Dr. Liu Gaohua | Signal Processing Awards | Best Researcher Award

Dr. Liu Gaohua, Tianjin University, China

Gaohua Liu is a dedicated engineer and researcher at the School of Electronic and Information Engineering at Tianjin University, where she has been engaged in teaching and motion recognition research since March 2013. She earned her Master of Engineering degree in Electromagnetic Field and Microwave from Tianjin University in 2013, where her thesis focused on downlink logical channel design and algorithm research in LTE under the supervision of Prof. HanSong Su. Prior to that, she completed her Bachelor of Engineering in Communication Engineering at Qingdao University of Science & Technology in 2010. Currently, Gaohua is pursuing her Ph.D. in Information and Communication Engineering, specializing in motion recognition based on multimodal signals, under the guidance of Prof. Jie Jin. Her contributions to the field have been recognized with several awards, including the “Shen-Zhikang Award” for outstanding young teachers at Tianjin University in June 2019 and a National First Prize in the fifth “Dingyang Cup” National Electrical and Electronic Teaching Case Design Competition in May 2018.

Professional Profile:

SCOPUS

Suitability for the Best Researcher Award

Gaohua Liu holds a Master’s degree in Electromagnetic Field and Microwave from Tianjin University, where she conducted significant research on LTE downlink logical channel design. Her foundational education in Communication Engineering from Qingdao University of Science & Technology further solidifies her expertise in the field.

🎓 Education

2010-2013: M.E. in Electromagnetic Field and Microwave
- Institution: Tianjin University, Tianjin, China
- Thesis Title: Downlink Logical Channel Design and Algorithm Research in LTE
- Supervisor: Prof. HanSong Su
2006-2010: B.E. in Communication Engineering
- Institution: Qingdao University of Science & Technology, Qingdao, China

💼 Work Experience

03/2013 – Present: Engineer
- Department: School of Electronic and Information Engineering, Tianjin University
- Focus: Teaching and Motion Recognition research
09/2018 – Present: Ph.D. Candidate
- Research Topic: Motion Recognition Based on Multimodal Signals
- Supervisor: Prof. Jie Jin
- Institution: Tianjin University, Tianjin, China

🏆 Awards and Honors

Jun. 2019: “Shen-Zhikang Award” for Tianjin University’s Young Teachers in Talent
May. 2018: National First Prize in “The Fifth ‘Dingyang Cup’ National Electrical and Electronic Teaching Case Design Competition”

Publication Top Notes:

Improved encoder-decoder temporal action detection algorithm

Improved human action recognition algorithm based on two-stream faster region convolutional neural network

Algorithm for student behavior detection based on neural network

Improved class room face recognition algorithm based on insightface and its application

Classroom face detection algorithm based on convolutional neural network

Prof Dr. Fengshou Gu | Signal Processing Award | Best Researcher Award

Professor at University of Huddersfield – The Institute of Railway Research (IRR) – Huddersfield, United Kingdom

Professor Fengshou Gu is a highly accomplished researcher and academic with a distinguished career in the field of condition monitoring and diagnostics. With over 30 years of experience, he has made significant contributions to developing advanced monitoring and diagnostic techniques, numerical simulation methods, and signal processing techniques. His research has focused on various areas, including machine modeling, fault diagnosis, energy harvesting, and wireless sensor networks. Professor Gu’s work has been published in numerous prestigious journals, and he has presented his research at international conferences. He has also supervised over 100 PhD students and examined many more worldwide. Overall, Professor Gu’s expertise, innovative research, and dedication to advancing the field of condition monitoring and diagnostics make him a highly respected figure in the academic and research community.

Professional Profile

Education:

Professor Fengshou Gu’s academic journey began at Taiyuan University of Technology in Shanxi, China, where he earned his Bachelor of Science (B.S.) in Mechanical Engineering, graduating in September 1979. He continued his studies at the same institution, completing his Master of Science (M.Sc.) in the Mechanical Department from January 1981 to March 1985. Professor Gu pursued his doctoral studies at the University of Manchester, United Kingdom, where he obtained his Doctorate (Dr.) from the School of Mechanical Engineering from August 2004 to September 2008.

Work Experiences:

Professor Fengshou Gu has accumulated a wealth of experience throughout his career, starting with his tenure as a Lecturer in Vibration and Acoustics at Taiyuan University of Technology, China, from January 1985 to June 1991. Following this, he served as a Research Engineer at the University of Manchester, U.K., from July 1991 to October 1996. His role evolved to Senior Research Engineer at the same institution, where he continued his impactful work until September 2007. Since then, Professor Gu has held the positions of Principal Research Fellow, Professor, Head of MDARG (Machine Diagnostics, Dynamics, and Artificial Intelligence Research Group), and Deputy Director of CEPE (Centre of Excellence for Precision Engineering), solidifying his reputation as a leading expert in condition monitoring and diagnostics.

