Dinesh Elayaperumal | Robotics Control | Best Researcher Award

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.

๐ŸŽ“ Education

  • ๐Ÿ“˜ Ph.D. in Electronic and Information Engineering
    Kunsan National University, South Korea (Sep 2017 โ€“ Feb 2024)
    ๐Ÿง  Thesis: Unified Segmentation-Based Deep Tracking for Intelligent Video Surveillance
    ๐Ÿ“Š CGPA: 4.2/4.5

  • ๐Ÿ’ก M.E. in Computer Science and Engineering
    Karpagam University, Tamil Nadu, India (Jun 2011 โ€“ May 2013)
    ๐Ÿงช Thesis: Classification of Alzheimerโ€™s Disease Using FMRI, PET & SPECT
    ๐Ÿ“Š CGPA: 8.67/10.0

  • ๐Ÿ–ฅ๏ธ B.E. in Computer Science and Engineering
    Anna University, Tamil Nadu, India (Aug 2007 โ€“ May 2011)
    ๐Ÿ•’ Thesis: Synchronizing Clocks in Ad-Hoc Networks
    ๐Ÿ“Š CGPA: 7.64/10.0

๐Ÿ’ผ Work Experience

  • ๐Ÿง  AI Research (Computer Vision) Software Engineer โ€“ Manager
    Humax Mobility โ€“ 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.

  • ๐Ÿ‘จโ€๐Ÿซ Assistant Professor โ€“ Computer Science and Engineering
    Narasusโ€™s Sarathy Institute of Technology, Tamil Nadu, India

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

๐Ÿ† Achievements & Honors

  • ๐ŸŽ“ Doctoral Fellowship
    Awarded by National Research Foundation (NRF) of Korea

  • ๐Ÿ… Best Leadership Award
    NSS Leadership Training Programme
    Organized by the Directorate of School Education, Tamil Nadu, India

๐Ÿ“œ Certifications & Trainings

  • ๐Ÿค– Learning Autonomous Driving Behaviors with LLMs & RL โ€“ Analytics Vidhya

  • ๐Ÿณ Containerization Using Docker โ€“ Coursera

  • ๐Ÿ”ฐ Docker for Beginners โ€“ Coursera

  • ๐Ÿ’ก Supervised ML & Regression โ€“ DeepLearning.AI & Stanford University

  • ๐Ÿง  Neural Networks and Deep Learning โ€“ DeepLearning.AI

  • ๐Ÿงฌ Machine Learning with Python โ€“ IBM

  • ๐Ÿ” Deep Learning & ML Introduction โ€“ Kaggle

  • ๐Ÿ Complete Python Course โ€“ Udemy

๐Ÿ“š Academic Projects

๐Ÿ“น Project I โ€“ Intelligent Video Surveillance for Anomaly Detection (Ph.D.)

  • ๐Ÿ” Specializes in segmentation-based deep tracking using CNNs and correlation filters

  • ๐Ÿค– Designed and simulated swarm robotic behavior using control laws like SMC, adaptive control, and backstepping

  • ๐Ÿ’ก Implemented feature fusion using VGG16/19, ResNet50, MDNet

  • โœ… Benchmarked performance on industry datasets

๐Ÿง  Project II โ€“ Alzheimerโ€™s Disease Classification Using ML (M.E.)

  • ๐Ÿ“ˆ Used FMRI, PET, and SPECT datasets for medical image classification

  • ๐Ÿงฎ Applied NMF and SVM to accurately distinguish AD patients from healthy individuals

๐Ÿ› ๏ธ Skills

Languages: Tamil (Native) ๐Ÿ—ฃ๏ธ | English (Professional) ๐Ÿ‡ฌ๐Ÿ‡ง | Korean (TOPIK Level-1) ๐Ÿ‡ฐ๐Ÿ‡ท
Programming: Python ๐Ÿ | C/C++ ๐Ÿ’ป | Java โ˜• | C#
ML Frameworks: TensorFlow โš™๏ธ | PyTorch ๐Ÿ”ฅ | Keras ๐Ÿค– | Scikit-learn ๐Ÿ“Š | OpenCV ๐Ÿ‘๏ธ
Tools: Docker ๐Ÿณ | Git/GitHub ๐Ÿ”ง | PyCharm ๐Ÿ’ก | MATLAB ๐Ÿ“ | ROS (Basic) ๐Ÿค–
Data Annotation: 2D/3D Labeling | 3D Bounding Box (BB) | Oriented Bounding Box (OBB)
Soft Skills: Teamwork ๐Ÿค | Problem Solving ๐Ÿง  | Fast Learner ๐Ÿš€

