Dr. Shuaa Alharbi | Deep learning Awards | Women Researcher Award

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Dr. Shuaa Alharbi | Deep learning Awards | Women Researcher Award 

Dr. Shuaa Alharbi, Qassim University, Saudi Arabia

Shuaa S. Alharbi is an Assistant Professor at the College of Computer Science, Qassim University, Saudi Arabia. She holds a B.Sc. and M.Sc. in Computer Science from Qassim University, and a Ph.D. in Computer Science from Durham University, UK. Her research expertise lies in machine learning, deep learning, and image processing, particularly in the biomedical domain. She specializes in developing novel deep learning architectures and techniques for analyzing medical images to enhance diagnostic accuracy. Her work focuses on curvilinear structure extraction and bioimage informatics, and she has published impactful research in esteemed journals, including Signal, Image and Video Processing and Methods. Dr. Alharbi has also contributed extensively to academic committees, curriculum development, and postgraduate supervision, reflecting her dedication to education and research excellence.

Professional Profile:

ORCID

 Suitability for the Women Researcher Award

Dr. Shuaa S. Alharbi has demonstrated substantial contributions in computer science, with a focus on machine learning, image processing, and medical image analysis. Her research is interdisciplinary, addressing key challenges in the fields of bioimage informatics, medical diagnostics, and AI-based deep learning applications. These align with global priorities in health technology and AI-driven innovation.

🎓 Education

  • B.Sc. in Computer Science (2007)
    📍 Qassim University, Saudi Arabia
  • M.Sc. in Computer Science (2014)
    📍 Qassim University, Saudi Arabia
  • Ph.D. in Computer Science (2020)
    📍 Durham University, United Kingdom
    🧑‍💻 Specialization: Bioimage Informatics, Machine Learning, and Image Processing

💼 Work Experience

  • Teaching Assistant (2008-2016)
    📍 Qassim University – College of Computer Science
  • Lecturer (2016-2020)
    📍 Qassim University – College of Computer Science
  • Assistant Professor (2020–Present)
    📍 Qassim University – College of Computer Science
  • Administrative Roles:
    • E-Content Supervisor (2020-2022)
    • IT Department Coordinator (2020-2022)
    • Member of various academic and examination committees

🏆 Achievements, Awards, and Honors

  • Published Research:
    • 📘 Sequential Graph-Based Extraction of Curvilinear Structures (2019)
      🔗 Signal, Image, and Video Processing Journal
    • 📘 The Multiscale Top-Hat Tensor (2019)
      🔗 Methods Journal
  • Research Contributions:
    🌟 Expertise in machine learning, deep learning, and medical image processing
    🌟 Development of novel architectures for analyzing curvilinear structures in biological and medical images
  • Committee Memberships:
    🏅 Standing Committees in the Scientific Council (2023-2024)
  • Supervision:
    🎓 Postgraduate Supervisor at the College of Computer Science

🌟 Areas of Interest

  • Machine Learning & Deep Learning 🤖
  • Medical Image Analysis 🏥
  • Computer Graphics and Signal Processing 🎨

Publication Top Notes:

Arabic Speech Recognition: Advancement and Challenges

Date Fruit Detection and Classification Based on Its Variety Using Deep Learning Technology

Exploring the Applications of Artificial Intelligence in Dental Image Detection: A Systematic Review

E-DFu-Net: An efficient deep convolutional neural network models for Diabetic Foot Ulcer classification

Integration of machine learning bi-modal engagement emotion detection model to self-reporting for educational satisfaction measurement

Prof. Jin Ho Suh | Deep Neural Network Awards | Best Researcher Award

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Prof. Jin Ho Suh | Deep Neural Network Awards | Best Researcher Award

Prof. Jin Ho Suh, Pukyong National University, South Korea

Dr. Jin-Ho Suh is a distinguished professor and expert in robotics, currently leading the Field Robotics Laboratory (FRLab) within the Major of Mechanical System Engineering at Pukyong National University, South Korea. With a Ph.D. in Control Engineering from the Tokyo Institute of Technology, Japan, and over two decades of academic and professional experience, Dr. Suh has significantly contributed to the fields of robotics and mechanical systems. He has held prominent roles, including Director of the Institute of Control, Robotics, and Systems, and is a Senior Member of IEEE. His leadership extends to national initiatives as the Chairman of the National Core Technology Committee for Robotics in South Korea and as an expert member of the Presidential Advisory Council on Science & Technology.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award: Prof. Jin-Ho Suh

Prof. Jin-Ho Suh, a distinguished researcher in the field of robotics and control engineering, holds a Ph.D. in Control Engineering from the Tokyo Institute of Technology and currently serves as a professor at Pukyong National University in South Korea. His extensive academic and professional experience, combined with significant contributions to the field, makes him an excellent candidate for the Best Researcher Award.

