Tag: Predictive Analytics Award

Summary of Suitability for Best Researcher Award – Dr. Hossein Bagherpour

Dr. Hossein Bagherpour is an exemplary candidate for the Best Researcher Award, recognized for his pioneering work at the intersection of biosystems engineering, artificial intelligence, and precision agriculture. As an Assistant Professor at Bu-Ali Sina University since 2013, Dr. Bagherpour has made significant contributions to the development and application of intelligent systems in agricultural automation and food quality assessment.

🎓 Education

🧪 Ph.D. in Biosystems Engineering – Tarbiat Modares University, Tehran, Iran
🚜 M.Sc. in Agricultural Machinery Engineering – Tarbiat Modares University, Tehran, Iran
⚙️ B.Sc. in Mechanical Engineering (Design of Machinery) – University of Tehran, Tehran, Iran

🏢 Work Experience

👨‍🏫 Assistant Professor, Department of Biosystems Engineering, Bu-Ali Sina University (2013–Present)
- 📍 Faculty of New Agriculture, Room 207
- 📍 Business Incubator Center No. 2, Room 7

🏆 Achievements & Contributions

📊 Supervised numerous Ph.D. and M.Sc. theses focusing on AI, deep learning, and smart agricultural systems
🤖 Developed algorithms for robotic harvesting, crop disease detection, and quality inspection using machine learning and computer vision
📚 Published multiple research papers (see Google Scholar) in areas such as AI-based phenotyping, intelligent sensors, and agricultural robotics

🎖 Awards & Honors

🌟 Recognized for advancing smart agriculture through AI integration
🧠 Leader in AI-driven research in agricultural biosystems

Publication Top Notes:

Hyperparameter Optimization of ANN, SVM, and KNN Models for Classification of Hazelnuts Images Based on Shell Cracks and Feature Selection Method

Enhancing the Performance of YOLOv9t Through a Knowledge Distillation Approach for Real-Time Detection of Bloomed Damask Roses in the Field

Development and Optimization of a Novel Deep Learning Model for Diagnosis of Quince Leaf Diseases

Detection of different adulteration in cinnamon powder using hyperspectral imaging and artificial neural network method

Design, Construction, and Evaluation of a Precision Vegetable Reaper to Use in Small Plots

A New Method to Optimize Deep CNN Model for Classification of Regular Cucumber Based on Global Average Pooling

Ms. Soree Hwang | Healthcare Intelligence Awards | Best Sensor for Health Monitoring Award

Posted on 26/05/202526/05/2025 by ScienceFather

Ms. Soree Hwang | Healthcare Intelligence Awards | Best Sensor for Health Monitoring Award

Ms. Soree Hwang, Korea Institute of Science and Technology (KIST), South Korea

So Ree Hwang is a dedicated researcher in the field of biomedical engineering currently pursuing her Ph.D. at Korea University. She holds a Master’s degree in Design and Engineering from Seoul National University of Science and Technology and a Bachelor’s degree in Mechanical Engineering from Korea Aerospace University. Since May 2022, she has been a student researcher at the Korea Institute of Science and Technology (KIST), where she contributes to the development of AI-based health management platforms, including lifelog acquisition systems and fatigue and stress detection technologies. Her research also focuses on gait analysis and stroke assessment using motion signal processing and wearable devices. So Ree has published numerous papers as a main and co-author in reputable journals such as Sensors, Frontiers in Human Neuroscience, and IEEE journals. Her work integrates machine learning and biomedical signal analysis to advance rehabilitation technologies and health monitoring systems.

Professional Profile:

Prediction of lower extremity multi-joint angles during overground walking by using a single IMU with a low frequency based on an LSTM recurrent neural network

Summary of Suitability for Best Researcher Award – So Ree Hwang

Dr. So Ree Hwang is a highly suitable candidate for the Best Researcher Award in the domain of health monitoring and biomedical engineering, with a strong multidisciplinary background and an impressive portfolio of impactful, AI-integrated sensor-based research.

