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 🎓

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

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:📄