๐Ÿ“š 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 Alzheimerโ€™s Disease using FMRI, PET and SPECT Images

Cited : 16

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

Cited : 11

Zhangbao Xu | nonlinear control | Best Researcher Award

Assoc. Prof. Dr. Zhangbao Xu | nonlinear control | Best Researcher Award

Associate Professor at Fuyang Normal University, China

Zhangbao Xu is an Associate Professor at Fuyang Normal University, China, specializing in high-accuracy servo control, adaptive control, and intelligent mechatronic systems. He earned his Ph.D. in Mechanical Engineering from Nanjing University of Science and Technology in 2017 and has over 20 publications in prestigious journals like IEEE Transactions on Industrial Electronics and IEEE/ASME Transactions on Mechatronics. He has served as a guest editor for Electronics and Actuators. His research integrates robust and intelligent control strategies for mechatronic applications.

Publication Profile

scopus

Education ๐ŸŽ“

Ph.D. in Mechanical Engineering (2017) โ€“ Nanjing University of Science and Technology, China B.S. in Mechanical Engineering and Automation (2012) โ€“ Huaqiao University, Xiamen, China

Experience ๐Ÿ’ผ

Associate Professor (2023โ€“Present) โ€“ School of Computer and Information Engineering, Fuyang Normal University, China Postdoctoral Researcher (2021โ€“2023) โ€“ Nanjing University of Aeronautics and Astronautics, China Lecturer (2017โ€“2023) โ€“ School of Mechanical Engineering, Anhui University of Technology, China

Awards and Honors ๐Ÿ†

Guest Editor โ€“ Electronics, Actuators Published in Top Journals โ€“ IEEE Transactions on Industrial Electronics, IEEE Transactions on Automation Science and Engineering Recognition for Research Contributions โ€“ High-impact publications in mechatronics, control systems, and intelligent automation

Research Focus ๐Ÿ”ฌ

Zhangbao Xu’s research centers on high-accuracy servo control, adaptive control, robust control, and intelligent control for mechatronic systems, emphasizing real-time applications, precision engineering, and industrial automation. ๐Ÿš€

Publications ๐Ÿ“–

๐Ÿ”น Total Publications: 7+ in top-tier journals ๐Ÿ“š
๐Ÿ”น Total Citations: 54+ (as per listed articles) ๐Ÿ“ˆ
๐Ÿ”น Key Focus Areas: Adaptive control, prescribed performance control, robust servo systems โš™๏ธ

๐Ÿ“Œ Notable Papers & Impact

โœ… Barrier Lyapunov Function-Based Adaptive Output Feedback Prescribed Performance Controller for Hydraulic Systems (2023) โ€“ 38 citations
โœ… Observer-Based Prescribed Performance Adaptive Neural Output Feedback Control (2023) โ€“ 15 citations
โœ… Adaptive Prescribed Performance Output Feedback Control for Full-State-Constrained DC Motors (2024) โ€“ 1 citation
โœ… RISE-Based Asymptotic Adaptive Prescribed Performance Control for DC Motors (2025) โ€“ Newly published

His research spans industrial automation, nonlinear system control, and mechatronics, with strong contributions in IEEE Transactions and European Journal of Control. ๐Ÿš€

Conclusion ๐ŸŽฏ

Zhangbao Xu is a highly promising candidate for the Best Researcher Award due to his exceptional research in control systems, strong academic foundation, and significant contributions through publications and editorial roles. To strengthen his candidacy further, expanding his international network, increasing research citations, and fostering industry ties would further elevate his influence and recognition.

Hugo Bildstein | Sensor-based Control | Best Researcher Award

Dr. Hugo Bildstein | Sensor-based Control | Best Researcher Award

Dr. LAAS-CNRS, France

Hugo Bildstein is a PhD candidate and Temporary Teaching and Research Assistant at the University of Toulouse 3 – Paul Sabatier, affiliated with the RAP team at LAAS-CNRS. His academic background includes a Master’s degree in Robotics from Toulouse and a previous engineering degree in Mechatronics from ENS Rennes. Hugo’s research focuses on visual predictive control for mobile manipulators, with notable publications in leading journals and conferences, including Robotics and Autonomous Systems (RAS) and IEEE/ASME AIM. His work explores strategies for improving visibility, manipulability, and stability in robotic systems.