🎓 Education

Ph.D. in Biomedical Engineering
Korea University, Seoul, Republic of Korea (2021 – Present)
M.S. in Design and Engineering
Seoul National University of Science and Technology, Seoul, Republic of Korea (2018 – 2020)
B.S. in Mechanical Engineering
Korea Aerospace University, Goyang-si, Republic of Korea (2011 – 2017)

💼 Work Experience

Student Researcher – Korea Institute of Science and Technology (KIST)
📍 Seoul, Republic of Korea (2022.05.01 – Present)
- 🧠 Developed a lifelog system and AI-based fatigue/stress management platform
- 🚶‍♂️ Contributed to gait analysis tech for knee disorder recovery
- 🧪 Worked on motion signal-based stroke assessment technologies
Research Intern – Korea Institute of Science and Technology (KIST)
📍 Seoul, Republic of Korea (2020.03.01 – 2021.12.31)
- 🧠 Focused on stroke assessment using motion signal analysis

🏆 Achievements & Research Contributions

📝 8 SCI-indexed papers as main or co-author, including in top journals like Sensors, Frontiers in Human Neuroscience, and IEEE
- 📊 Topics: Gait phase classification, stroke severity assessment, fatigue detection using AI, wearable systems
⚙️ First-author of applied engineering papers on 3D printing and IMU validation
🤖 Integrated machine learning models (CNN-LSTM-Attention, RNNs) into biomedical signal analysis
🧩 Contributed to the advancement of intelligent health monitoring and gait recovery systems

Publication Top Notes:

CITED:50

Classification of stroke severity using clinically relevant symmetric gait features based on recursive feature elimination with cross-validation

CITED:20

Classification of gait phases based on a machine learning approach using muscle synergy

CITED:14

Property analysis of photo-polymerization-type 3d-printed structures based on multi-composite materials

CITED:8

Machine learning based abnormal gait classification with IMU considering joint impairment

CITED:5

User-centered Design of a Multi-material 3D Printer

CITED:1

Mr. Wenpo Yao | Time Series | Best Researcher Award

Posted on 22/05/2025 by ScienceFather

Mr. Wenpo Yao | Time Series | Best Researcher Award

Mr. Wenpo Yao, Nanjing University of Posts and Telecommunications, China

Dr. Wenpo Yao is a researcher in Biomedical Engineering at Nanjing University of Posts and Telecommunications, with expertise spanning statistical physics, nonlinear dynamics, time series analysis, and biomedical signal processing. He earned his Ph.D. and Master’s degrees in Signal Processing from Nanjing University of Posts and Telecommunications in 2019 and 2013, respectively, following a Bachelor’s degree in Telecommunication Engineering from Jiangsu University in 2010. Dr. Yao has made significant contributions to the field of nonlinear time series analysis, particularly in developing and applying permutation-based methods to assess time irreversibility in physiological and complex systems. His work has been published in leading journals such as Physical Review E, Chaos, Solitons & Fractals, Communications in Nonlinear Science and Numerical Simulation, and Physics Letters A. His recent research emphasizes the application of nonlinear metrics to sleep EEG and heart rate variability, offering insights into nonequilibrium dynamics in biomedical signals.

Professional Profile:

Summary of Suitability: Dr. Wenpo Yao – Best Researcher Award

Dr. Wenpo Yao, currently engaged in Biomedical Engineering at Nanjing University of Posts and Telecommunications, is a highly accomplished researcher with deep expertise in statistical physics, nonlinear dynamics, time series analysis, and biomedical signal processing. His extensive publication record, innovative methodologies, and interdisciplinary research contributions mark him as a highly suitable candidate for the Best Researcher Award.

👨‍🎓 Education

🎓 Ph.D. in Signal Processing
Nanjing University of Posts and Telecommunications
(Sept. 2016 – July 2019)
🎓 Master’s in Signal Processing
Nanjing University of Posts and Telecommunications
(Sept. 2010 – April 2013)
🎓 Bachelor’s in Telecommunication Engineering
Jiangsu University
(Sept. 2006 – June 2010)

💼 Work Experience

🧑‍🏫 Researcher / Faculty in Biomedical Engineering
Nanjing University of Posts and Telecommunications
(Exact position title not specified, but actively involved in research and publication in the field)
📧 Email: yaowp@njupt.edu.cn

🧠 Research Interests

📈 Statistical Physics
🔁 Nonlinear Dynamics
📊 Time Series Analysis
🧬 Biomedical Signal Processing

🏆 Achievements & Honors

📝 Published 12+ high-impact journal papers, many in top-tier journals such as:
- Physical Review E
- Chaos, Solitons & Fractals
- Physics Letters A
- Communications in Nonlinear Science and Numerical Simulation
- Nonlinear Dynamics
- Applied Physics Letters
🧩 Contributed significantly to the field of time irreversibility analysis, especially in biomedical signals like EEG and heart rate variability.
🌟 Collaborative work with notable researchers like M. Perc, indicating international collaboration and interdisciplinary impact.
📈 Developed novel methods and parameters for analyzing nonequilibrium and nonlinear dynamics in complex systems.

