Dr. Etsuro Hori | Spectrum Analysis | Best Researcher Award

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Dr. Etsuro Hori | Spectrum Analysis | Best Researcher Award 

Dr. Etsuro Hori | Spectrum Analysis | University of Toyama | Japan

Etsuro Hori, Ph.D., is a Professor of Behavioral Science at the Faculty of Medicine, Toyama Medical and Pharmaceutical University, Japan. He earned his Bachelor and Master of Agriculture degrees from Niigata University and completed his Doctor of Philosophy in Medicine at Toyama Medical and Pharmaceutical University. Professor Hori began his professional career as a researcher at Nippon Chemiphar Co., Ltd., and later held academic positions as Research Assistant and Associate Professor in the Department of Physiology at Toyama Medical and Pharmaceutical University before his current professorship. His research focuses on neuroscience, behavioral science, and neurophysiological processes, with notable work on electroencephalography (EEG) in non-human primates, neural representation of spatial and reward learning, face detection mechanisms, and sleep physiology. Professor Hori has authored 81 scientific publications, with over 1,830 citations, and holds an h-index of 29, reflecting the impact and relevance of his work. He has contributed to the advancement of both fundamental and applied neuroscience, including studies on gamma oscillations in the superior colliculus and pulvinar, neural detection of faces and snakes, and the effects of sleep quality on fatigue in shift workers.

Professional Profile

Scopus

Suitability Summary 

Prof. Etsuro Hori is a highly accomplished scientist whose extensive career in behavioral science, physiology, and medical research positions him as a strong candidate for the Best Researcher Award. With a Doctor of Philosophy in Medicine (2001) from Toyama Medical and Pharmaceutical University, Prof. Hori has demonstrated over three decades of dedication to scientific discovery, translational research, and academic leadership.

Education 

  • Bachelor of Agriculture, Department of Animal Science, Faculty of Agriculture, Niigata University, Japan, 1991

  • Master of Agriculture, Graduate School of Agriculture, Niigata University, Japan, 1993

  • Doctor of Philosophy (Medicine), Toyama Medical and Pharmaceutical University, Japan, 2001

Work Experience 

  • Researcher, Nippon Chemiphar Co., Ltd., Tokyo, Japan, Apr. 1993 – Mar. 1999

  • Research Assistant, Department of Physiology, Faculty of Medicine, Toyama Medical and Pharmaceutical University, Japan, Apr. 1999 – Mar. 2005

  • Associate Professor, Department of Physiology, Faculty of Medicine, Toyama Medical and Pharmaceutical University, Japan, Apr. 2005 – Mar. 2013

  • Professor, Behavioral Science, Faculty of Medicine, Toyama Medical and Pharmaceutical University, Japan, Mar. 2013 – Present

Achievements, Awards, and Honors

  • Authored 81 publications with 1,830 citations

  • h-index of 29

  • Contributions to neuroscience, sleep research, and behavioral science including studies on EEG in monkeys, face detection in superior colliculus, and sleep quality in shift workers

  • Editorial and research recognition through multiple peer-reviewed publications in international journals such as Frontiers in Systems Neuroscience, Neuropsychologia, and Frontiers in Neurology

Publication Top Notes

Characteristics of Peripheral Intravenous Catheter Cannulation in Older Japanese Inpatients

Non-invasive electroencephalographical (EEG) recording system in awake monkeys

A Prototypical Template for Rapid Face Detection Is Embedded in the Monkey Superior Colliculus

Neural Representation of Overlapping Path Segments and Reward Acquisitions in the Monkey Hippocampus

Gamma oscillations in the superior colliculus and pulvinar in response to faces support discrimination performance in monkeys

Mr. Zhaoan Yu | Signal Detection | Best Researcher Award

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Mr. Zhaoan Yu | Signal Detection | Best Researcher Award 

Mr. Zhaoan Yu, Institute of Microelectronic of The Chinese Academy of Science, China