Skills:

Professor Fengshou Gu possesses a diverse range of skills that have been instrumental in his research and academic endeavors. He is proficient in numerical analysis, particularly in the context of friction stir welding, as evidenced by his review publications in this area. His expertise also extends to predictive modeling for biodiesel properties and their impact on engine performance, highlighting his strong background in engineering analysis and modeling. Additionally, Professor Gu has a deep understanding of machine condition monitoring, demonstrated by his work on energy harvesting technologies for self-powered wireless sensor networks and his research on diesel engine combustion characteristics. His skills also encompass signal processing techniques, including acoustic measurements and independent component analysis for fault diagnosis in mechanical equipment. Professor Gu’s proficiency in thermal imaging enhancement and modal analysis further underlines his expertise in machinery fault diagnosis. Overall, his skills in numerical analysis, predictive modeling, condition monitoring, and signal processing have contributed significantly to his impactful research contributions.

Achievements:

Professor Fengshou Gu has achieved numerous milestones in the field of condition monitoring and diagnostics, showcasing his exceptional expertise and innovative contributions. He has developed groundbreaking techniques such as single-channel Blind Source Separation (BSS) for acoustic source separation and the MSB-SE nonlinear modulation analysis theory, which have significantly advanced the field. His pioneering work on On-Rotor Sensing (ORS) based dynamic measurement and analysis theory has revolutionized dynamic measurement approaches. Professor Gu’s research has also led to the establishment of vibro-acoustic models (AAC, FAS) for tribological systems and diagnostic approaches, enhancing the understanding and diagnosis of complex machinery. Additionally, he has made significant contributions to online Operational Modal Analysis (OMA) with his Correlation Signal Cluster-based Stochastic Subspace Identification (CSC-SSI) method, applicable to both linear and nonlinear systems. Professor Gu’s innovative work extends to the development of instantaneous electric signature analysis for motor-driven system monitoring, nonlinear dynamic-based energy harvesting concepts, and thermal energy-based self-powered wireless sensor networks, showcasing his commitment to advancing sustainable and efficient monitoring technologies. His research on the nonlinear temperature field distribution of infrared thermal images for machine condition and performance monitoring has further demonstrated his pioneering approach to condition monitoring. Furthermore, Professor Gu has developed remote modal identification techniques based on photogrammetry analysis, highlighting his multidisciplinary and innovative research efforts.

Publications:

A review of numerical analysis of friction stir welding

Authors: X He, F Gu, A Ball

Citations: 542

Year: 2014

Prediction models for density and viscosity of biodiesel and their effects on fuel supply system in CI engines

Authors: B Tesfa, R Mishra, F Gu, N Powles

Citations: 278

Year: 2010

The measurement of instantaneous angular speed

Authors: Y Li, F Gu, G Harris, A Ball, N Bennett, K Travis

Citations: 230

Year: 2005

Energy harvesting technologies for achieving self-powered wireless sensor networks in machine condition monitoring: A review

Authors: X Tang, X Wang, R Cattley, F Gu, AD Ball

Citations: 216

Year: 2018

Detecting the crankshaft torsional vibration of diesel engines for combustion related diagnosis

Authors: P Charles, JK Sinha, F Gu, L Lidstone, AD Ball

Citations: 205

Year: 2009

A review on online state of charge and state of health estimation for lithium-ion batteries in electric vehicles

Authors: Z Wang, G Feng, D Zhen, F Gu, A Ball

Citations: 197

Year: 2021

Numerical simulation and experimental study of a two-stage reciprocating compressor for condition monitoring

Authors: M Elhaj, F Gu, AD Ball, A Albarbar, M Al-Qattan, A Naid

Citations: 196

Year: 2008

Combustion and performance characteristics of CI (compression ignition) engine running with biodiesel

Authors: B Tesfa, R Mishra, C Zhang, F Gu, AD Ball

Citations: 185

Year: 2013

Water injection effects on the performance and emission characteristics of a CI engine operating with biodiesel

Authors: B Tesfa, R Mishra, F Gu, AD Ball

Citations: 185

Year: 2012

A study of the noise from diesel engines using the independent component analysis

Authors: W Li, F Gu, AD Ball, AYT Leung, CE Phipps

Citations: 183

Year: 2001