Publication Top Notes:

Spectral, phase, and their interacting components for complexity analysis of depression electroencephalogram

Fuzzy permutation time irreversibility for nonequilibrium analysis of complex system

Permutation time irreversibility in sleep electroencephalograms: Dependence on sleep stage and the effect of equal values

Mr. Xincheng Guo | Time Series Awards | Best Machine Learning for Sensing Award

Posted on 21/05/2025 by ScienceFather

Mr. Xincheng Guo | Time Series Awards | Best Machine Learning for Sensing Award

Mr. Xincheng Guo, Shanghai University of Engineering Science, China

Xincheng Guo is a graduate student pursuing a Master’s degree in Electronic Information at Shanghai University of Engineering Science, with research focused on intelligent signal processing, deep learning, and IoT systems. His notable contributions include the development of an innovative CEEMDAN-WT-VMD framework for multi-source noise suppression in power load data and the design of advanced neural network models such as Bidirectional Temporal Convolutional Networks and Attention-based BiGRU for spatiotemporal modeling and signal denoising. He has published first-authored research on short-term power load forecasting in the journal Electronics (2025, Q1). Xincheng has also engineered a multi-sensor fire detection and patrol system integrating improved YOLOv5s vision algorithms with sensor fusion and high-precision positioning technologies. His technical expertise spans sensing algorithms, embedded systems, and AI frameworks like PyTorch and TensorFlow. He has received multiple honors, including the 2nd Prize in the 19th China Graduate Electronics Design Competition (Shanghai Division) and the National Graduate Scholarship.

Professional Profile:

Summary of Suitability for Best Machine Learning for Sensing Award conclusion

Xincheng Guo is a highly promising candidate for the Research for Best Machine Learning for Sensing Award, demonstrating strong expertise in intelligent signal processing and deep learning applied to multi-modal sensing systems. Currently pursuing a Master’s degree in Electronic Information at Shanghai University of Engineering Science, Guo has developed innovative methods for sensing signal denoising and prediction, including a novel CEEMDAN-WT-VMD framework that achieves significant noise reduction and a Bidirectional Temporal Convolutional Network that outperforms state-of-the-art models in power load forecasting. His research is supported by the National Natural Science Foundation of China, reflecting its scientific merit and relevance. Beyond theoretical contributions, Guo has designed practical embedded sensing systems integrating advanced vision algorithms and multi-sensor fusion for real-time fire detection, showcasing his ability to translate machine learning innovations into impactful applications. With published Q1 journal papers, recognized technical skills in AI frameworks, and awards in national electronics competitions, Xincheng Guo embodies the excellence and innovation that the Best Machine Learning for Sensing Award seeks to honor.

🎓 Education

Master of Electronic Information (2023.09 – 2026.09)
Shanghai University of Engineering Science
Focus: Intelligent Signal Processing, Deep Learning, IoT Systems

💼 Work Experience

Graduate Student
China Education and Research Network (CERNET), Beijing (Since 2023.09)

🏆 Achievements & Key Contributions

Developed CEEMDAN-WT-VMD framework for multi-source noise suppression, achieving a 46.3% noise reduction (SNR 227.1 dB)
Created Bidirectional Temporal Convolutional Network (BiTCN) with 0.65% MAPE on power load forecasting, outperforming top models
Designed an Attention-based BiGRU model for dynamic temporal feature weighting in noisy data
Published first-author paper:
“Short-Term Power Load Forecasting Based on CEEMDAN-WT-VMD Joint Denoising” in Electronics (2025, Q1, IF=3.0)
Built a Multi-Sensor Fire Detection and Patrol System using Raspberry Pi and MM32 with improved YOLOv5s vision algorithm (+8.2% mAP), flame/smoke sensor fusion, and GPS positioning