Zhaoan Yu is a senior engineer at the Institute of Microelectronics, Chinese Academy of Sciences in Beijing, China, where he has contributed significantly to the field of semiconductor device and integrated circuit testing. His research spans the development of high-precision source-measure units, high-speed digital/analog test boards, IP design, and testing algorithms, along with hardware–software integration for automated IC test systems. He also explores advanced methods for trace gas detection using infrared laser-based systems. Dr. Yu earned his Ph.D. in Microelectronics and Solid-State Electronics from the University of Chinese Academy of Sciences, following his Master’s and Bachelor’s degrees in the same field from Northwest University, Xi’an. He has progressed from research intern to assistant researcher, and currently serves as a senior engineer, with a career at the Institute of Microelectronics beginning in 2008. He has authored several peer-reviewed publications in the areas of quantum cascade lasers, UV image sensors, and spectroscopy methods. In addition, Zhaoan Yu is the inventor of multiple granted patents in the field of IC testing technologies and protection circuits. His work reflects a strong blend of innovation and application in microelectronic systems and sensor technologies.

Professional Profile:

SCOPUS

Summary of Suitability: Dr. Zhaoan Yu – Best Researcher Award

Dr. Zhaoan Yu is an outstanding candidate for the Best Researcher Award, recognized for his innovative contributions to the fields of semiconductor device testing, integrated circuit (IC) test systems, and infrared laser-based trace gas detection. His multidisciplinary research has advanced both the theory and application of high-precision electronic testing and photonic sensing, directly addressing critical engineering challenges in modern microelectronics.

Education:

  • Doctor of Philosophy in Microelectronics and Solid-State Electronics
    University of Chinese Academy of Sciences, Beijing, China – January 2016

  • Master of Science in Microelectronics and Solid-State Electronics
    Northwest University, Xi’an, China – July 2008

  • Bachelor of Science in Electronic Information Science and Technology
    Northwest University, Xi’an, China – July 2005

Work Experience:

  • Senior Engineer
    Institute of Microelectronics, Chinese Academy of Sciences, Beijing, China – April 2017 to Present

  • Assistant Researcher
    Institute of Microelectronics, Chinese Academy of Sciences, Beijing, China – October 2010 to March 2017

  • Research Intern
    Institute of Microelectronics, Chinese Academy of Sciences, Beijing, China – July 2008 to September 2010

Achievements and Contributions:

  • Led and contributed to key developments in semiconductor device and IC testing, including high-precision source-measure units and high-speed digital/analog test boards.

  • Active in research on hardware–software integration and test algorithms for automated IC test systems.

  • Contributed to research in infrared laser-based trace gas detection systems.

  • Authored multiple peer-reviewed technical publications in areas such as UV image sensors, temperature control modules, and quantum cascade laser technologies.

  • Granted multiple national patents in China related to array device testing and current-limiting protection systems.

Selected Honors and Recognitions:

  • Granted patents for innovations in array device testing and circuit protection (2024, 2023, 2019)

  • First demonstration of high-sensitivity deep UV image sensors at the 2022 IEEE Symposium on VLSI Technology and Circuits

  • Recognized contributor to advancements in microsystem technologies and laser-based sensing methods through publications in Micronanoelectronic Technology, Infrared and Laser Engineering, and other journals.

Publication Top Notes:

On-Site and Sensitive Pipeline Oxygen Detection Equipment Based on TDLAS

Hardware Implementation of Next Generation Reservoir Computing with RRAM-Based Hybrid Digital-Analog System

Lifetime Improvement of 28 nm Resistive Random Access Memory Chip by Machine Learning-Assisted Prediction Model Collaborated with Resurrection Algorithm

Mr. Jindong Zhang | Radio Frequency | Best Researcher Award

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Mr. Jindong Zhang | Radio Frequency | Best Researcher Award 

Mr. Jindong Zhang, Beijing University of Posts and Telecommunications, China

Zhang Jindong is a master’s candidate at Beijing University of Posts and Telecommunications, specializing in radio frequency power amplifiers. His research focuses on developing innovative designs for dual-band power amplifiers with enhanced efficiency and bandwidth for mobile communications. He has published an SCI-indexed journal paper in Microelectronics Journal and contributed to a project funded by the National Natural Science Foundation of China. Zhang has also filed a patent on an advanced output matching network for dual-band power amplifiers. His work has demonstrated significant improvements in drain efficiency and linearity, making valuable contributions to the field of RF circuit design for 5G applications.

