Dr. Dinesh Elayaperumal | Robotics Control | Best Researcher Award

AI Research Software Engineer at Humax Mobility Co. Ltd, South Korea

Dr. Dinesh Elayaperumal is an AI researcher and computer vision software engineer, currently serving as Manager in the AI Research (Computer Vision) division at Humax Mobility, South Korea. He earned his Ph.D. in Electronic and Information Engineering from Kunsan National University, specializing in deep learning-based object detection, segmentation, and multi-robot tracking systems. With expertise in 3D data annotation, Docker-based deployment, and ML frameworks such as TensorFlow, PyTorch, and OpenCV, Dr. Elayaperumal brings a robust mix of research and practical implementation skills. His prior academic work also includes medical image analysis for Alzheimer’s detection using machine learning techniques. He is a recipient of the prestigious NRF Korea Doctoral Scholarship.

Professional Profile

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award

Dr. Dinesh Elayaperumal is a cutting-edge AI researcher whose profile demonstrates a robust blend of academic depth, technical innovation, and practical deployment of intelligent systems in the fields of computer vision, machine learning, and robotics. With a Ph.D. from Kunsan National University (South Korea), Dr. Dinesh’s research has focused on unified segmentation-based deep tracking systems, contributing substantially to intelligent video surveillance and swarm robotics coordination.

🎓 Education

• 📘 Ph.D. in Electronic and Information Engineering
  Kunsan National University, South Korea (Sep 2017 – Feb 2024)
  🧠 Thesis: Unified Segmentation-Based Deep Tracking for Intelligent Video Surveillance
  📊 CGPA: 4.2/4.5

• 💡 M.E. in Computer Science and Engineering
  Karpagam University, Tamil Nadu, India (Jun 2011 – May 2013)
  🧪 Thesis: Classification of Alzheimer’s Disease Using FMRI, PET & SPECT
  📊 CGPA: 8.67/10.0

• 🖥️ B.E. in Computer Science and Engineering
  Anna University, Tamil Nadu, India (Aug 2007 – May 2011)
  🕒 Thesis: Synchronizing Clocks in Ad-Hoc Networks
  📊 CGPA: 7.64/10.0

💼 Work Experience

• 🧠 AI Research (Computer Vision) Software Engineer – Manager
  Humax Mobility – PARCS Division, Gyeonggi-do, South Korea

  • Leading the design and deployment of deep learning models for object tracking and segmentation.

  • Focused on smart mobility and intelligent surveillance systems.

• 👨‍🏫 Assistant Professor – Computer Science and Engineering
  Narasus’s Sarathy Institute of Technology, Tamil Nadu, India

  • Taught core computer science subjects and mentored students in research projects related to AI and ML.

🏆 Achievements & Honors

• 🎓 Doctoral Fellowship
  Awarded by National Research Foundation (NRF) of Korea

• 🏅 Best Leadership Award
  NSS Leadership Training Programme
  Organized by the Directorate of School Education, Tamil Nadu, India

📜 Certifications & Trainings

• 🤖 Learning Autonomous Driving Behaviors with LLMs & RL – Analytics Vidhya

• 🐳 Containerization Using Docker – Coursera

• 🔰 Docker for Beginners – Coursera

• 💡 Supervised ML & Regression – DeepLearning.AI & Stanford University

• 🧠 Neural Networks and Deep Learning – DeepLearning.AI

• 🧬 Machine Learning with Python – IBM

• 🔍 Deep Learning & ML Introduction – Kaggle

• 🐍 Complete Python Course – Udemy

📚 Academic Projects

📹 Project I – Intelligent Video Surveillance for Anomaly Detection (Ph.D.)

• 🔍 Specializes in segmentation-based deep tracking using CNNs and correlation filters

• 🤖 Designed and simulated swarm robotic behavior using control laws like SMC, adaptive control, and backstepping

• 💡 Implemented feature fusion using VGG16/19, ResNet50, MDNet

• ✅ Benchmarked performance on industry datasets

🧠 Project II – Alzheimer’s Disease Classification Using ML (M.E.)

• 📈 Used FMRI, PET, and SPECT datasets for medical image classification

• 🧮 Applied NMF and SVM to accurately distinguish AD patients from healthy individuals

🛠️ Skills

Languages: Tamil (Native) 🗣️ | English (Professional) 🇬🇧 | Korean (TOPIK Level-1) 🇰🇷
Programming: Python 🐍 | C/C++ 💻 | Java ☕ | C#
ML Frameworks: TensorFlow ⚙️ | PyTorch 🔥 | Keras 🤖 | Scikit-learn 📊 | OpenCV 👁️
Tools: Docker 🐳 | Git/GitHub 🔧 | PyCharm 💡 | MATLAB 📐 | ROS (Basic) 🤖
Data Annotation: 2D/3D Labeling | 3D Bounding Box (BB) | Oriented Bounding Box (OBB)
Soft Skills: Teamwork 🤝 | Problem Solving 🧠 | Fast Learner 🚀

📚 Top Noted Publications

Aberrance suppressed spatio-temporal correlation filters for visual object tracking

Cited : 55

Robust visual object tracking using context-based spatial variation via multi-feature fusion

Cited : 43

Learning spatial variance-key surrounding-aware tracking via multi-expert deep feature fusion

Cited : 22

Instinctive Classification of Alzheimer’s Disease using FMRI, PET and SPECT Images

Cited : 16

Visual object tracking using sparse context-aware spatio-temporal correlation filter

Cited : 11