verification at the National Electronics Complex, Pakistan, and contributed to satellite imaging systems at SUPARCO. Omer holds a BSc in Electrical Engineering from the University of Engineering and Technology, Taxila, and has published several papers in prominent journals. His technical skills are complemented by a range of certifications in machine learning, data science, and digital signal processing.

Professional Profile:

Summary of Suitability for Best Researcher Award

Omer Tariq is a Ph.D. candidate specializing in efficient and privacy-preserving deep learning for AIoT and Autonomous Systems. His work is highly relevant to current technological advancements and addresses significant challenges in machine learning, robotics, and autonomous systems. His research includes:

Education

Korea Advanced Institute of Science and Technology (KAIST)
Doctor of Philosophy (Ph.D.) in Computer Science
May 2021 – July 2025

  • Majors: Machine Learning & AI
  • CGPA: 3.74/4.3
  • Coursework: Programming for AI, Introduction to Artificial Intelligence, Design and Analysis of Algorithms, Intelligent Robotics, Human-Computer Interaction, Artificial Intelligence and Machine Learning, Technical Writing for Computer Science, Advanced Machine Learning, IoT Datascience

University of Engineering and Technology (UET), Taxila
Bachelor of Science in Electrical Engineering
Nov 2010 – July 2014

  • CGPA: 3.25/4.0
  • Thesis: Computer Vision-Assisted Object Detection and Control Framework for 3-DoF Robotic Arm
  • Area: Microelectronics, Control Systems, and Advanced Computer Architecture

Work Experience

Department of Industrial & Systems Engineering (ISysE), KAIST
Research Assistant
Nov. 2023 – March 2024

  • Designed and developed the electronics and power management module for the DAIM-Autonomous Mobile Robot, enhancing operational efficiency and reliability.
  • Engineered advanced robotics software systems for autonomous navigation and task execution.
  • Implemented state-of-the-art robot motion planning, mapping, and localization (SLAM) algorithms to improve real-time navigation accuracy.

National Electronics Complex, Pakistan (NECOP)
Engineering Manager & Team Lead
Apr. 2019 – Sep. 2022

  • Led verification and validation of high-performance SoC/RTL designs, ensuring system performance and reliability.
  • Spearheaded RTL development and optimization for high-performance IC designs, including logic synthesis, DFT, scan chain insertion, formal verification, and static timing analysis.
  • Managed the use of Synopsys and Cadence EDA tools for front-end and back-end digital IC design processes.

National Space Agency, Pakistan (SUPARCO)
Assistant Manager
Oct. 2014 – Apr. 2019

  • Designed and developed satellite imaging payload systems for national satellite missions.
  • Engineered high-speed, multi-layer PCB designs and conducted signal/power integrity simulations for satellite systems.
  • Developed embedded systems for the Satellite Ku-Band Positioning Unit, enhancing communication and positioning capabilities.

Publication top Notes:

2D Particle Filter Accelerator for Mobile Robot Indoor Localization and Pose Estimation

TabCLR: Contrastive Learning Representation of Tabular Data Classification for Indoor-Outdoor Detection

Compact Walsh–Hadamard Transform-Driven S-Box Design for ASIC Implementations

DeepIOD: Towards A Context-Aware Indoor–Outdoor Detection Framework Using Smartphone Sensors