Education 🎓

  • Ph.D. in Control Engineering
    Tokyo Institute of Technology, Japan (Dec 1998 – Mar 2002)
  • Master of Engineering
    Graduate School of Engineering, Pukyong National University, South Korea (Mar 1996 – Feb 1998)
  • Bachelor of Science in Mathematics
    Hanyang University, South Korea (Mar 1989 – Feb 1993)

Work Experience 🛠️

  • Professor (Sep 2018 – Present)
    Major of Mechanical System Engineering, Pukyong National University
  • Senior Member (Nov 2022 – Present)
    Institute of Electrical and Electronics Engineers (IEEE)
  • Director
    • Institute of Control, Robotics, and Systems (Jan 2022 – Present)
    • Korean Society for Precision and Engineering (Jan 2020 – Present)
    • Korea Robotics Society (Jan 2018 – Present)
    • Korean Society for Power System Engineering (Jan 2017 – Present)
  • Chairman of the National Core Technology Committee (Robot) (Nov 2017 – Present)
    Korean Association for Industrial Technology Security
  • Expert Member (Jan 2021 – Present)
    Presidential Advisory Council on Science & Technology, South Korea
  • Adjunct Professor (Dec 2013 – Aug 2018)
    Department of Mechanical Engineering, POSTECH
  • Director of R&D Division (Apr 2006 – Aug 2018)
    Korea Institute of Robotics and Convergence Technology (KIRO)
  • Post-Doctoral Fellow (Jun 2003 – Feb 2006)
    National Research Laboratory, Dong-A University

Achievements 🏆

  • Patents
    • 28 patents (7 international PCT)
  • Publications
    • 14 papers in international journals (13 SCI)
    • 23 papers in domestic journals (15 SCOPUS)
    • 15 papers in international conferences
    • 60 papers in domestic conferences

Awards and Honors 🌟

  • Director Roles in Leading Engineering Societies
    • Institute of Control, Robotics and Systems
    • Korea Robotics Society
    • Korean Society for Precision and Engineering
  • Presidential Advisory Council Member
    • Significant contributions to national robotics and precision engineering strategies.
  • Chairman, National Core Technology Committee (Robot)
    • Recognized leader in industrial robotics technology and security.

Publication Top Notes

Artificial Neural Network for Glider Detection in a Marine Environment by Improving a CNN Vision Encoder

Development of a Multi-Robot System for Pier Construction

Model-Free RBF Neural Network Intelligent-PID Control Applying Adaptive Robust Term for Quadrotor System

Development of Fishcake Gripping and Classification Automation Process Based on Suction Shape Transformation Gripper

Estimation and Control of a Towed Underwater Vehicle with Active Stationary and Low-Speed Maneuvering Capabilities

Adaptive Robust RBF-NN Nonsingular Terminal Sliding Mode Control Scheme for Application to Snake Robot’s Head for Image Stabilization

Development of Recovery System for Underwater Glider

Prof. Catalin Dumitrescu | Artificial Intelligence Awards | Excellence in Research

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Prof. Catalin Dumitrescu | Artificial Intelligence Awards | Excellence in Research

Prof. Catalin Dumitrescu, University Politehnica of Bucharest, Romania

Dr. Cătălin Dumitrescu is an Associate Professor and R&D Scientific Adviser specializing in Computing and Artificial Intelligence at the Department of Electronics & Telecommunications, Transportation Engineering Faculty, University Politehnica of Bucharest (UPB), Romania. With a Ph.D. in Digital Signal Processing and Machine Learning from UPB, he possesses extensive expertise in artificial intelligence, machine learning, and digital signal processing, particularly in applications related to defense, cybersecurity, and multimedia security. Dr. Dumitrescu has over 20 years of R&D experience in the defense industry, including roles in machine learning systems for IMINT & SIGINT. He is also a certified expert in Critical Infrastructure Risk Management and Competitive Intelligence.

 

Professional Profile:

Summary of Suitability for Excellence in Research: Dr. Catalin Dumitrescu

Dr. Catalin Dumitrescu exemplifies excellence in research through his extensive expertise, academic credentials, professional experience, and impactful contributions in the fields of Artificial Intelligence, Machine Learning, and Digital Signal Processing, particularly in applications for defense, transportation, and security.

Education

🎓 Ph.D. in Digital Signal Processing & Machine Learning – University Politehnica of Bucharest.
📜 Engineering Degree in Signal and Image Processing – Transportation Engineering Faculty, UPB.
🎓 Postgraduate Degree in International Business & Economics – Bucharest University of Economic Studies.
📑 Certified Expert in:

  • Critical Infrastructure Risk Management ⚠️
  • Competitive Intelligence 🧠

Professional Experience

🔹 2015 – Present: Associate Professor, R&D Adviser in AI & Computing, UPB.
🔹 2018 – Present: R&D Consultant, SOLIDUS AI TECH.
🔹 2015 – 2018: Software Systems Architect, UTI GROUP.
🔹 1995 – 2015: R&D Military Officer, Defense Advanced Technology Institute.
🔹 1986 – 1995: Electronics Engineer, Transport Research Institute.

