Mr. Md. Humayun Kabir | Transfer Learning Awards | Best Researcher Award

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Mr. Md. Humayun Kabir | Transfer Learning Awards | Best Researcher Award

Mr. Md. Humayun Kabir, International Islamic University Chittagong, Bangladesh

MD. Humayun Kabir is a dedicated educator and professional in the field of computer and communication engineering, currently serving as a Lecturer at the International Islamic University Chittagong, Bangladesh. With a strong foundation in Electronic and Telecommunication Engineering, he is pursuing his M.Sc. at Chittagong University of Engineering and Technology. Humayun’s professional experience includes roles as a Course Instructor at CSL Academy, Senior Technical Trainer at New Vision Information Technology Limited, and Course Instructor at ERevo Technologies Limited, where he specializes in Cisco Certified Network Associate (CCNA) training and various IT certifications. His career is marked by a commitment to enhancing students’ practical skills and preparing them for the rapidly evolving technology landscape. Humayun’s research interests encompass a broad range of topics, including computer networking, cybersecurity, artificial intelligence, machine learning, and the Internet of Things (IoT). With a passion for teaching and mentoring, he aims to inspire the next generation of technology professionals.

Professional Profile:

ORCID

Summary of Suitability for the Research for Best Researcher Award: 

MD. Humayun Kabir emerges as an outstanding candidate for the Research for Best Researcher Award due to his impressive combination of academic achievements, professional experience, and dedicated research interests. Here are the key reasons that support his suitability

📚 Education

  • M.Sc. (Engineering)
    Chittagong University of Engineering and Technology
    Studying since 2020
    GPA: 3.5/4.0
    Field: Electronic and Telecommunication Engineering
  • B.Sc. (Engineering)
    International Islamic University Chittagong
    Graduated in 2018
    GPA: 3.863/4.0
    Field: Electronic and Telecommunication Engineering
  • Higher Secondary Certificate (H.S.C)
    Chittagong Model School & College
    Graduated in 2013
    GPA: 4.90/5.0
    Field: Science
  • Secondary School Certificate (S.S.C)
    Agrasar Bouddya Anathalay High School
    Graduated in 2011
    GPA: 4.44/5.0
    Field: Science

💼 Professional Experience

  • Lecturer
    Department of Computer & Communication Engineering (CCE)
    International Islamic University Chittagong, Bangladesh
    January 2023 – Present
  • Course Instructor
    CSL Training (CSL Academy)
    Cisco Certified Network Associate Routing & Switching (CCNA)
    August 2024 – Present
  • Senior Technical Trainer
    New Vision Information Technology Limited (NVIT / New Horizons)
    Cisco Certified Network Associate Routing & Switching (CCNA)
    May 2023 – Present
  • Course Instructor
    ERevo Technologies Limited
    CCNA, MikroTik Certified Network Associate (MTCNA), RedHat Certified System Administrator (RHCSA), CompTIA A+, IT Essential Certification and Training, Microsoft Office Professionals
    February 2019 – Present
  • Assistant Proctor
    International Islamic University Chittagong, Bangladesh
    March 2023 – August 2024
  • Assistant Lecturer
    Department of Computer & Communication Engineering (CCE)
    International Islamic University Chittagong, Bangladesh
    January 2022 – December 2022
  • Adjunct Lecturer
    Department of Electronic & Telecommunication Engineering (ETE)
    International Islamic University Chittagong, Bangladesh
    November 2018 – December 2021
  • Teaching Assistant
    Department of Electronic & Telecommunication Engineering
    International Islamic University Chittagong, Bangladesh
    May 2018 – September 2018

🏆 Achievements and Awards

  • Cisco Certified Network Associate (CCNA) certification
  • MikroTik Certified Network Associate (MTCNA) certification
  • RedHat Certified System Administrator (RHCSA) certification
  • CompTIA A+ certification
  • IT Essentials Certification and Training
  • Microsoft Office Professionals certification

Publication Top Notes:

