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

 

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. Qiang Yu | Signal Theory Award | Best Researcher Award

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Mr. Qiang Yu | Signal Theory Award | Best Researcher Award

Mr. Qiang Yu, Shanxi Normal University, China

Dr. Qiang Yu is a distinguished professor in the Department of Mathematical Sciences at Shanxi Normal University, China. With a solid academic foundation, Dr. Yu obtained his B.S. in Mathematics Education from Shi He Zi University in 2003, followed by an M.S. in Applied Mathematics and a Ph.D. in Basic Mathematics from Shaanxi Normal University in 2009 and 2014, respectively. His doctoral research, under the guidance of Professor Baowei Wu, focused on nonlinear systems, stability, stabilization, and control. Dr. Yu’s professional career began as a mathematics teacher at Fukang No.1 Senior School in Xinjiang. He then advanced to academic positions at Heng Shui University and Shaanxi Normal University, where he steadily rose through the ranks from Lecturer to Associate Professor, and ultimately to Professor in December 2023. He also served as a visiting professor at the Shibaura Institute of Technology in Japan from 2019 to 2020, collaborating with Prof. Guisheng Zhai.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award

Dr. Qiang Yu demonstrates an exceptional academic and professional background that makes him highly suitable for the Best Researcher Award. His educational foundation in mathematics (B.S., M.S., and Ph.D. from Shi He Zi University and Shaanxi Normal University) underpins his rigorous work in complex areas like control theory, dynamical systems, and nonlinear systems. He has further specialized in switched systems, robust control, and time-delay systems—highly relevant research areas with widespread applications in engineering and mathematics.

📚 Academic Background

  • 🎓 B.S. in Mathematics Education (1999-2003) – Shi He Zi University
  • 🎓 M.S. in Applied Mathematics (2006-2009) – Shaanxi Normal University
  • 🎓 Ph.D. in Basic Mathematics (2011-2014) – Shaanxi Normal University
    • 📑 Advisor: Professor Baowei Wu
    • 🔍 Research Theme: Nonlinear Systems, Stability, Stabilization, and Control

🏫 Professional Experience

  • 🧑‍🏫 Math Teacher – Fukang No.1 Senior School, Xinjiang (2003-2006)
  • 📈 Lecturer – Heng Shui University, Hebei (2009-2011)
  • 🎓 Lecturer, Associate Professor, and Professor – Shaanxi Normal University, Shanxi (2014-present)
  • 🌏 Visiting Professor – Shibaura Institute of Technology, Saitama, Japan (2019-2020)

🔬 Research Interests

  • 🛠️ Switched Systems
  • 📏 Robust Control
  • ⏳ Time-Delay Systems
  • 📊 Control Theory and Engineering
  • 🧮 Applied Mathematics
  • 🔄 Dynamical Systems
  • 🤖 Neural Networks

🌐 Professional Memberships and Activities

  • 🔍 Reviewer for Mathematical Reviews
  • 🏅 Member, IEEE Control Systems Society
  • 🧩 Member, Chinese Mathematical Society
  • 🤖 Member, Chinese Association of Automation
  • 🇨🇳 Member, Society of Industry and Applied Mathematics of China
  • ✒️ Editorial Board Member, American Journal of Applied Mathematics (Since 2020)

🏆 Honors and Awards

  • 🥇 First Prize Gardener’s Scholarship, Shaanxi Normal University (2013)
  • 🥈 Second Prize in National College Student Academic Competitions (2013)
  • 🎖️ National Scholarship for Doctoral Students, Ministry of Education of China (2013)
  • 🏅 Excellent Postgraduate Student Award, Shaanxi Normal University (2014)
  • 🥉 Third Prize in Teachers’ Skills Competition, Shanxi Normal University (2015)
  • 🥈 Second Prize in National Mathematics Micro Course Design Competition (2016)
  • 🌟 Advanced Individual for Educational Excellence, Shanxi Normal University (2017)
  • 🥉 Third Prize for Excellent Academic Paper, Shanxi Science and Technology Department (2018)
  • 🥇 First Prize Science and Technology Award, Shaanxi Higher Education Institutions (2019)
  • 🏆 Second Prize of the Natural Science Award, Shaanxi Science and Technology (2022)

Publication top Notes:

Sampled-data synchronization of delayed multi-agent networks and its application to coupled circuit

CITED:62

Analysis of mixed convection flow in an inclined lid-driven enclosure with Buongiorno’s nanofluid model

CITED:56

Stability analysis for discrete-time switched systems with stable and unstable modes based on a weighted average dwell time approach

CITED:45

Coiflets solutions for Föppl-von Kármán equations governing large deflection of a thin flat plate by a novel wavelet-homotopy approach

CITED:39

Robust stability analysis of uncertain switched linear systems with unstable subsystems

CITED:38

Stability analysis of discrete-time switched linear systems with unstable subsystems

CITED:36

Dr. Zhengjia Xu | Signal Analysis Award | Best Researcher Award

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Dr. Zhengjia Xu | Signal Analysis Award | Best Researcher Award

Dr. Zhengjia Xu, Cranfield University, United Kingdom

Dr. Zhengjia Xu is an accomplished Electronic and Embedded Software Engineer with a rich blend of academic and industrial experience. He holds a Ph.D. in Aerospace from Cranfield University, where his research focused on cognitive communication and intelligent DSP for drone applications. Dr. Xu has a strong track record of over 25 peer-reviewed publications, including influential journal articles and conference papers in fields such as intelligent signal processing and aerospace engineering. Currently, he serves as a Research Fellow at Cranfield University, specializing in position, navigation, and timing systems, and has led several high-profile projects funded by ESA and EPSRC. His prior roles include Senior RF Engineer at Drone Defense Services Ltd, where he made significant advancements in passive RF radar and SDR-based receivers, and Electronic and Embedded Software Engineer at ASH Wireless (Captec LTD), where he developed advanced NB-IoT products and embedded firmware.

Professional Profile:

Summary of Suitability for the Best Researcher Award

Zhengjia Xu has a comprehensive technical and research background, demonstrating expertise in both industrial and academic settings. His experience spans a range of areas including embedded software development, digital system design, RF analysis, and intelligent signal processing.

Education

Ph.D. in Aerospace Engineering
Cranfield University, Cranfield, UK
September 2017 – March 2021

  • Research Area: Cognitive communication, intelligent DSP, drone communication
  • Thesis: “Cognitive Communication for UAV Applications”
  • Proposed a DSP algorithm enabled by deep learning for RF fingerprint identification, simulated air-to-ground communication performance, and proposed system architectures for UAV communications.

M.Sc. in Vehicle Operation Design
Nanjing University of Aeronautics and Astronautics, Nanjing, China
September 2014 – June 2017

  • Research Area: Aircraft modeling and control, fault-tolerant control
  • Simulated aircraft aerodynamic models, developed aircraft control algorithms, and analyzed real flight data. Involved in PCB layout design and the development of flight simulators.

Bachelor in Electrical and Electronics Engineering
Nanjing University of Aeronautics and Astronautics, Nanjing, China
September 2010 – June 2014

  • Thesis: “Research on Stability and Control of Quadratic Aircraft Based on STM32F407”
  • Designed PID-based flight control software on a self-designed PCB board with STM32 MCU.

Work Experience

Research Fellow in Position, Navigation, and Timing
Cranfield University, Bedford, UK
March 2023 – Present

  • Managed projects with stakeholders including Telespazio – Thales UK, European Space Agency, and others.
  • Co-supervised over 10 MSc and PhD student projects.
  • Main researcher for two ESA-funded projects and one EPSRC-funded 6G project.
  • Delivered lectures and developed course materials for 13 hours across four modules.

Senior RF Engineer
Drone Defense Services Ltd, Retford, UK
March 2022 – March 2023

  • Developed passive RF radar products, including software refactoring and hardware integration.
  • Improved radar detection range significantly and led the design of an SDR-based OFDM receiver.
  • Proficient in SDR developments and GPU platform optimization.

Electronic and Embedded Software Engineer
ASH Wireless (Captec LTD), Southampton, UK
March 2021 – March 2022

  • Developed an NB-IoT product for air-to-ground communication.
  • Customized IoT protocol suite and performed schematic design and RF validation.
  • Experienced in STM ARM Cortex-based embedded application developments.

Volunteer, IET Aerospace TN Committee
Institution of Engineering and Technology (IET)
September 2022 – Present

  • Participated in strategic planning and board meetings for the aerospace technical network.

Publication top Notes:

CITED:15
CITED:13
CITED:12
CITED:8
CITED:8

Mr. Lin Li | Compressive Sensing Award | Best Innovation Award

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Mr. Lin Li | Compressive Sensing Award | Best Innovation Award

Mr. Lin Li, Chengdu University of Technology, China

Li Lin received his M.S. degree in Educational Technology from Sichuan Normal University in Chengdu, China, in 2011. He is currently pursuing a Ph.D. in Earth Exploration and Information Technology at the same institution. His research interests focus on machine learning theory and 3D point cloud processes. From July 2011 to July 2019, Li Lin worked as a Senior Engineer specializing in production design at ThinkGeo (US) Science and Technology Co., Ltd. in Chengdu, Sichuan. With a strong background in computer science, Li Lin continues to contribute to the fields of technology and research.

Professional Profile:

 

Summary of Suitability for Best Innovation Award:

Li Lin’s background and research accomplishments demonstrate significant expertise and innovation in the field of 3D point cloud processes, particularly in machine learning and LiDAR technology. His academic journey, with an M.S. degree in educational technology and current Ph.D. studies in Earth exploration and information technology, shows his commitment to advancing technological solutions in a complex and emerging area. His research focuses on applying machine learning theory to 3D point cloud processing, which is crucial for various applications like geospatial analysis and environmental monitoring.

Education:

  • Master’s Degree in Educational Technology
    • Institution: Sichuan Normal University, Chengdu, China
    • Duration: September 1, 2008, to July 1, 2011
  • Ph.D. in Earth Exploration and Information Technology (Pursuing)
    • Institution: Sichuan Normal University, Chengdu, China
    • Current Status: Ongoing

Work Experience:

  • Senior Engineer (Production Design)
    • Company: ThinkGeo (US) Science and Technology Co., Ltd., Chengdu, Sichuan, China
    • Duration: July 1, 2011, to July 3, 2019

Research Interests:

  • Machine Learning Theory
  • 3D Point Cloud Processes

This outlines Li Lin’s career trajectory and expertise in both education and industry

Publication top Notes:

Compressing and Recovering Short-Range MEMS-Based LiDAR Point Clouds Based on Adaptive Clustered Compressive Sensing and Application to 3D Rock Fragment Surface Point Clouds

 

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:📄