🎖️ Awards & Honors

🥈 2nd Prize, 19th China Graduate Electronics Design Competition (Shanghai Division), 2024
🥉 3rd Prize, 6th Yangtze River Delta Smart City Competition, 2024
🎓 National Graduate Scholarship, 2023-2024
🛫 Aerospace Inspirational Scholarship, 2022-2023
🏅 CET-4 Certificate (English Proficiency)
💻 National Computer Technology and Software Professional Qualification (Primary Level)

Publication Top Notes:

Short-Term Power Load Forecasting Based on CEEMDAN-WT-VMD Joint Denoising and BiTCN-BiGRU-Attention

Dr. Lizheng Deng | Forecasting | Best Researcher Award

Posted on 24/04/2025 by ScienceFather

Dr. Lizheng Deng | Forecasting | Best Researcher Award

Dr. Lizheng Deng, Tsinghua University, China

Dr. Lizheng Deng, born in September 1994 in Anhui Province, China, is a postdoctoral researcher at the School of Safety Science, Institute of Public Safety Research, Tsinghua University in Beijing. He holds a Ph.D. in Safety Science and Engineering from Tsinghua University, where his dissertation focused on landslide subsurface deformation behavior using acoustic emission (AE) monitoring under the mentorship of Professor Hongyong Yuan. His academic journey also includes visiting research stints at Loughborough University in the UK and Montanuniversitaet Leoben in Austria. Dr. Deng’s research centers on geotechnical monitoring, particularly leveraging acoustic emission technologies and artificial intelligence to assess and predict subsurface deformation in geological settings. His work during his Ph.D. led to the development of an innovative AE waveguide array, now employed in landslide monitoring projects across multiple provinces in China. In his postdoctoral research, he continues to explore the dynamics of granular material–metal structure interactions and the associated AE mechanisms, with the support of the Beijing Natural Science Foundation and China Postdoctoral Science Foundation.

Professional Profile:

Summary of Suitability for the Research for Best Researcher Award

Dr. Lizheng Deng stands out as a highly suitable candidate for the Research for Best Researcher Award based on his impressive academic and research trajectory, international collaborations, and impactful contributions to geotechnical monitoring using Acoustic Emission (AE) and Artificial Intelligence (AI). With a Ph.D. from Tsinghua University and postdoctoral research at the same prestigious institution, Dr. Deng has made significant advancements in landslide subsurface deformation behavior monitoring, a critical area for disaster risk reduction. His innovations, such as the AE array and AI-integrated early warning models, are not only academically recognized—published in top-tier journals like Engineering Geology and Landslides—but also applied nationwide, directly influencing public safety via China’s GeoCloud monitoring system. Funded by leading scientific foundations and supported by multiple government ministries, Dr. Deng’s research is both cutting-edge and socially impactful, embodying the excellence and real-world application expected of a recipient of this award.

🎓 Education

PhD in Safety Science and Engineering (09/2017 – 06/2022)
Tsinghua University, Beijing, China 🇨🇳
Dissertation: “Research on Landslide Subsurface Deformation Behaviour Using Acoustic Emission Monitoring”
👨‍🏫 Supervisor: Prof. Hongyong Yuan (Chang Jiang Scholars)
Visiting PhD Student (02/2020 – 08/2020)
Loughborough University, UK 🇬🇧
👨‍🏫 Supervisors: Prof. Neil Dixon, Alister Smith
B.E. in Safety Engineering (09/2013 – 06/2017)
China University of Mining and Technology, Beijing
Thesis: Roof control methods in hard rock mining >700m
👨‍🏫 Supervisor: Prof. Yueping Qin, Prof. Nikolaus A. Sifferlinger
Visiting Student (02/2017 – 05/2017)
Montanuniversitaet Leoben, Austria 🇦🇹
👨‍🏫 Supervisor: Prof. Nikolaus A. Sifferlinger

💼 Work Experience

Postdoctoral Researcher (07/2022 – present)
School of Safety Science, Institute of Public Safety Research, Tsinghua University
🧪 Focus: Acoustic emission (AE) from granular material-metal interactions

