Shiyu Liu - Engineering - Best Researcher Award

Hebei University - China

AUTHOR PROFILE

SCOPUS

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 📊

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 📚

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

ACADEMIC BACKGROUND

Mrs. Vedika Vishawas Avhad is an accomplished academic in the field of Computer Engineering. She is currently pursuing her PhD at Pillai HOC in Panvel and has completed her M.E. in Computer Engineering from YTIET, Karjat in 2019 with a CGPA of 7.77. Her undergraduate studies culminated in a B.E. in Computer Engineering from D.Y. Patil, Pune in 2014, where she achieved 61.80%. Additionally, she holds a Diploma in Computer Engineering from K.K. Wagh Polytechnic, Nashik, completed in 2010 with a commendable score of 72.90%.

PROFESSIONAL EXPERIENCE

Mrs. Avhad's professional journey includes roles as an Assistant Professor at Vasantdada Patil Pratishthan’s College of Engineering & Visual Arts in Sion since July 2019. She has also served as a Lecturer at Shivajirao S. Jondhale Polytechnic, Dombivli from June 2016 to March 2018, and as an Assistant Professor at B R Harne College of Engineering, Vangni from January 2016 to May 2016. Her teaching experience is complemented by her roles as a department-level Exam Coordinator, BE & TE student Project Guide, and various coordination responsibilities in academic events and processes.

RESEARCH INTERESTS AND OBJECTIVES

Her research interests focus on innovative applications of computer engineering in health and forensic sciences. She is currently engaged in research projects such as "Iridology-based Early Stage Predictions of Human Health Conditions using Computer Vision and Deep Learning" and "Searching and Detecting Forged Multimedia Data in Forensic Investigation." These projects aim to develop precise patterns of iris for health predictions and efficient detection methods for multimedia forensics, respectively.

PUBLICATIONS

Mrs. Avhad has contributed significantly to academic literature with publications in various reputed journals. Notable works include articles on topics such as Smart EVMs for reducing frauds based on biometric identification, efficient Cibpre schemes with provable security, multimedia data forensics, jamming-aware traffic allocation, plant health monitoring systems, customer churn prediction, heart disease prediction, age and gender prediction, and obstacle detection for the visually impaired.

PROFESSIONAL DEVELOPMENT

She has actively participated in numerous faculty development programs, workshops, and trainings. Some of these include AICTE-ISTE sponsored STTPs on emerging trends in data science, data security, and applications of mathematics in engineering, as well as FDPs on topics like blockchain technology, software project management, and natural language processing. These programs have been instrumental in enhancing her teaching methodologies and research capabilities.

ACADEMIC CONTRIBUTIONS AND SERVICE

Beyond her teaching and research, Mrs. Avhad has been involved in various academic and administrative roles. She has served as a Paper-Setter for University of Mumbai and K. J. Somaiya Institute of Engineering and Information Technology, anchored official, technical, and cultural programs, and worked as an examiner and moderator for university examinations. Her contributions also extend to supporting departmental committees and mentoring students in their academic and research pursuits.