Professional Profile:

ORCID

Suitability Summary for Best Researcher Award – Zhang Jindong

Zhang Jindong is an emerging researcher in radio frequency power amplifiers, currently pursuing his master’s degree at Beijing University of Posts and Telecommunications. His contributions to dual-band power amplifier design, participation in a National Natural Science Foundation of China (NSFC) project, and SCI journal publication highlight his research potential.

🎓 Education:

  • Master’s Candidate in Electrical Engineering (Specialization in Radio Frequency Power Amplifiers)
    Beijing University of Posts and Telecommunications (BUPT), China

💼 Work & Research Experience:

  • Postgraduate Researcher at BUPT, focusing on power radio frequency amplifiers

  • Contributed to National Natural Science Foundation of China (NSFC) projects

  • Publication 📄: SCI-indexed paper in Microelectronics Journal

  • Patent Pending 🔬: “An Output Matching Network for Dual-Band Power Amplifiers” (Application No.: 202411228542.4)

🏆 Achievements & Recognitions:

  • Developed a novel dual-band matching network integrating harmonic control

  • Designed a high-efficiency power amplifier achieving 60.1%–71.8% drain efficiency and 41.5/41.4 dBm output power

  • Demonstrated exceptional bandwidth, linearity, and efficiency with 5G NR signals

  • SCI Journal Publication 📖: Microelectronics Journal (2025, Vol. 156, Article 106552)

🎖 Awards & Honors:

  • Contributor to NSFC-funded research projects 🏅

  • Recognized for innovations in radio frequency circuit design 🔧

  • Patent Filing for advancements in dual-band power amplifier technology 📜

Publication Top Notes:

A novel dual-band power amplifier with integrated harmonic control based on dual transmission lines

Dr. Longbin Jin | Signal Processing Awards | Best Researcher Award

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Dr. Longbin Jin | Signal Processing Awards | Best Researcher Award 

Dr. Longbin Jin, Konkuk University, South Korea

Longbin Jin, is a Ph.D. candidate in Computer Science at Konkuk University, Korea, with an expected graduation in February 2025. His research focuses on adaptive visual prompting for video action recognition in vision-language models under the guidance of Professor Eun Yi Kim. He holds a Master’s degree in Smart ICT Convergence and a Bachelor’s degree in Mechanical Engineering & Automation from Shanghai University, China. Throughout his academic career, Longbin has received numerous accolades, including winning the ICASSP 2023 SPGC Challenge and multiple Excellence and Encouragement Prizes at the Korea Software Congress. Currently, he serves as an AI Researcher at Voinosis in Seoul, where he develops AI models for early detection of hearing loss and cognitive impairment in the elderly. He is also an instructor at Konkuk University, teaching courses on Artificial Intelligence, Computer Vision, and Machine Learning. His project experience includes collaborations on medical imaging and virtual reality, demonstrating his expertise in applying AI technologies across diverse fields. Longbin is proficient in English, Chinese, and Korean, reflecting his international background and commitment to advancing technology in healthcare and education.

Professional Profile:

GOOGLE SCHOLAR

Research for Community Impact Award: Longbin Jin’s Suitability

Longbin Jin is a highly qualified candidate for the Research for Community Impact Award due to his significant contributions in the fields of artificial intelligence and healthcare, particularly in projects that directly benefit the community.

📚 Education

  • Ph.D. in Computer Science
    Konkuk University, Korea
    Expected: February 2025
    Thesis: Adaptive Visual Prompting for Video Action Recognition in Vision-Language Models
    Advisor: Prof. Eun Yi Kim
  • M.S. in Smart ICT Convergence
    Konkuk University, Korea
    Graduated: August 2020
    Thesis: E-EmoticonNet: EEG-based Emotion Recognition with Context Information
    Advisor: Prof. Eun Yi Kim
  • B.S. in Mechanical Engineering & Automation
    Shanghai University, China
    Graduated: August 2018

💼 Work Experience

  • AI Researcher
    Voinosis, Seoul, Korea
    December 2022 – Present

    • Researcher on AI models for early detection of hearing loss and cognitive impairment based on voice analysis for the elderly (VoiceCheck & BrainGuardDoctor Apps).
  • Instructor
    Konkuk University, Seoul, Korea
    March 2022 – Present

    • Teaching courses on Computer Vision, Artificial Intelligence, and Machine Learning.
  • AI Engineer
    Lulla, Seoul, Korea
    October 2022 – November 2022

    • Main researcher for an AI model for a child face-matching system to assist kindergarten teachers (Lulla App).