💡 Career Highlights:

  • 20+ years of experience in Machine Learning, AI, and Cyber Defence.
  • Expertise in IMINT & SIGINT for the defence sector 🛡️.
  • Development of advanced algorithms and software architecture for signal processing and AI systems.

Research Interests

🔍 Core Areas:

  • Artificial Intelligence & Machine Learning 🤖
  • Digital Signal Processing 📡
  • Neural Networks for Audio & Image Analysis 🎧🖼️
  • Cyber Security & Forensics 🕵️‍♂️
  • Cognitive Radio Systems 📻

🔍 Specialized Focus:

  • Deep Learning for object detection and classification 🖥️
  • Brain-Computer Interfaces 🧠
  • EEG, EKG, and EMG signal analysis 📊
  • Cryptography & Multimedia Security 🔒

Teaching Expertise

📚 Courses include:

  • Cyber Security & Defence 🔐
  • Digital Image Processing 📷
  • Real-Time Signal Processing ⏱️
  • Multimedia Forensics and Security 🎥

Publication top Notes:

Fuzzy logic for intelligent control system using soft computing applications

CITED:61

Development of an acoustic system for UAV detection

CITED:60

Using brain-computer interface to control a virtual drone using non-invasive motor imagery and machine learning

CITED:21

Aircraft trajectory tracking using radar equipment with fuzzy logic algorithm

CITED:21

Internal Auditing & Risk Management, No. 4 (56)

CITED:17

Monitoring system with applications in road transport

CITED:17

Mr. Heng Luo | Machine Learning Awards | Young Scientist Award

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Mr. Heng Luo | Machine Learning Awards | Young Scientist Award 

Mr. Heng Luo, The Hong Kong Polytechnic University, Hong Kong

Heng Luo is a distinguished researcher and PhD candidate at The Hong Kong Polytechnic University, specializing in the Institute of Textiles and Clothing since January 2021. His academic journey is marked by diverse and rich experiences across several prestigious institutions. Heng holds a Master’s degree in Electronic Engineering from the University of Electronic Science and Technology of China, completed in 2013, followed by another Master’s degree from the same institution in 2016, focusing on the Department of Industrial and Systems Engineering. Additionally, he earned an MSc from the University of Warwick’s Manufacturing Group. Heng’s research interests span across smart hardware, artificial intelligence, flexible devices, robotics, signal processing, cloud computing, and edge computing. His dedication to advancing technology is reflected in his active memberships with the Institution of Engineering and Technology and the IEEE, where he also contributes as a member of the Young Professionals group. His contributions to the field are recognized on platforms such as SciProfiles and ORCID, showcasing his commitment to connecting research and researchers worldwide. Heng Luo’s work exemplifies the integration of interdisciplinary knowledge and innovative thinking, driving forward the frontiers of technology and engineering

Professional Profile:

ORCID

Education:

  • 🎓 PhD, The Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Kowloon, Hong Kong (2021 – Present)
  • 🎓 MSc, Warwick Manufacturing Group, The University of Warwick, Coventry, West Midlands, UK (2013 – 2016)
  • 🎓 MSc, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong (2013 – 2016)
  • 🎓 Master Degree, Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China (2012 – 2013)
  • 🎓 Bachelor Degree, Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China (2008 – 2012)

Membership and Service:

  • 🏛️ Member, Institution of Engineering and Technology, Hong Kong, UK (2021 – Present)
  • 🌐 Member, IEEE, Hong Kong, NY, US (2021 – Present)
  • 👨‍💻 Young Professionals, IEEE, Hong Kong, NY, US (2021 – Present)

Work Experience

Note: The original information provided did not include details about work experience. If there is specific information about Heng Luo’s work experience that needs to be included, please provide those details.

Publication top Notes:

Integrated Wearable System for Monitoring Skeletal Muscle Force of Lower Extremities

Evaluating and Modeling the Degradation of PLA/PHB Fabrics in Marine Water

Ionic Hydrogel for Efficient and Scalable Moisture‐Electric Generation

Article identification method and device based on machine learning

Observer-based control of discrete-time fuzzy positive systems with time delays

Observer-based control of discrete-time fuzzy positive systems with time delays

Stability analysis of discrete-time fuzzy positive systems with time delays

Method for generating multi-input multi-output over-horizon (MIMO-OTH) radar waveforms based on digital signal processor (DSP) sequences