Shiyu Liu - Engineering - Best Researcher Award
Hebei University - China
AUTHOR PROFILE
SHIYU LIU: RESEARCHER IN AI-BASED MONITORING 🔬
Shiyu Liu, currently a lecturer and postdoctoral researcher at Hebei University, has been making significant contributions in the field of spectral detection and analysis using artificial intelligence. His primary research revolves around spectral detection, machine learning, and AI-driven health monitoring systems for lithium-ion batteries, bringing innovative solutions to environmental monitoring and engineering applications.
AI-DRIVEN BATTERY MONITORING 🔋
Liu's work focuses on the health monitoring of lithium-ion batteries through artificial intelligence techniques. He combines electrochemical impedance spectroscopy with machine learning to accurately predict battery capacity and health. This research is vital for improving battery longevity, particularly in electric vehicles and sustainable energy systems, where battery performance is crucial.
SPECTRAL ANALYSIS & AI ALGORITHMS đź“Š
Liu's expertise extends to spectral detection and analysis, utilizing AI-based algorithms for processing near-infrared (NIR) spectroscopy data. His research aims to address issues such as high noise interference and spectral peak overlap, which often hinder accurate detection of complex organic compounds. By integrating machine learning and chemometric methods, he strives for precision in environmental pollutant measurement and industrial applications.
INNOVATIVE PROJECTS & PARTNERSHIPS 🤝
Shiyu Liu has actively contributed to several national and provincial projects, including the National Natural Science Foundation of China. His projects range from detecting environmental pollutants using spectral analysis to developing remote sensing image processing algorithms for space applications. These collaborations underscore his role in advancing both environmental science and technology.
CUTTING-EDGE PUBLICATIONS đź“š
Liu has published extensively in prestigious journals, such as Fuel and Spectrochimica Acta, with a focus on using AI techniques for diesel fuel analysis and NIR spectroscopy. His innovative approach combines deep learning with spectral data to enhance the accuracy of fuel property detection, contributing to advancements in both energy and environmental fields.
PROFESSIONAL ENGAGEMENTS & PRESENTATIONS 🎤
Liu actively participates in international conferences, presenting his research findings to global audiences. Notably, he presented at the 2023 UNIfied International Conference in the UK, where he shared insights on battery health monitoring using AI. His academic activities also include contributions to forums on infrared technology, further solidifying his reputation in AI-driven research.
AWARDS & RECOGNITIONS 🏆
Shiyu Liu has received several prestigious awards, including the CSC Scholarship for his visiting PhD tenure at the University of Huddersfield. His accolades also include national scholarships, recognition as an “excellent graduate,” and top prizes in mathematical and physics competitions. These honors reflect his commitment to academic excellence and innovation in his field.
NOTABLE PUBLICATION
Title: Series fusion of scatter correction techniques coupled with deep convolution neural network as a promising approach for NIR modeling
Authors: Liu, S., Wang, S., Hu, C., Kong, D., Yuan, Y.
Journal: Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy
Year: 2023
Title: A MLP-Based Transfer Learning Model Using EIS Health Features for State of Health Estimation of Lithium-Ion Battery
Authors: Zhao, X., Wang, Z., Liu, S., Gu, F., Ball, A.
Conference: ICAC 2023 - 28th International Conference on Automation and Computing
Year: 2023
Title: Markov Transform Field Coupled with CNN Image Analysis Technology in NIR Detection of Alcohols Diesel
Authors: Liu, S., Wang, S., Hu, C., Kong, D.
Conference: Mechanisms and Machine Science
Year: 2023
Title: Rapid and accurate determination of diesel multiple properties through NIR data analysis assisted by machine learning
Authors: Liu, S., Wang, S., Hu, C., Kong, D., Wang, J.
Journal: Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy
Year: 2022
Title: Determination of alcohols-diesel oil by near infrared spectroscopy based on gramian angular field image coding and deep learning
Authors: Liu, S., Wang, S., Hu, C., Bi, W.
Journal: Fuel
Year: 2022