🏆 Achievements, Awards, and Honors

  • Winner of ICASSP 2023 SPGC Challenge: Multilingual Alzheimer’s Dementia Recognition through Spontaneous Speech (First Author) 🥇
  • Excellence Prize, Korea Software Congress 2023 🥇
  • Encouragement Prize, ACM Student Research Competition, Computer Human Interaction 2020 (First Author) 🎖️
  • Excellence Prize, Korea Software Congress 2019 (First Author) 🏅
  • Encouragement Prize, Korea Software Congress 2019 (First Author) 🎖️
  • Excellent Presentation, International Conference on Culture Technology 2018 🌟

Publication Top Notes:

Interpretable Cross-Subject EEG-Based Emotion Recognition Using Channel-Wise Features†

CITED:29

Consen: Complementary and simultaneous ensemble for alzheimer’s disease detection and mmse score prediction

CITED:15

Eeg-based user identification using channel-wise features

CITED:7

E-EmotiConNet: EEG-based emotion recognition with context information

CITED:2

Emotion Recognition based BCI using Channel-wise Features

CITED:1

 

Kim Bjerge | Signal Processing | Best Researcher Award

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Kim Bjerge | Signal Processing | Best Researcher Award

Mr. Kim Bjerge, Aarhus University, Denmark.

Kim Bjerge is an Associate Professor at Aarhus University in the Department of Electrical and Computer Engineering, specializing in Signal Processing and Machine Learning. With a Ph.D. focused on Computer Vision and Deep Learning for Insect Monitoring, Kim combines academic expertise with significant industry experience. He has held various teaching and leadership positions at Aarhus University and has contributed to research projects in computer vision. His work has resulted in a notable H-index of 14 and 1080 citations on Google Scholar. Kim is dedicated to advancing technology in engineering education and research. 🎓💻📈

Publication Profiles 

Googlescholoar

Education and Experience

  • Ph.D. in Computer Vision and Deep Learning for Insect Monitoring (Aarhus University, 2022 – present) 📚
  • M.Sc. Eng. in Information Technology (Aarhus University, 2013) 📖
  • B. Eng. in Electronics Engineering (Engineering College of Aarhus, 1989) 🔧
  • Associate Professor and Group Leader (Aarhus University, 2021 – present) 🎓
  • Associate Professor and Group Leader, Signal Processing (Aarhus University, 2009 – 2020) 📊
  • Senior Consultant, IT-Development (Danish Technological Institute, 2007 – 2009) 🛠️
  • Software Development Manager (TC Electronic A/S, 1999 – 2007) 🎶
  • System Developer (Crisplant A/S, 1996 – 1999) 📦
  • System Manager (Sam-system A/S, 1989 – 1996) 💼

Suitability For The Award

Mr. Kim Bjerge, Associate Professor at Aarhus University’s Department of Electrical and Computer Engineering, is an exemplary candidate for the Best Researcher Award due to his outstanding contributions to computer vision, deep learning, and signal processing. With a remarkable career spanning academia and industry, he has made groundbreaking advancements in the fields of artificial intelligence, embedded systems, and digital signal processing, impacting both research and application development globally.

Professional Development

Kim Bjerge has pursued extensive professional development through various programs. He completed the Pedagogical Programme in Engineering at the Center for Engineering Education Research and Development, earning 10 ECTS credits. Additionally, he participated in project management training at Provinu and various management courses at Aarhus Business College, enhancing his skills in human resources, organizational strategy, and software engineering. His commitment to ongoing learning ensures that he remains at the forefront of engineering education and technology. 📚🔧🌱

Research Focus

Kim Bjerge’s research focuses on the intersection of computer vision, deep learning, and machine learning, particularly in the context of insect monitoring. His work aims to develop innovative solutions that enhance the understanding and management of ecological systems through advanced image analysis and artificial intelligence techniques. By leveraging his expertise in signal processing, he contributes to the development of cutting-edge technologies that have practical applications in various fields, including agriculture and environmental science. 🌱🔍🤖

