Mr. Mingjian Zhu | Microwave Photonics Awards | Best Researcher Award

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Mr. Mingjian Zhu | Microwave Photonics Awards | Best Researcher Award 

Mr. Mingjian Zhu, Beijing Jiaotong University, China

Mingjian Zhu is a postgraduate researcher at the Institute of Lightwave Technology, Beijing Jiaotong University, specializing in optical fiber sensing. He holds a Master’s degree in Information and Communication Engineering and has been actively engaged in fiber optic sensing research for three years. His primary research focus is on optical fiber magnetic field sensing based on optoelectronic oscillators (OEO). Throughout his academic journey, he has contributed to publications indexed in Scopus and other reputable databases, participated in research projects, and filed a patent. His work aims to advance the field of fiber optic sensing technology with applications in precision measurement and industrial sensing. Mingjian Zhu continues to explore innovative solutions in optical sensing, contributing to research and development in this rapidly evolving domain.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award  

Mingjian Zhu has demonstrated a strong foundation in fiber optic sensing research, particularly in optical fiber magnetic field sensing based on optoelectronic oscillators (OEO). While he is still in the early stages of his research career, his commitment to innovation and academic contributions highlight his potential as a promising researcher in the field.

🎓 Education:

  • Master’s Degree in Fiber Optic Sensing – Beijing Jiaotong University (Ongoing)
  • Bachelor’s Degree in Information and Communication Engineering – Beijing Jiaotong University

💼 Work Experience:

  • Postgraduate Researcher at the Institute of Lightwave Technology, Beijing Jiaotong University (Since 2022)
  • 3 Years of Experience in Fiber Optic Sensing, specializing in Magnetic Field Sensing Based on Optoelectronic Oscillators (OEO)

🏆 Achievements & Research Contributions:

  • 📄 1 Journal Publication indexed in Scopus/Web of Science
  • 🔬 1 Research Project completed and ongoing
  • 💡 1 Patent published or under process
  • 📖 1 Journal Publication in other indexing databases
  • 🎤 Conference Presentations in the field of fiber optic sensing

🏅 Awards & Honors:

  • Nominated for Best Research Scholar Award
  • Recognition in the field of Optical Fiber Magnetic Field Sensing
  • Contributing to Research & Innovation in Optoelectronics and Sensing Technology

Publication Top Notes:

High-Sensitivity Magnetic Field Sensor Based on an Optoelectronic Oscillator with a Mach–Zehnder Interferometer

 

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

 

Mr. Rifa Asyari | Signal Processing Awards | Best Researcher Award

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Mr. Rifa Asyari | Signal Processing Awards | Best Researcher Award

Mr. Rifa Asyari, University of Southern Denmark, Denmark.

Rifa Atul Izza Asyari is a highly skilled RF Engineer with over four years of hands-on experience in designing, analyzing, and optimizing advanced RF systems such as radar, RF front-end modules, metasurfaces, and antennas. He is currently pursuing a Ph.D. in Biomedical Engineering at the University of Southern Denmark, with his research focused on radar technology for vital sign monitoring, and is set to graduate in December 2024. He holds an M.Sc. in Telecommunication Engineering from National Sun Yat-Sen University, Taiwan, where he developed high-gain array antennas with frequency-selective surfaces, and a B.Sc. in Electrical Engineering from Universitas Islam Indonesia, Indonesia, with a thesis on optical network design for 4G LTE systems.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award

Rifa Atul Izza Asyari demonstrates an exemplary profile as a highly skilled RF Engineer and researcher with significant contributions in academia and industry. Here’s why Rifa is an excellent candidate for the Best Researcher Award

🎓 Education:

  • PhD in Biomedical Engineering 🏫
    University of Southern Denmark (Odense, Denmark)
    📅 Expected Completion: Dec 2024
    📑 Thesis: Radar for Vital Sign Monitoring
  • MSc in Telecommunication Engineering 📡
    National Sun Yat-Sen University (Kaohsiung, Taiwan)
    📅 June 2019
    📑 Thesis: High Gain Array Antenna with Frequency Selective Surface for Vital Sign Monitoring
  • BSc in Electrical Engineering ⚡
    Universitas Islam Indonesia (Yogyakarta, Indonesia)
    📅 Feb 2016
    📑 Thesis: Optical Network Design for 4G Long Term Evolution Sleman

