Assist. Prof. Dr. Fan-Jie Kung | Artificial Intelligence | Best Researcher Award

Assistant Professor at National Taipei University of Technology, Taiwan

Fan-Jie Kung is an accomplished academic and researcher in electrical engineering, currently serving as an Assistant Professor at the National Taipei University of Technology, Taiwan. With expertise spanning human-machine interface design, radar signal processing, and advanced acoustic technologies, Kung brings a unique interdisciplinary perspective to his work. His focus on developing robust signal processing frameworks—especially for speech enhancement and auditory modeling—demonstrates both a strong engineering foundation and innovative application of machine learning techniques. Kung’s professional journey bridges academia and applied research, contributing impactful work through journal publications, competitive projects, and teaching roles.

Profile

ORCID

Education

Fan-Jie Kung’s academic background is firmly rooted in electrical engineering. He earned his Doctorate in Electrical Engineering from National Tsing Hua University, Taiwan, where he studied from February 2017 to January 2024, graduating with an outstanding GPA of 4.20 out of 4.30. Prior to this, he completed a Master’s Degree in Electrical Engineering from the same institution between 2011 and 2013. His undergraduate studies were undertaken at National Taipei University of Technology from 2007 to 2011, where he earned his Bachelor’s Degree with a GPA of 3.86 out of 4.00. Notably, Kung also participated in a rigorous Summer School Program in Mechanical Engineering at Technion-Israel Institute of Technology in 2019, achieving a commendable grade of 92.8 out of 100. This international academic experience enriched his perspective and strengthened his analytical capabilities in engineering design.

Experience

Kung’s professional and academic experience is extensive and diverse. In 2024, he joined the Department of Electrical Engineering at National Taipei University of Technology as an Assistant Professor. Before that, he was a postdoctoral researcher at National Yang Ming Chiao Tung University. He previously held a software engineering role at the National Chung-Shan Institute of Science & Technology from 2013 to 2019, where he specialized in human-machine interface design and radar signal processing. Concurrently, he gained teaching experience as a teaching assistant for various electrical engineering courses at National Tsing Hua University and National Taipei University of Technology. From 2022 to 2024, he also managed the lab website for the Telecom Electroacoustics Audio (TEA) Lab, further showcasing his involvement in both academic communication and applied research.

Research Interest

Kung’s research interests encompass a wide spectrum of topics within signal processing and intelligent acoustics. His core interests include statistical speech signal processing, noise reduction, dereverberation, source counting, source localization and tracking, machine learning, and deep learning. He has particularly contributed to spatial-spectral denoising frameworks and multichannel Wiener filtering techniques aimed at enhancing speech signals in noisy and reverberant environments. His work also frequently intersects with biomedical applications, such as improving cochlear implant performance through better auditory parameter estimation.

Award

Throughout his academic journey, Kung has earned multiple accolades reflecting both technical excellence and innovative thinking. He was a finalist in the prestigious 2020 NCTU Three-Minute Thesis (3MT) Competition and participated in the DARPA Subterranean Challenge Final Round in Washington, D.C., the same year. He also demonstrated product innovation in the 2012 “Voice Care” development project. In his early academic years, he won first place in a 2010 RFID competition and ranked 17th in a national Calculus competition in 2008. He was recognized five times with the Academic Excellence Award at National Taipei University of Technology, attesting to his sustained high performance.

Publication

• F.-J. Kung,
  “An Integrated Spatial-Spectral Denoising Framework for Robust Electrically Evoked Compound Action Potential Enhancement and Auditory Parameter Estimation,”
  Sensors, vol. 25, no. 11, pp. 1–22, June 2025. (Impact Factor: 3.40, Q1 ranking)

• F.-J. Kung, M. R. Bai,
  “A Nested Generalized Sidelobe Canceller for Source Counting and Localization, and Signal Separation in Reverberant Fields,”
  Journal of the Acoustical Society of America, vol. 154, pp. 3769–3781, Dec. 2023. (Impact Factor: 2.40)

• M. R. Bai, F.-J. Kung, C.-S. Tao,
  “Tracking of Moving Sources in a Reverberant Environment Using Evolutionary Algorithms,”
  IEEE Access, vol. 10, pp. 107563–107574, Oct. 2022. (Impact Factor: 3.90)

• M. R. Bai, F.-J. Kung,
  “Speech Enhancement by Denoising and Dereverberation Using a Generalized Sidelobe Canceller-Based Multichannel Wiener Filter,”
  Journal of the Audio Engineering Society, vol. 70, no. 3, pp. 140–155, Mar. 2022. (Impact Factor: 1.91)

Conclusion

Fan-Jie Kung exemplifies a modern researcher who integrates deep technical skills with a drive for practical innovation. His multifaceted contributions in areas such as source localization, speech enhancement, and auditory modeling position him as a rising academic with potential for international leadership in acoustic signal processing. His ability to bridge theory and application through impactful research, effective teaching, and award-winning innovation underscores his valuable role in advancing both science and engineering education.