Publication Top Notes 

  • Deep learning and computer vision will transform entomology – Cited by: 362, Year: 2021 📖
  • Towards the fully automated monitoring of ecological communities – Cited by: 141, Year: 2022 🌱
  • An automated light trap to monitor moths (Lepidoptera) using computer vision-based tracking and deep learning – Cited by: 119, Year: 2021 🦋
  • Real-time insect tracking and monitoring with computer vision and deep learning – Cited by: 110, Year: 2021 📹
  • A computer vision system to monitor the infestation level of Varroa destructor in a honeybee colony – Cited by: 85, Year: 2019 🐝
  • Accurate detection and identification of insects from camera trap images with deep learning – Cited by: 61, Year: 2023 🔍
  • A living laboratory exploring mobile support for everyday life with diabetes – Cited by: 40, Year: 2010 📱
  • Hierarchical classification of insects with multitask learning and anomaly detection – Cited by: 26, Year: 2023 📊
  • Enhancing non-technical skills by a multidisciplinary engineering summer school – Cited by: 19, Year: 2017 🎓

Prof. Shing-Tai Pan | Signal Processing Awards | Best Researcher Award

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Prof. Shing-Tai Pan | Signal Processing Awards | Best Researcher Award 

Prof. Shing-Tai Pan, National University of Kaohsiung, Taiwan

Shing-Tai Pan, is a distinguished academic in the field of computer science and engineering. He earned his M.S. degree in Electrical Engineering from National Sun Yat-Sen University, Kaohsiung, Taiwan, in 1992, followed by a Ph.D. from National Chiao Tung University, Hsinchu, Taiwan, in 1996. Since 2006, he has been a Professor in the Department of Computer Science and Information Engineering at the National University of Kaohsiung, Taiwan. Prof. Pan is an active member of several professional organizations, including the Taiwanese Association for Artificial Intelligence (TAAI), the Chinese Automatic Control Society (CACS), and The Association for Computational Linguistics and Chinese Language Processing (ACLCLP). His research interests encompass biomedical signal processing, digital signal processing, speech recognition, evolutionary computations, artificial intelligence applications, and intelligent control system design.

Professional Profile:

SCOPUS

ORCID

Summary of Suitability for the Best Researcher Award: Shing-Tai Pan

Shing-Tai Pan is a distinguished academic and researcher whose extensive contributions to the fields of biomedical signal processing, speech recognition, and artificial intelligence make him a highly suitable candidate for the Best Researcher Award. With a career spanning over two decades, his work reflects innovation, collaboration, and a commitment to advancing technology for societal benefits.

Education

  1. M.S. in Electrical Engineering
    • Institution: National Sun Yat-Sen University, Kaohsiung, Taiwan
    • Year: 1992
  2. Ph.D. in Electrical Engineering
    • Institution: National Chiao Tung University, Hsinchu, Taiwan
    • Year: 1996

Work Experience

  1. Department of Computer Science and Information Engineering
    • Position: Professor
    • Institution: National University of Kaohsiung, Kaohsiung, Taiwan
    • Joined: 2006

Professional Memberships

  • Taiwanese Association for Artificial Intelligence (TAAI)
  • Chinese Automatic Control Society (CACS)
  • The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)

Research Interests

  • Biomedical Signal Processing
  • Digital Signal Processing
  • Speech Recognition
  • Evolutionary Computations
  • Artificial Intelligence Applications
  • Intelligent Control Systems Design

Publication Top Notes:

Fuzzy‐HMM modeling for emotion detection using electrocardiogram signals

Performance Improvement of Speech Emotion Recognition Systems by Combining 1D CNN and LSTM with Data Augmentation

Editorial for special issue entitled “CACS2020: Applications of emerging intelligent techniques on modeling and control of modern systems”

Editorial for special section “CACS18: Modelling and control for practical systems”

Efficient robust speech recognition with empirical mode decomposition using an FPGA chip with dual core

 

Dr. Fahman Saeed | Signal Distortion Awards | Best Researcher Award

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Dr. Fahman Saeed | Signal Distortion Awards | Best Researcher Award 

Dr. Fahman Saeed, Imam Mohammad Ibn Saud Islamic University (IMSIU), Saudi Arabia

Dr. Fahman Saeed is an Assistant Professor in the College of Computer and Information Sciences at Imam Mohammad Ibn Saud Islamic University (IMSIU) in Riyadh, Saudi Arabia. With a Ph.D. in Computer Science from King Saud University, his research focuses on deep learning models, particularly for automatic diabetic retinopathy screening. He has contributed significantly to various research projects, including the development of fingerprint interoperability solutions and privacy-protected breast cancer screening systems, earning multiple ISI papers, patents, and conference presentations. Dr. Saeed also has extensive experience in machine learning, specializing in PyTorch, TensorFlow, and large language models. In addition to his academic achievements, he actively participates in professional activities, such as curriculum development and leading workshops on AI, NLP, and generative AI. His dedication to education and research, coupled with his expertise in artificial intelligence, continues to influence both his academic institution and the broader scientific community.