🏆 Achievements & Contributions

🔬 Innovated AE Array Monitoring Technology
Used in landslide early warning systems across 20+ sites in 8 provinces in China.
👉 Integrated with AI for landslide deformation modeling and risk prediction.
🛠 Field Implementation & Tech Adoption
AE monitoring tech adopted by:
- Ministry of Natural Resources (MNR)
- China’s Geological Hazard Monitoring System (GeoCloud)
📚 Publications in top journals
- Engineering Geology
- Landslides
- Measurement

🥇 Awards & Honors

🧾 “Certificate of Universal Instrumentation for Geological Hazard Monitoring” – Ministry of Natural Resources, China
🙌 Letter of Appreciation – Recognizing real-world impact of his monitoring tech
💰 Funded by:
- Beijing Natural Science Foundation
- China Postdoctoral Science Foundation
- Ministry of Industry and Information Technology of China
- Ministry of Natural Resources of China

Publication Top Notes:

Spatio-Temporal Deformation Prediction of Large Landslides in the Three Gorges Reservoir Area Based on Time-Series Graph Convolutional Network Model

Acoustic emission behavior generated from active waveguide during shearing process

Noise Cancellation Method Based on TVF-EMD with Bayesian Parameter Optimization

Automatic classification of landslide kinematics using acoustic emission measurements and machine learning

Machine learning prediction of landslide deformation behaviour using acoustic emission and rainfall measurements

Experimental Investigation on Integrated Subsurface Monitoring of Soil Slope Using Acoustic Emission and Mechanical Measurement

Correlation between Acoustic Emission Behaviour and Dynamics Model during Three-Stage Deformation Process of Soil Landslide

On Image Fusion of Ground Surface Vibration for Mapping and Locating Underground Pipeline Leakage: An Experimental Investigation

Prof. Syafruddin Side | Transmission Prediction | Best Researcher Award

Posted on 10/03/202510/03/2025 by ScienceFather

Prof. Syafruddin Side | Transmission Prediction | Best Researcher Award

Prof. Syafruddin Side, Makassar State University, Indonesia.

Prof. Dr. Syafruddin Side is a distinguished mathematician specializing in mathematical modeling, dynamical systems, and differential equations. He is a faculty member in the Department of Mathematics at the Faculty of Mathematics and Science, Universitas Negeri Makassar, Indonesia. He earned his Bachelor’s degree in Applied Mathematics from Hasanuddin University (1991-1996), followed by a Master’s degree in Analysis and Applied Mathematics from Bandung Institute of Technology (2000-2003), and a Ph.D. in Applied Mathematics from the National University of Malaysia (2009-2013). His doctoral research focused on mathematical modeling of the spread of dengue viruses in Indonesia and Malaysia. With an h-index of 18 on Google Scholar and 13 on Scopus, he has made significant contributions to his field through numerous publications. His research interests lie in solving complex mathematical problems using analytical and computational techniques.

Professional Profile:

Stability analysis and numerical simulation of SEIR model for pandemic COVID-19 spread in Indonesia

Summary of Suitability for Best Researcher Award

Based on Prof. Dr. Syafruddin Side’s research profile, he appears to be a strong candidate for the Best Researcher Award, given his expertise and contributions in applied mathematics, particularly in mathematical modelling, dynamical systems, and differential equations. Below is a detailed evaluation of his suitability for the award.

🎓 Education Background

S-1 (Bachelor’s Degree) – 📍 Hasanuddin University (1991-1996)
- Field: Applied Mathematics
- Thesis: Solution of Poisson Equation with Boundary Element Method
- Supervisor: Dr. Jeffry Kusuma
S-2 (Master’s Degree) – 📍 Bandung Institute of Technology (2000-2003)
- Field: Analysis and Applied Mathematics
- Thesis: Analytical Perturbation for General Characteristics Value Semi-Simple
- Supervisor: Prof. Dr. Wono Setya Budi
S-3 (Doctoral Degree, Ph.D.) – 📍 National University Malaysia (2009-2013)
- Field: Applied Mathematics
- Thesis: SIR and SEIR Mathematical Models for the Spread of Dengue Viruses in South Sulawesi, Indonesia, and Selangor, Malaysia
- Supervisor: Prof. Dr. Mohd. Salmi Md. Noorani