Design and Simulation of AI-Enabled Digital Twin Model for Smart Industry 4.0

Enhancing Insider Malware Detection Accuracy with Machine Learning Algorithms

Transfer Learning-Based Anomaly Detection System for Autonomous Vehicle

Design and Implement IoT-Based Intelligent Manageable Smart Street Lighting Systems for Future Smart City

Design and Analysis of Multiband Microstrip Patch Antenna Array for 5G Communications

 

Ms. Congying Sun | Object Detection Awards | Best Researcher Award

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Ms. Congying Sun | Object Detection Awards | Best Researcher Award 

Ms. Congying Sun, Xi’an University of Technology, China

Congying Sun, a native of Xianyang City, Shaanxi Province, is an emerging researcher specializing in control science, engineering, and multi-modal remote sensing technologies. She earned her Bachelor’s degree in Printing Engineering from Xi’an University of Technology in 2022 and is currently pursuing a Master’s degree in Control Science and Engineering at the same institution, expected to graduate in 2025. Her professional experience includes a tenure at the Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, where she played a pivotal role in developing an infrared-visible aircraft image dataset and deploying state-of-the-art infrared small target detection models. Congying has demonstrated her ability to merge academic excellence with practical application through her contributions to national and engineering projects, including research on multi-source collaborative intelligent perception technology for aircraft and non-cooperative multi-target classification and cognition technology.

Professional Profile:

ORCID

Suitability of Congying Sun for the Best Researcher Award

Congying Sun demonstrates exceptional qualifications and accomplishments, making her an outstanding candidate for the Research for Best Researcher Award. Below is a summary of her key achievements and strengths

🎓 Education

  • Master’s Degree in Control Science and Engineering (August 2022 – July 2025)
    🏫 Xi’an University of Technology
  • Bachelor’s Degree in Printing Engineering (September 2018 – July 2022)
    🏫 Xi’an University of Technology

🧑‍💻 Professional Experience

Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences (July 2023 – August 2024)

  • 📸 Independently created an infrared-visible aircraft image dataset, including camera selection, data collection, and image annotation.
  • 📝 Authored project proposals, research papers, and patents with great precision.
  • 🤖 Developed and deployed infrared small target detection models and multi-modal remote sensing image fusion detection models.

🚀 Research Projects

  • Multi-source Collaborative Intelligent Perception Technology for Aircraft (August 2023 – June 2024) ✈️
  • Non-cooperative Multi-target Classification and Cognition Technology (October 2023 – March 2024) 🎯

🏅 Achievements

  • Granted Invention Patents:
    • 📜 Infrared Small Target Detection Method (CN118762159A)
    • 📜 Multi-modal Feature Fusion Target Detection Model and Method (CN118865046A)

💡 Research Interests

🔍 Machine Learning | 🌍 Multi-modal Remote Sensing | 🎯 Target Detection

Congying Sun’s innovative approach, technical expertise, and impactful contributions to cutting-edge research make her a rising star in the field of control science and engineering. 🌟

Publication Top Notes:

Location-Guided Dense Nested Attention Network for Infrared Small Target Detection

MMYFnet: Multi-Modality YOLO Fusion Network for Object Detection in Remote Sensing Images

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. Lianfa Li | Artificial Intelligence Award | Top Researcher Award

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Mr. Lianfa Li | Artificial Intelligence Award | Top Researcher Award 

Mr. Lianfa Li, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, China 

Dr. Lianfa Li is a distinguished Senior Research Associate and Lead Data Scientist at the University of Southern California’s Department of Population and Public Health Sciences. Since August 2017, he has been at the forefront of innovations in data science and machine learning, with a particular focus on remote sensing and air pollution modeling to study exposure and health effects. Dr. Li’s academic journey began with a Bachelor of Science in Resources, Planning, and Management from Nanjing University in 1998, followed by a Ph.D. in Geographical Information Science from the Institute of Geographical Sciences and Natural Resources Research at the Chinese Academy of Sciences in 2005. His career includes significant roles such as Associate Professor at the Chinese Academy of Sciences, Postdoctoral Scholar and Associate Specialist at the University of California, Irvine, and Research Associate at USC’s Department of Preventive Medicine.

Professional Profile:

 

ORCID

 

Summary of Suitability for the Top Researcher Award

Lianfa Li, PhD, currently a Senior Research Associate and Lead Data Scientist at the University of Southern California’s Department of Population and Public Health Sciences, is an exemplary candidate for the Top Researcher Award. His extensive background in data science and machine learning, particularly in the realm of remote sensing and air pollution exposure, positions him as a leader in his field. Below are the reasons why Dr. Li is suitable for this prestigious award:

EDUCATION 🎓📚

  • PhD in Geographical Information Science (June 2005)
    Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
    Advisor: Prof. Jinfeng Wang
  • Bachelor of Science in Resources, Planning and Management (Aug 1998)
    Nanjing University, Nanjing, Jiangsu Province, China
    Advisor: Prof. Yunliang Shi

ACADEMIC EMPLOYMENT 🏛️💼

  • Senior Research Associate, Lead Data Scientist (Aug 2017-Present)
    Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA
    Leading innovations in data science and machine learning, and the modeling efforts in remote sensing and air pollution (exposure and health effects)
  • Research Associate (Aug 2017-July 2014)
    Department of Preventive Medicine, University of Southern California, Los Angeles, CA
  • Associate Specialist (June 2013-June 2014)
    Program in Public Health, University of California, Irvine, CA

HONORS AND AWARDS 🏆🎖️

  1. 2010.6
    The paper about Bayesian risk modeling (Risk Analysis, 30(7), 1157-1175) selected for a media outreach campaign in 2010 by Society for Risk Analysis
  2. 2007.5
    Chinese Academy of Sciences KC Wong Work Incentive Fund
  3. 2004.3
    The Excellent Presidential Scholarship of Chinese Academy of Sciences, 2004

WORKSHOP AND PRESENTATION 🎤📅

  1. Biweekly workshop: “Air pollution and exposure modeling” (2015-present, University of Southern California, California, USA)
  2. Invited presentation: “GCN-assisted U-Net for segmentation of OCT images” (Bay area data science workshop, Mar. 27, 2021)
  3. Invited presentation: “Enhancing semantic segmentation with contextual information” (Bay area data science workshop, Dec. 07, 2019)

Publication top Notes:

Geocomplexity Statistical Indicator to Enhance Multiclass Semantic Segmentation of Remotely Sensed Data with Less Sampling Bias

Multiscale Entropy-Based Surface Complexity Analysis for Land Cover Image Semantic Segmentation

Generating Fine-Scale Aerosol Data through Downscaling with an Artificial Neural Network Enhanced with Transfer Learning

Encoder–Decoder Full Residual Deep Networks for Robust Regression and Spatiotemporal Estimation

Multi-Scale Residual Deep Network for Semantic Segmentation of Buildings with Regularizer of Shape Representation

Optimal Inversion of Conversion Parameters from Satellite AOD to Ground Aerosol Extinction Coefficient Using Automatic Differentiation

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

Prof. Changgyun Kim | Artificial Intelligence Award | Best Researcher Award

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Prof. Changgyun Kim | Artificial Intelligence Award | Best Researcher Award 

Prof. Changgyun Kim, Department of Artificial Intelligence & Software/Samcheok,South Korea

Changgyun Kim is an esteemed academic and researcher associated with Kangwon National University, Department of Artificial Intelligence & Software, and Dongguk University’s Industrial Engineering department in South Korea. His research expertise spans deep learning, healthcare, and data mining. He has made significant contributions to the field, including developing AI-based systems for detecting betting anomalies in sports, diagnosing tooth-related diseases using panoramic images, and creating models for obesity diagnosis using 3D body information. His work is published in renowned journals such as Scientific Reports, Annals of Applied Sport Science, JMIR Medical Informatics, Sensors, Sustainability, the International Journal of Distributed Sensor Networks, and Applied Sciences. Dr. Kim’s notable projects include establishing IoT-based smart factories for SMEs in Korea and developing web applications for obesity diagnosis using data mining methodologies. His extensive research portfolio underscores his commitment to advancing AI applications in various domains

Professional Profile:

ORCID

 

Education

No specific details about Changgyun Kim’s educational background are provided in the provided information. To give a more comprehensive overview, details such as degrees obtained, institutions attended, and fields of study would be needed.

Work Experience

  1. Dongguk University: Jung-gu, Seoul, KR
    • Department: Industrial Engineering
    • Position: Not specified in the provided information.
  2. Kangwon National University
    • Department: Artificial Intelligence & Software
    • Position: Not specified in the provided information.

Publication top Notes:

 

AI-based betting anomaly detection system to ensure fairness in sports and prevent illegal gambling

Detectability of Sports Betting Anomalies Using Deep Learning-based ResNet: Utilization of K-League Data in South Korea

Tooth-Related Disease Detection System Based on Panoramic Images and Optimization Through Automation: Development Study

Development of an Obesity Information Diagnosis Model Reflecting Body Type Information Using 3D Body Information Values

Development of a Web Application Based on Human Body Obesity Index and Self-Obesity Diagnosis Model Using the Data Mining Methodology

Establishment of an IoT-based smart factory and data analysis model for the quality management of SMEs die-casting companies in Korea

Prof. Ming-Hsiang Su | Deep Learning | Best Researcher Award

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Prof. Ming-Hsiang Su | Deep Learning | Best Researcher Award 

Prof. Ming-Hsiang Su, Data Science, Soochow University, Taiwan, Taiwan

Ming-Hsiang Su is an esteemed assistant professor in the Department of Data Science at Soochow University in Taipei, Taiwan. He earned his Ph.D. in Computer Science and Information Engineering from National Chung Cheng University and has an impressive academic background with an M.S. in Management Information Systems from National Pingtung University of Science and Technology and a B.S. in Computer Science from Tunghai University. His research expertise includes spoken dialogue systems, personality trait perception, speech emotion recognition, and speech signal processing. Before his current role, Ming-Hsiang conducted postdoctoral research at National Cheng Kung University and served as a lecturer at multiple institutions, including National Pingtung University of Science and Technology and National Chung Cheng University. His professional journey also includes a stint as an R&D engineer at Cino Group. His work in deep learning, natural language processing, and emotion and personality perception has significantly contributed to advancements in speech signal processing.

Professional Profile:

ORCID

 

🎓 Education

  • Ph.D. in Computer Science and Information Engineering, National Chung Cheng University
  • M.S. in Management Information Systems, National Pingtung University of Science and Technology
  • B.S. in Computer Science, Tunghai University

💼 Work Experience

  • Assistant Professor (August 2020 – Present)
    Department of Data Science at Soochow University, Taipei, Taiwan
  • Postdoctoral Fellow (August 2013 – July 2020)
    Department of Computer Science and Information Engineering (CSIE) at National Cheng Kung University, Tainan, Taiwan
  • Lecturer (June 2013 – July 2013)
    Skill Evaluation Center of Workforce Development Agency, Ministry of Labor, Taichung City, Taiwan
  • Lecturer (February 2012 – January 2013)
    Department of Management Information Systems at National Pingtung University of Science and Technology, Pingtung, Taiwan
  • Lecturer (September 2006 – January 2013)
    Department of Mathematics at National Chung Cheng University, Chiayi, Taiwan
  • R & D Engineer (August 2003 – September 2004)
    Cino Group, Taipei, Taiwan

Ming-Hsiang Su’s career reflects his dedication to advancing the field of computer science, particularly in speech and signal processing, through a blend of academic excellence and practical research. 🌟

Publication top Notes:

Few-Shot Image Segmentation Using Generating Mask with Meta-Learning Classifier Weight Transformer Network

Implementation of Sound Direction Detection and Mixed Source Separation in Embedded Systems

Semantic-Based Public Opinion Analysis System

Conditional Adversarial Learning for Empathetic Dialogue Response Generation

Speech Emotion Recognition Considering Nonverbal Vocalization in Affective Conversations