Professional Profile:

ORCID

Suitability for Best Researcher Award: Fahman Saeed

Fahman Saeed is exceptionally suited for the Best Researcher Award due to his outstanding contributions to the field of computer science, particularly in the areas of deep learning, machine learning, and artificial intelligence. With a robust academic background and extensive experience in both research and teaching, Dr. Saeed has demonstrated leadership in advancing the application of machine learning technologies in critical areas like medical diagnostics and data security.

Education 🎓

  • Ph.D. in Computer Science
    • Institution: King Saud University, Saudi Arabia 🎓
    • Graduation: November 2021 📅
    • Dissertation: Developing an auto deep learning model with less complexity and high performance for automatic diabetic retinopathy screening 🧠💻
  • M.Sc. in Computer Science
    • Institution: King Saud University, Saudi Arabia 🎓
    • Graduation: May 2014 📅
  • B.Sc. in Computer Science
    • Institution: King Saud University, Saudi Arabia 🎓
    • Graduation: February 2007 📅

Academic Experience 📚

  • Assistant Professor
    • Institution: College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia 🏫
    • Duration: 2022 to Present ⏳
    • Responsibilities: Teaching courses in Artificial Intelligence 🤖, Natural Language Processing 💬, Algorithm Design and Analysis 💻, Image Processing 🖼️, and Computer Vision 👀
  • Lecturer (Part-time)
    • Institution: King Saud University, Riyadh, Saudi Arabia 🎓
    • Duration: 2017 to 2021 ⏳
  • Researcher
    • Institution: King Saud University, Riyadh, Saudi Arabia 🧪
    • Duration: March 2015 to 2021 ⏳
    • Projects:
      • Automatic Diabetic Retinopathy Screening 🩺👁️
        • Achievements: Two ISI papers 📄
      • Identification of Fingerprint Interoperability 🧑‍⚖️
        • Achievements: One patent, one ISI paper, two conference papers 📑
      • Cloud-Based Privacy-Protected Computer-Aided Diagnosis System for Breast Cancer Screening 🩻
        • Achievements: One ISI paper 📄

Publication Top Notes

Adaptive Renewable Energy Forecasting Utilizing a Data-Driven PCA-Transformer Architecture

Blockchain-Based Quality Assurance System for Academic Programs
Optimal Sizing and Placement of Distributed Generation under N-1 Contingency Using Hybrid Crow Search–Particle Swarm Algorithm
A Data-Driven Convolutional Neural Network Approach for Power Quality Disturbance Signal Classification (DeepPQDS-FKTNet)

Designing the Architecture of a Convolutional Neural Network Automatically for Diabetic Retinopathy Diagnosis

 

Prof. Miao Zhang | Signal Localization Awards | Best Researcher Award

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Prof. Miao Zhang | Signal Localization Awards | Best Researcher Award 

Prof. Miao Zhang, Xiamen University, China

Miao Zhang is a Professor at Xiamen University, Fujian, China, specializing in electrical and electronic engineering. He earned his B.S., M.S., and D.E. degrees from the Tokyo Institute of Technology, Japan, in 2003, 2005, and 2008, respectively. From 2005 to 2008, he was a Research Fellow of the Japan Society for the Promotion of Science and subsequently served as a Researcher and Assistant Professor at the Tokyo Institute of Technology until 2016, when he joined Xiamen University as an Associate Professor. His research focuses on glass-based antenna-in-package, millimeter-wave and THz antennas, and array antennas for 5G and car radar applications. Dr. Zhang has received several prestigious awards, including the Best Letter Award from the IEICE Communication Society (2009), the Young Engineer Award from the IEICE Technical Committee on Antennas and Propagation (2010), the IEEE AP-S Japan Chapter Young Engineer Award (2011), and the Best Paper Award at the 9th European Conference on Antennas and Propagation (2015). He is a Senior Member of IEEE, CIE, and IEICE.