👨‍🏫 Work Experience

Professor at the Department of Mathematics, Faculty of Mathematics and Science, Universitas Negeri Makassar (UNM) 📍🇮🇩
Researcher in Mathematical Modeling, Dynamical Systems, and Differential Equations
Mentor & Supervisor for Master’s and Ph.D. Students 🎓✍️

🏆 Achievements, Awards & Honors

H-index: 📊
- Google Scholar: 18
- Scopus: 13
Published in Renowned Journals 📚
Invited Speaker at International Conferences 🎤🌍
Recognized for Contributions to Mathematical Modeling in Epidemiology 🦠📈
Contributor to National and International Research Projects 🔬💡

Publication Top Notes:

CITED:490

A SIR model for spread of dengue fever disease (simulation for South Sulawesi, Indonesia and Selangor, Malaysia)

CITED:172

SEIR model for transmission of dengue fever in Selangor Malaysia

CITED:102

An SIR epidemic model for COVID-19 spread with fuzzy parameter: the case of Indonesia

CITED:98

Lyapunov functions of SIR and SEIR model for transmission of dengue fever disease

CITED:69

Dr. Li Qin | Monitoring Award | Best Researcher Award

Posted on 26/02/2025 by ScienceFather

Dr. Li Qin | Monitoring Award | Best Researcher Award

Dr. Li Qin, Zhejiang Ocean University, China

Dr. Li Qin is a faculty member in the Department of Information Engineering at Zhejiang Ocean University, China. He earned his Ph.D. in Information and Communication Engineering from Dalian Maritime University in 2019, where he also completed his M.S. and B.S. degrees. He was a visiting Ph.D. student at the Cullen College of Engineering, University of Houston, from 2017 to 2018. Before joining Zhejiang Ocean University in 2024, he served as an associate research fellow and lecturer at Ningbo University and was a visiting scholar at Zhejiang University. His research focuses on information engineering and related technologies.

Professional Profile:

Suitability of Li Qin, Ph.D., for the Best Researcher Award

Dr. Li Qin demonstrates a strong academic background and research experience in the field of Information and Communication Engineering. His contributions to multidisciplinary research, particularly in marine science, engineering, and tunnel lighting systems, highlight his diverse expertise. Below is an evaluation based on key award criteria:

📚 Education

🎓 Ph.D. in Information and Communication Engineering (Mar. 2015 – Jan. 2019)
🔹 Dalian Maritime University, China

🎓 Visiting Ph.D. Researcher (Sept. 2017 – Sept. 2018)
🔹 Cullen College of Engineering, University of Houston, TX, USA

🎓 M.S. in Electronic Science and Technology (Sept. 2013 – Mar. 2015)
🔹 Dalian Maritime University, China

🎓 B.S. in Electronic Information Science and Technology (Sept. 2009 – July 2013)
🔹 Dalian Maritime University, China

🏢 Professional Experience

👨‍🏫 Lecturer (June 2024 – Present)
🔹 Department of Information Engineering, Zhejiang Ocean University, China

🧑‍🔬 Associate Research Fellow (Dec. 2022 – May 2024)
🔹 Department of Information Science and Engineering, Ningbo University, China

🎓 Visiting Scholar (Sept. 2022 – Sept. 2023)
🔹 Ocean College, Zhejiang University, China

👨‍🏫 Lecturer (Jan. 2019 – Dec. 2022)
🔹 Department of Information Science and Engineering, Ningbo University, China

🏆 Achievements, Awards & Honors

🌟 Outstanding Research Contribution – Recognized for significant contributions to Information and Communication Engineering
📜 Published Multiple Research Papers – Articles in prestigious SCI/EI-indexed journals
🏅 Government and Institutional Grants – Secured funding for various research projects
🔬 Key Research Areas – Wireless Communications, Signal Processing, Ocean Information Engineering

Publication Top Notes:

Actual Truck Arrival Prediction at a Container Terminal with the Truck Appointment System Based on the Long Short-Term Memory and Transformer Model

Proposal for a Calculation Model of Perceived Luminance in Road Tunnel Interior Environment: A Case Study of a Tunnel in China

Comparative Study of Energy Savings for Various Control Strategies in the Tunnel Lighting System

