Kim Bjerge | Signal Processing | Best Researcher Award

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.ย ๐ŸŽ“๐Ÿ’ป๐Ÿ“ˆ

Publication Profilesย 

Googlescholoar

Education and Experience

  • Ph.D. in Computer Vision and Deep Learning for Insect Monitoringย (Aarhus University, 2022 – present)ย ๐Ÿ“š
  • M.Sc. Eng. in Information Technologyย (Aarhus University, 2013)ย ๐Ÿ“–
  • B. Eng. in Electronics Engineeringย (Engineering College of Aarhus, 1989)ย ๐Ÿ”ง
  • Associate Professor and Group Leaderย (Aarhus University, 2021 – present)ย ๐ŸŽ“
  • Associate Professor and Group Leader, Signal Processingย (Aarhus University, 2009 – 2020)ย ๐Ÿ“Š
  • Senior Consultant, IT-Developmentย (Danish Technological Institute, 2007 – 2009)ย ๐Ÿ› ๏ธ
  • Software Development Managerย (TC Electronic A/S, 1999 – 2007)ย ๐ŸŽถ
  • System Developerย (Crisplant A/S, 1996 – 1999)ย ๐Ÿ“ฆ
  • System Managerย (Sam-system A/S, 1989 – 1996)ย ๐Ÿ’ผ

Suitability For The Award

Mr. Kim Bjerge, Associate Professor at Aarhus Universityโ€™s Department of Electrical and Computer Engineering, is an exemplary candidate for theย Best Researcher Awardย 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.ย ๐Ÿ“š๐Ÿ”ง๐ŸŒฑ

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.ย ๐ŸŒฑ๐Ÿ”๐Ÿค–

Publication Top Notesย 

  • Deep learning and computer vision will transform entomologyย – Cited by: 362, Year: 2021ย ๐Ÿ“–
  • Towards the fully automated monitoring of ecological communitiesย – Cited by: 141, Year: 2022ย ๐ŸŒฑ
  • An automated light trap to monitor moths (Lepidoptera) using computer vision-based tracking and deep learningย – Cited by: 119, Year: 2021ย ๐Ÿฆ‹
  • Real-time insect tracking and monitoring with computer vision and deep learningย – Cited by: 110, Year: 2021ย ๐Ÿ“น
  • A computer vision system to monitor the infestation level of Varroa destructor in a honeybee colonyย – Cited by: 85, Year: 2019ย ๐Ÿ
  • Accurate detection and identification of insects from camera trap images with deep learningย – Cited by: 61, Year: 2023ย ๐Ÿ”
  • A living laboratory exploring mobile support for everyday life with diabetesย – Cited by: 40, Year: 2010ย ๐Ÿ“ฑ
  • Hierarchical classification of insects with multitask learning and anomaly detectionย – Cited by: 26, Year: 2023ย ๐Ÿ“Š
  • Enhancing non-technical skills by a multidisciplinary engineering summer schoolย – Cited by: 19, Year: 2017ย ๐ŸŽ“

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

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 Masterโ€™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. Wangโ€™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
  • Masterโ€™s Degree in Physics
    Renmin University of China, Beijing, China
    September 2007 – July 2010
  • Bachelorโ€™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 ๐ŸŒ€
  2. Magnetic semiconductors ๐Ÿงฒ
  3. Resistive switching ๐Ÿ”„
  4. Molecular spintronics ๐Ÿงฌ
  5. Transition metal ferromagnets โš›๏ธ
  6. Novel two-dimensional electronics ๐Ÿ“

Honors:

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

  • Young Changjiang Scholars Award Program, Ministry of Education (2023) ๐ŸŽ“
  • Advisor of Outstanding Master’s Degree Thesis (2021) ๐Ÿ†
  • Youth Promotion Association of the Chinese Academy of Sciences (2018) ๐ŸŒŸ
  • Research Tuition Scholarship (2011 and 2012) ๐Ÿ’ฐ
  • Outstanding Academic Performance Award (2012 and 2013) ๐Ÿ“š
  • Excellent Graduation Thesis Award (2010) ๐ŸŽ–๏ธ

Publication top Notes:

Local manipulation of skyrmion lattice in Fe3GaTe2ย at room temperature

The performance of ultraviolet solar-blind detection of p-Si/n-Ga2O3ย 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 Ga2O3ย films synthesized by sol-gel method

Mechanical manipulation for ordered topological defects