Professional Profile:

SCOPUS

Summary of Suitability for the Best Researcher Award

Miao Zhang is a highly accomplished researcher in electrical and electronic engineering, with significant contributions to the fields of millimeter-wave and terahertz antennas, 5G applications, and automotive radar systems. His profile demonstrates extensive academic achievements, impactful research output, and a strong record of professional recognition.

🎓 Education:

  • B.S. in Electrical and Electronic Engineering 🎓 – Tokyo Institute of Technology 🇯🇵, 2003.
  • M.S. in Electrical and Electronic Engineering 🎓 – Tokyo Institute of Technology 🇯🇵, 2005.
  • D.E. in Electrical and Electronic Engineering 🎓 – Tokyo Institute of Technology 🇯🇵, 2008.

🔬 Career Milestones:

  • 2005–2008: Research Fellow at Japan Society for the Promotion of Science (JSPS) 🇯🇵.
  • 2008–2013: Researcher at the Tokyo Institute of Technology.
  • 2013: Promoted to Assistant Professor at Tokyo Institute of Technology.
  • 2016: Joined Xiamen University as an Associate Professor.

📡 Research Interests:

  • Glass-based antenna-in-package 📦.
  • Millimeter-wave 📶 and THz antennas 🌌.
  • Array antennas for 5G 📱 and car-radar 🚗 applications.

🏆 Awards and Recognitions:

  • 2009 🏅: Best Letter Award – IEICE Communication Society.
  • 2010 🥇: Young Engineer Award – IEICE Technical Committee on Antennas and Propagation.
  • 2011 ⚡: IEEE AP-S Japan Chapter Young Engineer Award.
  • 2015 📜: Best Paper Award – 9th European Conference on Antennas and Propagations.

Publication Top Notes

Development of CGA-PWW Devices Based on Advanced Wafer-Level Processing Technology

An Air-Filled Double-Sided Gap Waveguide Based on Glass Packaging for mm-W Applications

Solder-Free Si-Based mm-W Metallic Waveguide Based on Scaleable Dumbbell-Shaped Holey-EBG Structures

A Waveguide Cavity Antenna for Automotive 4D Millimeter-Wave Radar Applications

A Novel Dual-Linearly-Polarized Quadrifilar Helix Antenna

Self-Decoupled Coupled Line Antenna Pair (CLAP)

Development of Low-Loss and Low-Cost Air-Filled Transmission Lines based on Advanced Glass Wafer Packaging

Dr. B. Omkar Lakshmi Jagan | Signal Estimation Award | Best Researcher Award

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Dr. B. Omkar Lakshmi Jagan | Signal Estimation Award | Best Researcher Award 

Dr. B. Omkar Lakshmi Jagan, Vignan’s Institute of Information Technology, India

Dr. Banana Omkar Lakshmi Jagan is an accomplished academic and researcher in the field of Statistical Signal Processing, with a Ph.D. from Koneru Lakshmaiah Education Foundation. Currently serving as an Assistant Professor in the Department of Computer Science Engineering at Vignan’s Institute of Information Technology, Dr. Jagan has a diverse teaching and research background. His previous roles include Assistant Professor in Artificial Intelligence and Machine Learning at Malla Reddy University and research positions with the NRB-DRDO projects focused on submarine target motion analysis and performance evaluation of algorithms. With over five years of research experience and nearly two years in teaching, Dr. Jagan has specialized in Deep Learning, Machine Learning, Linux Programming, and IoT. He has also earned additional certifications in Deep Learning and IoT from NPTEL. His commitment to both academic excellence and innovative research drives his career in exploring advanced technologies and methodologies in his field.

Professional Profile:

Suitability for the Best Researcher Award:

Dr. Banana Omkar Lakshmi Jagan has demonstrated significant achievements in research, teaching, and contributions to multiple domains, particularly in Statistical Signal Processing, Machine Learning, Deep Learning, and Target Tracking. Based on his extensive academic background, research projects, and publications, he is a strong candidate for the Best Researcher Award.

