Dr. Thanh-Nghia Nguyen | Signal Processing | Best Researcher Award

Posted on by ScienceFather

Dr. Thanh-Nghia Nguyen | Signal Processing | Best Researcher Award

Dr. Thanh-Nghia Nguyen | HCMC University of Technology and Education | Vietnam

Dr. Nguyen Thanh Nghia (PhD) is a dedicated researcher and educator in Electronics and Biomedical Engineering at Ho Chi Minh City University of Technology and Education. With expertise in Biomedical Signal Processing, Artificial Intelligence, and Electronic Engineering, his research focuses on ECG signal analysis, deep learning applications, and medical device development. Dr. Nghia has contributed extensively through publications and research projects, particularly in ECG noise elimination and heart disease classification. His work bridges the gap between AI and healthcare, advancing biomedical engineering for better patient diagnostics and monitoring. 🌍📡🧠

Professional Profile:

ORCID

Suitability for Best Researcher Award

Dr. Nguyen Thanh Nghia is a strong candidate for the Best Researcher Award due to his outstanding contributions to biomedical signal processing, artificial intelligence applications in healthcare, and electronic engineering. His research has significantly impacted medical diagnostics, ECG signal enhancement, and AI-driven healthcare solutions, making his work highly valuable in both academia and industry.

Education & Experience🎓🔬

📌 PhD in Electronics Engineering – Ho Chi Minh City University of Technology and Education (2016-2023)
📌 Master’s in Electronics Engineering – Ho Chi Minh City University of Technology and Education (2009-2012)
📌 Bachelor’s in Electrical & Electronics Engineering – Ho Chi Minh City University of Technology and Education (2002-2007)

🔧 2007-2010 – Engineer, TNHH Wonderful Sai Gon Electrics (WSE), Vietnam (Machine Maintenance, Repair & ISO Management)
📡 2010-2017 – Lecturer, Cao Thang Technical College (Electronics Engineering)
👨‍🏫 2017-Present – Lecturer & Researcher, Ho Chi Minh City University of Technology and Education (Electronics & Biomedical Engineering)

Professional Development 🚀

Dr. Nguyen Thanh Nghia continuously enhances his expertise in Biomedical Engineering and Artificial Intelligence. He has led multiple research projects, developing ECG noise filters, heart disease classification systems, and medical signal processing tools. His work integrates machine learning and deep learning models for improved healthcare applications. Dr. Nghia actively collaborates with international scholars, publishing in high-impact journals 📑. He also mentors students and professionals, shaping the future of biomedical technology. His passion for innovation in AI-driven medical devices is evident in his contributions to academia and industry, fostering advancements in diagnostic healthcare systems. 🏥💡

Research Focus 🔍📊

Dr. Nguyen Thanh Nghia’s research primarily focuses on Biomedical Signal Processing, with an emphasis on ECG signal analysis, artifact removal, and AI-driven medical diagnostics. His work in deep learning-based heart disease classification contributes to the automation of medical diagnoses and remote health monitoring 🏥📡. He also explores wearable sensor technology, EEG-based brain-computer interfaces (BCI), and AI applications in healthcare 🤖. Through his innovative research, Dr. Nghia aims to enhance health monitoring systems, reduce diagnostic errors, and advance medical signal processing techniques, ultimately improving patient care and medical technology. 📉💙

Awards & Honors 🏆🎖️

🏅 Best Research Paper Award – Recognized for outstanding contributions to Biomedical Signal Processing & AI applications 📝
🏅 Outstanding Researcher Award – Ho Chi Minh City University of Technology and Education (for excellence in AI-driven ECG analysis) 📡
🏅 Top Innovator in Medical Engineering – Honored for advancements in ECG noise elimination and AI-based medical diagnostics 🏥🧠
🏅 Young Scientist Recognition – For impactful publications in deep learning and medical signal processing 📊📚

Publication Top Notes:

    • 📌 A VGG-19 model with transfer learning and image segmentation for classification of tomato leaf disease – TH Nguyen, TN Nguyen, BV Ngo  🔗 Cited by: 69
    • 📌 A deep learning framework for heart disease classification in an IoTs-based system – TH Nguyen, TN Nguyen, TT Nguyen  🔗 Cited by: 24
    • 📌 Detection of EEG-based eye-blinks using a thresholding algorithm – DK Tran, TH Nguyen, TN Nguyen 🔗 Cited by: 17
    • 📌 Artifact elimination in ECG signal using wavelet transform – TN Nguyen, TH Nguyen, VT Ngo🔗 Cited by: 17
    • 📌 Deep Learning Framework with ECG Feature-Based Kernels for Heart Disease Classification – THN Thanh-Nghia Nguyen 🔗 Cited by: 16

 

 

Mohtasham Khanahmadi | signal processing | Best Researcher Award

Posted on by ScienceFather

Mohtasham Khanahmadi | signal processing | Best Researcher Award

Mr.Mohtasham Khanahmadi, Semnan University, Iran.

Mr.Mohtasham Khanahmadi is an Iranian civil engineering researcher specializing in structural health monitoring, damage detection, and signal processing. With over five years of experience, he focuses on nondestructive evaluation, inverse problems, and modal analysis of thin-walled and composite structures. He holds a B.Sc. in Civil Engineering from Velayat University and an M.Sc. in Structural Engineering from Semnan University. Proficient in MATLAB, Abaqus, and computational modeling, he has authored impactful research on damage localization and interfacial debonding detection. Passionate about enhancing structural integrity, his contributions advance the field of applied and computational mathematics in civil engineering. 🔍🛠️

Publication Profile

Orcid
Scopus
Google Scholar

Education & Experience 🎓👷‍♂️

📌 B.Sc. in Civil Engineering – Velayat University, Iran (2011–2015)
📌 M.Sc. in Structural Engineering – Semnan University, Iran (2015–2018)
📌 Researcher in Structural Health Monitoring & Damage Detection (5+ years)
📌 Expert in Computational Mathematics & Signal Processing for Civil Structures
📌 Published Research in High-Impact Structural Engineering Journals.

Suitability Summary

Dr. Mohtasham Khanahmadi is a distinguished civil engineering researcher recognized for his outstanding contributions to structural health monitoring, damage detection, and signal processing. With over five years of dedicated research, he has demonstrated exceptional expertise in nondestructive evaluation, applied and computational mathematics, inverse problems, and modal analysis of thin-walled and composite structures, including plates, beams, and columns. His pioneering methodologies have significantly advanced the assessment of structural integrity and performance, making him a highly deserving candidate for the Best Researcher Award.

Professional Development 📈🔬

Mr.Mohtasham Khanahmadi actively contributes to the advancement of structural health monitoring through cutting-edge research in damage detection and localization techniques. His expertise spans signal processing,  nverse problems, and modal analysis, with a strong focus on nondestructive evaluation of civil structures. Skilled in MATLAB, Abaqus, and Microsoft Office tools, he integrates computational methods to enhance structural performance. His work in analyzing thin-walled and composite structures under axial loads has led to significant advancements in interfacial debonding detection and modal curvature-based irregularity indices. Dedicated to academic excellence, he continuously engages in professional learning and knowledge dissemination. 📊🏗️.

Research Focus  🔍🏢

Mr.Mohtasham Khanahmadi’s research centers on structural health monitoring 🏗️, emphasizing damage detection and localization in civil engineering structures. His work involves signal processing 📡, nondestructive evaluation 🛠️, and computational mathematics 🔢 to enhance the integrity of thin-walled and composite structures such as plates, beams, and columns. He specializes in inverse problem-solving to assess structural behavior under different conditions, including modal analysis of concrete-filled steel tubular (CFST) columns. By developing advanced methodologies, he contributes to the early detection of structural failures, leading to safer and more efficient engineering solutions. 🚧🔬.

Awards & Honors 🏆🎖️

🏅 Recognized for impactful research in structural health monitoring & damage detection
🏅 Published in high-impact journals, including Measurement & IJSSD
🏅 Contributions to computational civil engineering methodologies acknowledged in academia
🏅 Active collaborator in multidisciplinary structural engineering research projects
🏅 Recognized for advancing nondestructive evaluation techniques for damage localization.

Publication Top Notes

📌 A numerical study on vibration-based interface debonding detection of CFST columns using an effective wavelet-based feature extraction technique – 2024

📌 Interfacial Debonding Detection in Concrete-Filled Steel Tubular (CFST) Columns with Modal Curvature-Based Irregularity Detection Indices – 2024

📌 Vibration-based damage localization in 3D sandwich panels using an irregularity detection index (IDI) based on signal processing – 2024

📌 Vibration-based health monitoring and damage detection in beam-like structures with innovative approaches based on signal processing: A numerical and experimental study – 2024

 

 

 

Assist. Prof. Dr. Chaofeng Zhao | Signal Processing | Best Researcher Award

Posted on by ScienceFather

Assist. Prof. Dr. Chaofeng Zhao | Signal Processing | Best Researcher Award

Assist. Prof. Dr. Chaofeng Zhao | Luoyang Normal University | China

Zhao Chaofeng is a dedicated academic and researcher specializing in digital communications, signal processing, and image processing. 📡🔍 He holds a Ph.D. in Control Engineering from Xi’an University of Technology (2020), an M.S. in Applied Mathematics from Beifang University for Nationalities (2012), and a B.S. in Applied Mathematics from Fuyang Normal University (2005). 🎓 Currently serving as a lecturer at Luoyang Normal University, he has authored 20 research papers, including 10 in prestigious journals like ND, IJBC, and CIS. 📖✍️ Additionally, he holds 4 authorized invention patents, contributing significantly to technological advancements. 🔬💡

Professional Profile:

ORCID

Suitability for Best Researcher Award

Dr. Zhao Chaofeng is a highly accomplished researcher in the fields of digital communications, signal processing, and image processing. His strong academic background, with a Ph.D. in Control Engineering, along with his M.S. and B.S. in Applied Mathematics, demonstrates a solid foundation in mathematical modeling and engineering applications.

Education & Experience 📚👨‍🏫

  • 🎓 Ph.D. in Control Engineering – Xi’an University of Technology, 2020
  • 🎓 M.S. in Applied Mathematics – Beifang University for Nationalities, 2012
  • 🎓 B.S. in Applied Mathematics – Fuyang Normal University, 2005
  • 👨‍🏫 Lecturer – School of Information Technology, Luoyang Normal University, China
  • ✍️ Published 20 research papers, including 10 in ND, IJBC, CIS, and other top journals
  • 🔬 Holds 4 authorized invention patents in the fields of signal and image processing

Professional Development 📡🔬📖

Zhao Chaofeng continuously expands his expertise in digital communications and signal processing through active research and publications. 📝 He contributes to the academic community by mentoring students and participating in technological advancements. 💡 His research explores innovative applications in coding and engineering mathematical methods, driving progress in modern communication systems. 📶 As a lecturer at Luoyang Normal University, he is committed to knowledge-sharing and academic excellence. 🏫 His work has received recognition through multiple patents, and he remains engaged in interdisciplinary studies to enhance the efficiency and accuracy of digital signal applications. 🚀🔍

Research Focus 🔬📡📊

Dr. Zhao’s research revolves around digital communications, signal processing, and image processing, aiming to enhance modern technology’s efficiency and reliability. 📡 His work integrates coding techniques and mathematical modeling to optimize communication systems. 📊 Through cutting-edge innovations, he explores advanced signal filtering, noise reduction, and image enhancement for various applications. 🖼️📡 His interdisciplinary approach bridges mathematics, engineering, and computational methods to develop robust solutions in data transmission and processing. 📶🔍 His contributions have significantly impacted theoretical advancements and practical applications in the field, fostering progress in modern digital communication. 🚀💡

Awards & Honors 🏆🎖️

  • 🏅 Published 20 research papers, including 10 in ND, IJBC, CIS, and other prestigious journals
  • 📜 4 authorized invention patents in digital communications and signal processing
  • 🎓 Recognized for contributions in mathematical modeling and engineering applications
  • 🌍 Active participant in international conferences and research collaborations
  • 🏆 Awarded research grants for innovative work in digital signal and image processing

Publication Top Notes:

🔐 Delayed Chaotic Image Encryption Using Cross-Layer and DNA Coding Techniques
🖼 A Novel Image Encryption Algorithm by Delay Induced Hyper-chaotic Chen System
📖 Weakness Analyzing and Performance Improvement for Image Encryption with Chaos Across Cylinder
📊 Optimal Control of Stochastic System with Fractional Brownian Motion
📸 Image Encryption Based on Hyper-chaotic Multi-attractors

 

 

Mr. Eric Jacob Bacon | Digital Signal processing

Posted on by ScienceFather

Mr. Eric Jacob Bacon : Leading Researcher in Digital Signal processing

Mr. Eric Jacob Bacon, Northeastern University, China

🎓 Bringing a wealth of expertise with a Ph.D. in Biomedical Engineering and a solid foundation, holding Master and Bachelor degrees in Software and Electrical Engineering. With close to two years of professional experience in Electrical Engineering and a strong background in ICT and Software Engineering, He thrives in interdisciplinary settings. Her passion is harnessing technology to transform healthcare, highlighted in her innovative Ph.D. research and impactful software contributions. He enthusiastic about leading projects that seamlessly integrate healthcare, computer technologies, and electrical engineering to encourage collaboration and fuel societal innovation. 🌟

🌐 Professional Profiles : 

Scopus

ORCID

Professional & Technical Skills 🚀🔧

In the realm of academia, He have cultivated a proficiency in crafting meticulously researched and well-articulated scientific papers. Her expertise extends to presenting complex findings in a clear, concise, and academically rigorous manner. Specializing in AI and Digital Signal Processing, her technical skills are finely tuned to contribute to the forefront of technological advancements. 📝🔬

Algorithm Development and Optimization 🧠📊 He adept at crafting advanced algorithms for medical imaging analysis, focusing on refining Classification, Detection, and Segmentation processes. Her dedication to precision-driven efficiency ensures accurate and streamlined outcomes in AI and data analysis processes. 🔄💻

Software and Tools Mastery 🛠️ Proficient in an extensive suite of statistical and data analysis tools, including SPSS, PyTorch, SPM, Tensorflow, and other industry-standard applications. Leveraging these tools, He conduct sophisticated analyses and draw robust conclusions. 📊🔍

Networking and Electrical Technologies Proficiency ⚡🌐 In the domain of networking and electrical technologies, He excel at optimizing systems for enhanced efficiency and performance. Demonstrating proficiency, He design and implement robust, scalable solutions within this dynamic field. 💡🔌

Programming Abilities and Database Technologies 💻📚 Proficient in multiple programming languages, such as Python, MATLAB, and Java, He contribute to streamlined and efficient software development processes. Additionally, her knowledge in various database technologies enables efficient data storage, retrieval, and management. 🖥️🗃️

Multilingual Communication Skills 🌐🗣️ Fluent in both French and English, He facilitate effective communication in diverse academic and professional settings. Possessing advanced Mandarin skills further enhance her global communication capabilities, fostering collaboration across linguistic boundaries. 🌍🗨️

Advanced Data Analytics 📈🔍 With a proven ability to derive actionable insights from diverse datasets, He employ cutting-edge analytical techniques to uncover valuable information, contributing to informed decision-making and innovation. 🧮💡

Publications ( Top Note ) :

1.  Epileptogenic Zone Localization in Refractory Epilepsy by FDG-PET: The Comparison of SPM and SPM-CAT with Different Parameter Settings

2.  Functional and effective connectivity analysis of drug-resistant epilepsy: a resting-state fMRI analysis

3.  Cortical Surface Analysis for Focal Cortical Dysplasia Diagnosis by using PET Images

4.  Resting-State Functional Connectivity Analysis Using an Independent Component Approach

5.  Neuroimage Analysis Using Artificial Intelligence Approaches: A Systematic Review