💼 Work Experience:

  • Senior Hardware R&D Engineer ⚙️ at Pegatron (Batam, Indonesia)
    📅 Sept 2019 – Jan 2022

    • Designed and validated RF front-end WiFi modules and IP cameras.
    • Improved broadband performance by 40% and optimized key metrics like EVM and BER.
    • Conducted DVT, OTA measurements, and troubleshooting for WiFi and 5G communication standards.
  • Fibre Optic Engineer 🌐 at Biznet Networks (Yogyakarta, Indonesia)
    📅 May 2016 – Jun 2017

    • Planned and designed fiber-optic network architectures.
    • Conducted fusion splicing and troubleshooting using OTDR.
  • Heavy Dump Truck Operator 🚛 at Pamapersada Nusantara (Tabalong, Indonesia)
    📅 Jan 2010 – Sept 2012

    • Operated Komatsu trucks for open-cast mining operations.

🏆 Achievements:

  • 🏅 Best Student Paper Award at Taiwan Telecommunication Annual Symposium (2020)
  • 🌟 Top 50 Online Global Startup Weekend Unite to Fight COVID-19 (2020)
  • 📜 IMPTE Scholarship Award at National Sun Yat-Sen University (2017)

🔧 Technical Skills:

  • Programming: 🖥️ MATLAB, Python, C/C++, R
  • RF Tools: 📡 CST, Ansys, ADS, Spectrum Analyzer
  • Networking: 🌐 LAN/WAN, TCP/IP, VPN
  • Soft Skills: 🗣️ Leadership, Problem-solving, Presentation

Publication Top Notes:

High Gain Array Antenna With FSS for Vital Sign Monitoring Through the Wall

Prof. Xiaolei Wang | Signal Processors Award | Best Researcher Award

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Prof. Xiaolei Wang | Signal Processors Award | Best Researcher Award

Prof. Xiaolei Wang, Beijing University of Technology, China

Dr. Wang Xiaolei is a distinguished Associate Professor in the College of Physics and Optoelectronics at Beijing University of Technology, where she has been a faculty member since June 2019. With a strong background in materials science, she obtained her Ph.D. from the City University of Hong Kong in 2013, following her Master’s degree from Renmin University of China and her Bachelor’s degree from Northwestern Polytechnical University. Prior to her current role, she served as an Assistant Professor and later an Associate Professor at the Institute of Semiconductors, Chinese Academy of Sciences, from August 2013 to June 2019, and as an Academic Visitor at the University of Cambridge’s Department of Materials Science & Metallurgy. Dr. Wang’s research focuses on spintronic devices, magnetic semiconductors, resistive switching, and novel two-dimensional electronics. She is actively involved in the academic community as a permanent member of the Chinese Physical Society, Beijing Optical Society, and Beijing Cross Society, and serves as the Deputy Director of the Optical Society Youth Council. Additionally, she contributes as an Associate Editor for the Journal of Superconductivity and Novel Magnetism and a Guest Editor for multiple journals, including Symmetry.

Professional Profile:

Summary of Suitability for Best Researcher Award:

Wang Xiaolei, a distinguished Professor in Chemistry and Material Science, has a remarkable research portfolio and extensive contributions to various cutting-edge fields, which make her an excellent candidate for the Best Researcher Award. Her work primarily focuses on spintronics, magnetic semiconductors, resistive switching, molecular spintronics, and two-dimensional electronics.

Education

  • Ph.D. in Physics and Materials Science
    City University of Hong Kong, Hong Kong
    August 2010 – July 2013
  • Master’s Degree in Physics
    Renmin University of China, Beijing, China
    September 2007 – July 2010
  • Bachelor’s Degree in Applied Physics
    Northwestern Polytechnical University, Xi’an, Shanxi, China
    September 2002 – July 2006

Work Experience

  • Associate Professor
    College of Physics and Optoelectronics, Faculty of Science
    Beijing University of Technology, Beijing, China
    June 19, 2019 – Present

    • Conducting research and teaching in spintronics and optoelectronics.
  • Assistant Professor / Associate Professor
    State Key Laboratory of Superlattices and Microstructures
    Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China
    August 1, 2013 – June 18, 2019

    • Engaged in research on semiconductor materials and spintronic devices.
  • Academic Visitor
    Department of Materials Science & Metallurgy
    University of Cambridge, Cambridge, Cambridgeshire, United Kingdom
    January 5, 2013 – July 5, 2013

    • Participated in collaborative research projects in materials science.

Research Areas:

Dr. Wang’s research spans a diverse range of topics:

  1. Spintronic devices 🌀
  2. Magnetic semiconductors 🧲
  3. Resistive switching 🔄
  4. Molecular spintronics 🧬
  5. Transition metal ferromagnets ⚛️
  6. Novel two-dimensional electronics 📏

Honors:

Dr. Wang has received several prestigious awards for her contributions to science:

  • Young Changjiang Scholars Award Program, Ministry of Education (2023) 🎓
  • Advisor of Outstanding Master’s Degree Thesis (2021) 🏆
  • Youth Promotion Association of the Chinese Academy of Sciences (2018) 🌟
  • Research Tuition Scholarship (2011 and 2012) 💰
  • Outstanding Academic Performance Award (2012 and 2013) 📚
  • Excellent Graduation Thesis Award (2010) 🎖️

Publication top Notes:

Local manipulation of skyrmion lattice in Fe3GaTe2 at room temperature

The performance of ultraviolet solar-blind detection of p-Si/n-Ga2O3 heterojunctions with/without hole-blocking layer

Thickness- and Field-Dependent Magnetic Domain Evolution in van der Waals Fe3GaTe2

Determination of Enantiomeric Excess by Optofluidic Microlaser near Exceptional Point

Study on the structural, optical and electrical properties of N-doped Ga2O3 films synthesized by sol-gel method

Mechanical manipulation for ordered topological defects

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

 

 

 

Mr. Yeonjae Park | Signal Cleaning Award | Best Scholar Award

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Mr. Yeonjae Park | Signal Cleaning Award | Best Scholar Award

Mr. Yeonjae Park, The Graduate School of Yonsei University, South Korea

Yeonjae Park is a Master’s student at Yonsei University in the Department of Medical Informatics and Biostatistics, under the guidance of Professor Dae Ryong Kang. With a strong foundation in Computer and Telecommunication Engineering as well as Information and Statistics, Park obtained dual B.S. degrees from Yonsei University, where they were mentored by Professors Cho Young-rae and Na Seongyong. Their research interests span machine learning, deep learning, generative models, multi-modal data analysis, and time series forecasting. Park has gained valuable research experience through various positions, including as a researcher intern at the Artificial Intelligence-Information Retrieval Lab, a researcher at the Applied Data Science Lab, and their current role at the National Health BigData Clinical Research Institute. Their projects encompass a range of topics, from text extraction and OCR recognition to complex analyses in genomics, disease correlations, and the effectiveness of medical treatments.

Professional Profile:

Summary of Suitability for Best Scholar Award:

Yeonjae Park has a strong academic foundation, holding dual Bachelor’s degrees in Computer and Telecommunication Engineering and Information and Statistics from Yonsei University, one of South Korea’s most prestigious institutions. Currently, Yeonjae is pursuing a Master’s degree in Medical Informatics and Biostatistics at the same university, under the guidance of a notable advisor, Dae Ryong Kang.

Education 📚

  • Samseon Middle School, Seoul, Korea (Mar. 2010 ~ Jul. 2010)
  • SungSan Middle School, Seoul, Korea (Jul. 2010 ~ Feb. 2013)
  • Kwangsung High School, Seoul, Korea (Mar. 2013 ~ Feb. 2016)
  • Yonsei University, Department of Computer and Telecommunication Engineering 🖥️ (Mar. 2016 ~ Aug. 2021)
    • B.S. in Computer and Telecommunication Engineering
    • Advisor: Prof. Cho Young-rae
  • Yonsei University, Department of Information and Statistics 📊 (Feb. 2016 ~ Aug. 2021)
    • B.S. in Information and Statistics
    • Advisor: Prof. Na Seongyong
  • Yonsei University, Department of Medical Informatics and Biostatistics 🧬 (Aug. 2021 ~ Present)
    • Master Student
    • Advisor: Prof. Dae Ryong Kang

Research Interests 🔍

  • Machine Learning / Deep Learning 🤖
  • Generative Models 🌀
  • Multi Modal 🧠
  • Time Series Forecasting ⏳

Research Experiences 💼

  • Researcher Intern at Artificial Intelligence-Information Retrieval Lab, Yonsei University, Korea (May. 2019 ~ Apr. 2020)
  • Researcher at Applied Data Science Lab, Yonsei University, Korea (May. 2020 ~ Jan. 2021)
  • Researcher at National Health BigData Clinical Research Institute, Korea (Jan. 2021 ~ Present)

 

Publication top Notes:

Development and Validation of a Real-Time Service Model for Noise Removal and Arrhythmia Classification Using Electrocardiogram Signals

Intracardiac Echocardiogram: Feasibility, Efficacy, and Safety for Guidance of Transcatheter Multiple Atrial Septal Defects Closure

 

 

 

Dr. Zhigang Zhu | Signal Processing Award | Best Researcher Award

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Dr. Zhigang Zhu | Signal Processing Award | Best Researcher Award

Dr. Zhigang Zhu, Xidian University, China

Zhigang Zhu, born on October 27, 1989, is a distinguished postdoctoral researcher in the School of Electronic Engineering at Xidian University. With a robust educational foundation, Zhigang holds a Ph.D. in Control Science and Engineering from Xidian University. His academic journey began at Qingdao University of Technology, where he earned his undergraduate degree in Telecommunication Engineering in 2009.Zhigang’s expertise lies in deep learning and signal processing, with a keen focus on signal representation and recognition. His research achievements are substantial, having published over 20 SCI-indexed papers in prestigious journals such as Remote Sensing, IEEE TAES, IEEE TIM, and IEEE SPL. He is a recognized member of both the Chinese Institute of Electronics (CIE) and the Institute of Electrical and Electronics Engineers (IEEE).

Professional Profile

🎓 Education & Academic Achievements:

I hold a Ph.D. in Control Science and Engineering from Xidian University, completed in 2015. I began my academic journey with a Bachelor’s degree in Telecommunication Engineering from Qingdao University of Technology in 2009. Currently, I am a postdoctoral researcher in the School of Electronic Engineering at Xidian University. My specialization lies in deep learning and signal processing, particularly in signal representation and signal recognition.

📚 Experience & Professional Engagements:

Since 2015, I have been deeply involved in research and academia. I have led numerous projects, including a significant initiative by the National Natural Science Foundation of China focused on deep learning. My work in electronics science and technology has earned me accolades such as the Shaanxi Higher Education Institutions Scientific Research Outstanding Achievement Award. Additionally, I have made substantial contributions to the field by publishing over 20 SCI-indexed papers in renowned journals like IEEE TAES and IEEE TIM.

🌐 Research & Contributions:

My research interests include computer vision, signal processing, and deep learning. I have been recognized with multiple national and provincial awards for my innovative research and entrepreneurial efforts. As a member of both the Chinese Institute of Electronics (CIE) and the Institute of Electrical and Electronics Engineers (IEEE), I actively contribute to the scientific community. I have also guided a student team to win prestigious awards in competitions such as the Shaanxi Provincial Internet+ Innovation and Entrepreneurship Competition.

🏆 Recognition & Impact:

My dedication to advancing technology and fostering innovation has been recognized through various awards, including the Excellence Award at the National Post-Doctoral Innovation and Entrepreneurship Competition. I strive to inspire the next generation of researchers and apply my work for the benefit of society.

 

.Publications Notes:📄