Education 

  • Ph.D. in Statistical Signal Processing
    2023
    Koneru Lakshmaiah Education Foundation (Deemed to be University), Andhra Pradesh
  • M.Tech. in Power Systems
    2016
    Koneru Lakshmaiah Education Foundation (Deemed to be University), Andhra Pradesh
  • B.Tech. in Electrical and Electronics Engineering
    2014
    Sri Sivani College of Engineering, JNTU Kakinada, Andhra Pradesh
  • Intermediate (M.P.C)
    2008
    Board of Intermediate Education, Andhra Pradesh
  • Xth Grade
    2006
    Council for the Indian School Examinations, Delhi

Work Experience

  1. Assistant Professor
    Department of Computer Science Engineering
    Vignan’s Institute of Information Technology (A), Duvvada, Visakhapatnam, Andhra Pradesh, India
    May 22, 2024 – Present
  2. Assistant Professor
    Department of Artificial Intelligence and Machine Learning, Department of Computer Science Engineering
    School of Engineering, Malla Reddy University, Hyderabad, Telangana, India
    December 28, 2022 – May 22, 2024
  3. Research Associate (RA)
    NSTL-DRDO Project, Department of Electronics and Communication Engineering
    Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India
    July 17, 2022 – December 27, 2022
    Project Title: Performance Evaluation of all TMA Algorithms for Bot & Calculation of MLA & SOA for Identified Zigging Targets
  4. Senior Research Fellow (SRF)
    NRB-DRDO Project, Department of Electronics and Communication Engineering
    Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India
    July 9, 2021 – January 8, 2022
    Project Title: State of Art Submarine Target Motion Analysis
  5. Junior Research Fellow (JRF)
    NRB-DRDO Project, Department of Electronics and Communication Engineering
    Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India
    July 9, 2019 – July 8, 2021
    Project Title: State of Art Submarine Target Motion Analysis
  6. Junior Research Fellow (JRF)
    NRB-DRDO Project, Department of Electronics and Communication Engineering
    Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India
    July 12, 2016 – July 11, 2018
    Project Title: Advance Submarine Target Motion Analysis

Publication top Notes:

CITED:56
CITED:26
CITED:21
CITED:18
CITED:13
CITED:11

Assist Prof Dr. Hwa-Dong Liu | Signal Processing | Best Researcher Award

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Assist Prof Dr. Hwa-Dong Liu | Signal Processing | Best Researcher Award

Assist Prof Dr. Hwa-Dong Liu, Undergraduate Program of Vehicle and Energy Engineering, National Taiwan Normal University, Taiwan

Hwa-Dong Liu is an Assistant Professor at National Taiwan Normal University (NTNU) in Taipei, Taiwan, specializing in power electronics, microcontrollers, rail vehicle power systems, and solar power systems. He holds a Ph.D. in Electrical Engineering from National Taiwan University of Science and Technology (NTUST). His research interests include the development of advanced power converters, control strategies for renewable energy systems, and innovative solutions for electric vehicle charging. Dr. Liu has authored numerous papers in reputable journals, with a focus on improving the efficiency and performance of power electronic systems and renewable energy technologies. His recent work includes contributions to energy management systems, high-gain boost converters, and novel MPPT algorithms for solar power generation.

Professional Profile:

Summary of Suitability for Best Researcher Award 

Hwa-Dong Liu has expertise in several cutting-edge fields including power electronics, microcontrollers, rail vehicle power systems, and solar power systems. This diversity indicates a broad impact on multiple important areas of research.

Education

  • Ph.D. in Electrical Engineering from National Taiwan University of Science and Technology (NTUST).

Work Experience

  • Assistant Professor at National Taiwan Normal University (NTNU).

Expertise

  1. Power Electronics
  2. Microcontroller
  3. Rail Vehicle Power Systems
  4. Solar Power Systems

Publication top Notes:

An improved solar step-up power converter for next-generation electric vehicle charging

Hybrid Management Strategy for Outsourcing Electromechanical Maintenance and Selecting Contractors in Taipei MRT

An Improved High Gain Continuous Input Current Quadratic Boost Converter for Next-Generation Sustainable Energy Application

Novel MPPT algorithm based on honey bees foraging characteristics for solar power generation systems

High-Voltage Autonomous Current-Fed Push-Pull Converter with Wireless Communication Applied to X-Ray Generation