Professional Profiles:

scopus

Academic Background ๐ŸŽ“:

Hugo Bildstein is currently a Temporary Teaching and Research Assistant at the University of Toulouse 3 – Paul Sabatier, working within the RAP team at LAAS-CNRS, Toulouse. His academic journey includes a PhD at the same university from 2020-2024, following a Masterโ€™s degree in Robotics: Decision and Control (RODECO) at the University of Toulouse 3 – Paul Sabatier. Hugo also holds a Masterโ€™s degree in Mechatronics from ENS Rennes and ranked 11th in the Agrรฉgation in Industrial Engineering Sciences, Electrical Engineering option in 2019.

Research Activities and ย ๐Ÿ“š:

Hugo’s research focuses on enhancing visual predictive control for mobile manipulators. His work includes:โ€œVisual Predictive Control for Mobile Manipulators: Visibility, Manipulability, and Stabilityโ€ – to be published in Robotics and Autonomous Systems (RAS) in 2024.โ€œEnhanced Visual Predictive Control Scheme for Mobile Manipulatorsโ€ – presented at the 2023 European Conference on Mobile Robots (ECMR) in Coimbra, Portugal.โ€œMulti-camera Visual Predictive Control Strategy for Mobile Manipulatorsโ€ – showcased at the 2023 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM) in Seattle, USA.โ€œVisual Predictive Control Strategy for Mobile Manipulatorsโ€ – discussed at the 2022 European Control Conference (ECC) in London, United Kingdom.

Research Analysis for Hugo Bildstein

Strengths for the Award:

  1. Innovative Contributions: Hugo Bildstein’s research focuses on cutting-edge topics in robotics, particularly visual predictive control for mobile manipulators. His work on enhancing control schemes through multi-camera strategies and visual feedback systems is highly relevant and forward-thinking in the field of robotics and autonomous systems.
  2. Diverse Research Outputs: Bildstein has published several papers in prestigious journals and conferences, demonstrating a consistent and impactful research output. His papers, such as those presented at the European Conference on Mobile Robots (ECMR) and the IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), highlight significant contributions to the field.
  3. Academic Excellence: His strong academic background, including a PhD in Robotics and a Masterโ€™s degree in Robotics and Control, coupled with high rankings in competitive exams like the Agrรฉgation in Industrial Engineering Sciences, underscores his deep expertise and commitment to the field.
  4. Teaching and Research Experience: As a Teaching and Research Assistant at the University of Toulouse 3 – Paul Sabatier, Bildstein not only engages in advanced research but also contributes to academic teaching, showcasing his ability to bridge research and education effectively.

Areas for Improvement:

  1. Citation Impact: While Bildstein has several publications, some of his recent papers have yet to accumulate significant citations. Increasing the visibility and impact of his work through broader dissemination and collaboration could enhance his academic profile.
  2. Interdisciplinary Applications: Expanding research to explore interdisciplinary applications of his work could provide broader impact and open new avenues for practical implementation of his findings.
  3. Research Collaboration: Engaging in collaborative research with industry partners or other academic institutions could provide additional resources and perspectives, potentially leading to more comprehensive studies and real-world applications.

Conclusion:

Hugo Bildstein is a promising candidate for the Best Researcher Award due to his innovative contributions to the field of robotics, particularly in visual predictive control for mobile manipulators. His strong academic background, diverse research outputs, and active role in teaching and research highlight his potential and dedication. Addressing areas such as citation impact and interdisciplinary applications could further enhance his standing in the research community.

โœ๏ธPublications Top Note :

1. Enhanced Visual Predictive Control Scheme for Mobile Manipulators

Authors: Hugo Bildstein, A. Durand-Petiteville, V. Cadenat

Citations: 0

2. Multi-camera Visual Predictive Control Strategy for Mobile Manipulators

Authors: Hugo Bildstein, A. Durand-Petiteville, V. Cadenat

3. Visual Predictive Control Strategy for Mobile Manipulators

Authors: Hugo Bildstein, A. Durand-Petiteville
Citations: 2
Access: Open access