Use of Pupil Area and Fixation Maps to Evaluate Visual Behavior of Drivers inside Tunnels at Different Luminance Levels—A Pilot Study

Dynamic luminance tuning method for tunnel lighting based on data mining of real-time traffic flow

Prof. Dr. Weidong Jiao | Smart Detection | Best Researcher Award

Posted on 20/02/2025 by ScienceFather

Prof. Dr. Weidong Jiao | Smart Detection | Best Researcher Award

Prof. Dr. Weidong Jiao, Zhejiang Normal University, China

Dr. Weidong Jiao was born in Wafangdian, Liaoning, China, in 1970. He received his B.E. and M.E. degrees in Safety Engineering and Mechanical Engineering from Gansu University of Technology in 1992 and 2001, respectively, and earned his Ph.D. in Mechanical Engineering from Zhejiang University in 2004. From 2004 to 2009, he served as a Professor in the Mechanical Engineering Department at Jiaxing University. Since 2013, he has been a Professor at the School of Engineering, Zhejiang Normal University. Dr. Jiao has authored over 100 research articles and holds approximately 20 invention patents. His research focuses on smart testing and signal processing, mechanical dynamics, and condition monitoring and fault diagnosis of mechanical equipment. He also serves as an Editor for the Journal of Vibration, Measurement & Diagnosis.

Professional Profile:

Summary of Suitability for Best Researcher Award – Prof. Weidong Jiao

Prof. Weidong Jiao is a highly qualified candidate for the Best Researcher Award, based on his extensive contributions to mechanical engineering, fault diagnosis, and intelligent signal processing. His strong research background, innovative work, and leadership in academia make him a worthy contender for this prestigious recognition.

🎓 Education:

B.E. in Safety Engineering – Gansu University of Technology, Lanzhou (1992)
M.E. in Mechanical Engineering – Gansu University of Technology, Lanzhou (2001)
Ph.D. in Mechanical Engineering – Zhejiang University, Hangzhou (2004)

💼 Work Experience:

Professor, Mechanical Engineering Department, Jiaxing University (2004–2009)
Professor, School of Engineering, Zhejiang Normal University (Since 2013)

🏆 Achievements & Contributions:

📚 Published over 100 research articles
🔬 Invented approximately 20 innovations
🛠️ Expertise in smart testing, signal processing, mechanical dynamics, condition monitoring, and fault diagnosis
📝 Editor of Journal of Vibration, Measurement & Diagnosis

🏅 Awards & Honors:

🎖️ Recognized for contributions in mechanical engineering and diagnostics
🏅 Honored for advancements in fault diagnosis and condition monitoring
🔍 Acknowledged for outstanding research and academic contributions in mechanical dynamics

Publication Top Notes:

Compact multiphysics coupling modeling and analysis of self-excited vibration in maglev trains

Deep learning in industrial machinery: A critical review of bearing fault classification methods

Recursive prototypical network with coordinate attention: A model for few-shot cross-condition bearing fault diagnosis

Double attention-guided tree-inspired grade decision network: A method for bearing fault diagnosis of unbalanced samples under strong noise conditions

Cross-Conditions Fault Diagnosis of Rolling Bearing Based on Transitional Domain Adversarial Network

Assoc. Prof. Dr. Junfeng Chen | Data Smoothing Awards | Best Researcher Award

Posted on 20/12/2024 by ScienceFather

Assoc. Prof. Dr. Junfeng Chen | Data Smoothing Awards | Best Researcher Award

Assoc. Prof. Dr. Junfeng Chen, Hohai University, China

Junfeng Chen is an accomplished Associate Professor at the College of Artificial Intelligence and Automation at Hohai University in Changzhou, Jiangsu, China. She holds a Ph.D. in Control Science and Engineering from Zhejiang University, where her dissertation focused on stagnation analysis of computational intelligence approaches. Chen also completed her M.Sc. in Automation at Harbin University of Science and Technology, concentrating on multi-sensor information fusion and its applications in mobile robotics. With a career at Hohai University spanning over a decade, she has progressed from Associate Lecturer to Lecturer, and now to Associate Professor, contributing significantly to the fields of artificial intelligence and automation. Her research interests encompass various aspects of computational intelligence, and she has published several papers in reputable journals, reflecting her commitment to advancing knowledge in her field.

Professional Profile: