Prof. Xiaoxia Wan | Sensing Technology | Excellence in Innovation

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Prof. Xiaoxia Wan | Sensing Technology | Excellence in Innovation 

Prof. Xiaoxia Wan, Wuhan University, China

Wan Xiaoxia, is a distinguished professor and doctoral supervisor specializing in color science and technology. She is currently a faculty member in the Department of Printing and Packaging at Wuhan University, where she has served since 2018. Wan holds a Ph.D. in Cartography and Geographic Information Systems from Wuhan University, and her educational background includes a Master’s in Geographic Information Systems and a Bachelor’s in Cartography from the same institution. Her academic journey was enriched by her experience as a senior visiting scholar at the Munsell Color Science Laboratory, California State University, and Rochester Institute of Technology. In addition to her teaching role, she holds several significant positions, including Deputy Director of the Teaching Guidance Committee for Light Industry Majors of the Ministry of Education and member of both the China Printing and Color Standardization Technical Committees. Wan has received numerous awards for her teaching and research, including the National Excellent Course designation for her course “Introduction to Printing” and recognition as a leading talent in the news and publishing industry. Her research has led to successful projects funded by the National Natural Science Foundation of China, focusing on color reproduction methods for cultural relics. Wan’s contributions to her field have been acknowledged through several prestigious awards, including the Hubei Science and Technology Progress Award and the China National Textile and Apparel Council Science and Technology Award.

Professional Profile:

SCOPUS

Summary of Suitability for Excellence in Innovation: Wan Xiaoxia

Dr. Wan Xiaoxia is a highly qualified candidate for the Excellence in Innovation award, distinguished by her extensive contributions to color science and technology, particularly in the realm of printing and packaging. Her pioneering research and leadership roles in various educational and professional organizations reflect her commitment to advancing innovation in her field.

Education 🎓

  • Senior Visiting Scholar
    Munsell Color Science Laboratory, California State University, Los Angeles and Rochester Institute of Technology (2004-2006)
  • Ph.D. in Engineering
    Cartography and Geographic Information Systems, Wuhan University (1995-2002)
  • Master of Engineering
    Geographic Information Systems, Wuhan University of Surveying and Mapping (1992-1995)
  • Bachelor of Engineering
    Cartography, Wuhan University of Surveying and Mapping (1982-1986)

Work Experience 💼

  • Professor & Doctoral Supervisor
    Department of Printing and Packaging, Wuhan University (2018-present)
  • Vice Dean
    School of Journalism and Communication, Wuhan University (2000-present)
  • Lecturer
    School of Printing Engineering, Wuhan University of Surveying and Mapping (1996-2000)
  • Teaching Assistant
    Department of Cartography, Wuhan University of Surveying and Mapping (1986-1992)
  • Doctoral Supervisor
    School of Printing and Packaging, Wuhan University (2004-present)

Achievements 📚

  • National Excellent Course
    “Introduction to Printing” (2008)
  • National Excellent Shared Course
    “Introduction to Printing” (2010)
  • National Bi Sheng Newcomer Award (2009)
  • Suzhou Industrial Park Leading Talent (2012)
  • Hubei Province News and Publishing Figures (2012)
  • National News and Publishing Industry Leading Talent (2013)
  • Wuhan City Huanghe Talent (2014)
  • Wuhan University Excellent Teaching and Research Achievement First Prize (2008)
  • Hubei Province Higher Education Teaching Achievement First Prize (2008, 2018)

Awards & Honors 🏆

  • Second Prize of Hubei Science and Technology Progress Award
    Key Technology and Application of Color Reproduction Based on Spectrum (2020)
  • Dunhuang Academy “Excellent Academic Achievement Award”
    Protection Technology Category, Second Prize (2017)
  • China National Textile and Apparel Council Science and Technology Award
    Key Technology and Industrialization of Full-Color Yarn Manufacturing, Second Place (2016)

Publication Top Notes:

A Color Reproduction Method for Exploring the Laser-Induced Color Gamut on Stainless Steel Surfaces Based on a Genetic Algorithm

Enhancement of laser-induced surface coloring through laser double-scan method

Prediction model for laser marking colors based on color mixing

A Novel Correction Method of Kubelka–Munk Model for Color Prediction of Pre-colored Fiber Blends

Dynamic Projection Method of Electronic Navigational Charts for Polar Navigation

Spectral missing color correction based on an adaptive parameter fitting model

 

Prof. Dr. Ahmad Jalal | Portable Sensors Awards | Best Researcher Award

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Prof. Dr. Ahmad Jalal | Portable Sensors Awards | Best Researcher Award 

Prof. Dr. Ahmad Jalal, Air University, Pakistan

R. Ahmad Jalal is an accomplished academic and researcher, currently serving as an Associate Professor in the Department of Computer Science and Engineering at Air University, Islamabad, Pakistan. He also leads the Intelligent Media Center (IMC) as its Director, overseeing a team of 15 MS and Ph.D. students, researchers, and developers contributing to innovative R&D activities with both national and international collaborations.

Professional Profile:

GOOGLE SCHOLAR

Suitability of R. Ahmad Jalal for the Best Researcher Award

Dr. R. Ahmad Jalal’s extensive academic and professional contributions position him as a highly suitable candidate for the Best Researcher Award. With his role as an Associate Professor in the Department of Computer Science and Engineering at Air University, Islamabad, and as the Director of the Intelligent Media Center (IMC), he has demonstrated leadership in research and innovation.

Education 🎓

  • Ph.D. in Computer Engineering, Pohang University of Science and Technology (POSTECH), South Korea
  • Master’s in Computer Science, (Details not provided, assumed prior to Ph.D.)

Work Experience 💼

  1. Associate Professor (March 2019 – Present)
    • Air University, Department of Computer Science and Engineering, Islamabad, Pakistan.
  2. Director, Intelligent Media Center (IMC) (2017 – Present)
    • Leading a team of 15 MS and Ph.D. students, researchers, and developers working on R&D for international and national collaborations.

Achievements & Contributions 🌟

  • Supervision: Successfully supervised 9 Ph.D. students and 21 MS students.
  • Patents:
    • Depth-based invariant human activity recognition using R transformation features (Co-inventor), Korea Copyright Commission, Patent No. 134571-0003856, 2011.
  • Publications: Multiple impactful papers with notable awards (details below).

Awards and Honors 🏆

  1. Best Paper Award (Runner-up) – ICAEM 2018
    • Facial Expression Recognition in Image Sequences Using 1D Transform and Gabor Wavelet Transform
    • Presented at IEEE Conference of Applied and Engineering Mathematics, pp. 82-87.
  2. Best Paper Award – ICOST 2011
    • Daily Human Activity Recognition Using Depth Silhouettes and R Transformation for Smart Home
    • Presented at the 9th ICOST, Lecture Notes in Computer Science (Springer), LNCS 6719, pp. 25-32.

Notable Roles ✨

  • Leader: Spearheading advanced research in AI, human activity recognition, and media technologies.
  • Innovator: Developed patented solutions in depth-based human activity recognition.

Publication Top Notes:

Robust human activity recognition from depth video using spatiotemporal multi-fused features

CITED:399

A Depth Video Sensor-based Life Logging Human Activity Recognition System for Elderly Care in Smart Indoor Environments

CITED:301

Depth video-based human activity recognition system using translation and scaling invariant features for life logging at smart home

CITED:249

Human activity recognition via recognized body parts of human depth silhouettes for residents monitoring services at smart home

CITED:208

Students’ Behavior Mining in E-learning Environment Using Cognitive Processes with Information Technologies

CITED:186

Vision-based human activity recognition system using depth silhouettes: A smart home system for monitoring the residents

CITED:117

Dr. Yue Wang | Sensor development Award | Best Researcher Award

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Dr. Yue Wang | Sensor development Award | Best Researcher Award 

Dr. Yue Wang, University of Science and Technology Liaoning, China

Dr. Yue Wang is an Associate Professor at the School of Chemical Engineering at the University of Science and Technology Liaoning in China. He earned his Bachelor’s degree from the University of Science and Technology Anshan and both his Master’s and Doctorate degrees from the University of Science and Technology Liaoning and Saitama Institute of Technology, Japan, respectively. Since joining the University of Science and Technology Liaoning in 2006, Dr. Wang has focused his research on sensors and biosensors, biofuel cells, supercapacitors, energy harvesting, and artificial muscles. His work has resulted in over 60 published scientific papers, garnering approximately 600 citations, reflecting his significant contributions to the field. Dr. Wang has secured multiple research grants from various institutions, including the Education Department of Liaoning Province and the Natural Science Foundation of Liaoning Province, to advance his projects on conductive sensors, pesticide sensors, electrochemical biosensors, and wearable smart sensing technologies. Additionally, he completed a visiting scholarship at the University of Texas at Dallas in 2019-2020, further enhancing his academic and research expertise.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award: Yue Wang

Yue Wang is an exemplary candidate for the Best Researcher Award, primarily due to his substantial academic qualifications, extensive research contributions, and impactful work in the field of Material Science, specifically within sensor and biosensor technologies.

Education

  • Bachelor’s Degree in Material Science
    University of Science and Technology Anshan, China
    September 1998 – July 2002
  • Master’s Degree in Material Science
    University of Science and Technology Liaoning, China
    September 2003 – March 2006
  • Ph.D. in Material Science
    Saitama Institute of Technology, Japan
    April 2008 – March 2011

Work Experience

  • Associate Professor
    University of Science and Technology Liaoning, China
    April 2006 – Present
  • Visiting Scholar
    University of Texas at Dallas
    April 2019 – March 2020

Publication top Notes:

A carbon black–doped chalcopyrite–based electrochemical sensor for determination of hydrogen peroxide

Glucose oxidase, horseradish peroxidase and phenothiazine dyes-co-adsorbed carbon felt-based amperometric flow-biosensor for glucose

Crab gill–derived nanorod-like carbons as bifunctional electrochemical sensors for detection of hydrogen peroxide and glucose

Cellulose-derived hierarchical porous carbon based electrochemical sensor for simultaneous detection of catechol and hydroquinone

A triphenylamine based fluorescent probe for Zn2+ detection and its applicability in live cell imaging

1,8-naphthalimide-triphenylamine-based red-emitting fluorescence probes for the detection of hydrazine in real water samples and applications in bioimaging in vivo

Prof Wanrun Li | Vision Sensing | Best Researcher Award

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Prof Wanrun Li | Vision Sensing | Best Researcher Award

Prof Wanrun Li, Lanzhou University of Technology, China 

Professor Wanrun Li is a distinguished academic and researcher in Structural Health Monitoring, currently serving as the Vice Dean of the School of Civil Engineering at Lanzhou University of Technology, China. With a focus on fatigue analysis, wind turbine vibration control, and structural health monitoring, he has led numerous research projects funded by national and regional foundations. His work has significantly contributed to understanding the seismic performance of super-tall buildings, damage identification, and fatigue life prediction of wind turbines. He has held multiple leadership roles, including Associate Professor and department head, and has been a visiting scholar at prestigious institutions.

Professional Profile:

Suitability for the Best Researcher Award: 

Professor Wanrun Li’s extensive research portfolio, leadership in high-stakes projects, and contributions to structural engineering make him a strong candidate for the Best Researcher Award. His work in wind turbine vibration control and fatigue analysis is critical for the advancement of sustainable energy infrastructure. However, to strengthen his candidacy, broadening the impact of his research on industry standards and further enhancing global outreach would be valuable steps forward. Overall, his dedication to innovative research and significant contributions to civil engineering position him as a deserving nominee for this prestigious award.

Education

Professor Wanrun Li earned his Ph.D. in Structural Engineering from Lanzhou University of Technology in 2013, specializing in Structural Health Monitoring under the guidance of Prof. Yongfeng Du and Prof. Y.Q. Ni. He was also a joint-supervised Ph.D. candidate at Hong Kong Polytechnic University from 2011-2012. His academic background includes an M.S. in Disaster Prevention and Mitigation from Lanzhou University of Technology (2010) and a B.S. in Civil Engineering from the same institution (2008). His education laid the foundation for his expertise in monitoring structural health and analyzing the fatigue of civil structures.

Work Experience

Wanrun Li has over a decade of academic and research experience. Currently, he is a Professor and Vice Dean at Lanzhou University of Technology. He previously served as an Associate Professor and Head of the Department of Building Engineering. His international experience includes being a visiting scholar at the University of Illinois Urbana-Champaign and Southeast University, China. Over the years, he has led research initiatives focused on vibration control, fatigue life prediction, and damage identification in large structures such as wind turbines and high-rise buildings.

Skills

Professor Li’s technical expertise includes advanced knowledge in Structural Health Monitoring, Wind Turbine Vibration Control, and Weld Fatigue Analysis. His skills extend to predictive modeling, statistical pattern recognition, and seismic data analysis. He is proficient in developing new devices for vibration reduction, using machine vision technology for turbine blade detection, and applying experimental and multi-scale simulation techniques for assessing fatigue in steel structures. His proficiency with numerical modeling, experimental research, and structural design underpins his research and teaching efforts.

Awards and Honors

Wanrun Li has been recognized with multiple prestigious awards, including the Hongling Outstanding Young Scholar Award at Lanzhou University of Technology (2019-2021) and the Science Fund for Distinguished Young Scholars of Gansu Province (2021-2024). His work has earned several grants from the National Natural Science Foundation of China (NSFC), totaling over ¥1.9 million for projects related to wind turbine structures and vibration control. These honors affirm his significant contributions to structural engineering and disaster prevention.

Membership

Professor Li is actively engaged in several professional organizations, contributing to the advancement of structural health monitoring and civil engineering. He collaborates closely with renowned research groups and institutions, including the University of Illinois Urbana-Champaign and Southeast University. His membership in national scientific communities has enabled him to secure significant research funding and present his findings in both domestic and international conferences.

Teaching Experience

With a passion for mentoring, Professor Li has been an academic instructor at Lanzhou University of Technology since 2013, progressing from instructor to professor. As a faculty member, he has taught courses related to Structural Engineering, Civil Engineering, and Structural Health Monitoring. His role as the Chief Duty Professor for the Hongliu Top-class Major in Civil Engineering reflects his commitment to academic excellence. He also supervises graduate students, guiding them through research projects and fostering a collaborative learning environment.

Research Focus

Professor Li’s research is centered on Structural Health Monitoring, Weld Fatigue Analysis, and Vibration Control of Wind Turbines. He is particularly interested in seismic data analysis of tall structures, wind-induced fatigue of turbines, and developing new devices for reducing tower vibrations. His projects include studies on vibration control using tuned liquid column dampers and fatigue life prediction of wind turbines in harsh environments. His innovative work integrates machine vision technology and UAVs for turbine blade detection, and he has contributed significantly to enhancing structural safety and durability.

Publication top Notes:

“Wind turbine blade defect detection and measurement technology based on improved SegFormer and pixel matching”

    • Year: 2024
    • Journal: Optics & Laser Technology
    • DOI: 10.1016/j.optlastec.2024.111381

“Mitigation of In-Plane Vibrations in Large-Scale Wind Turbine Blades with a Track Tuned Mass Damper”

    • Year: 2023
    • Journal: Structural Control and Health Monitoring
    • DOI: 10.1155/2023/8645831

“Dynamic Characteristic Monitoring of Wind Turbine Structure Using Smartphone and Optical Flow Method”

    • Year: 2022
    • Journal: Buildings
    • DOI: 10.3390/buildings12112021

“Dynamic Characteristics Monitoring of Large Wind Turbine Blades Based on Target-Free DSST Vision Algorithm and UAV”

    • Year: 2022
    • Journal: Remote Sensing
    • DOI: 10.3390/rs14133113

“Seismic Vibration Mitigation of Wind Turbine Tower Using Bi-Directional Tuned Mass Dampers”

    • Year: 2020
    • Journal: Mathematical Problems in Engineering
    • DOI: 10.1155/2020/8822611

“Low-cycle fatigue test and life assessment of carbon structural steel GB Q235B butt joints and cruciform joints”

    • Year: 2019
    • Journal: Advances in Structural Engineering
    • DOI: 10.1177/1369433218795292

“Seismic Performance of a New Precast Concrete Shear Wall with Bolt Connection”

    • Year: 2019
    • Journal: Gongcheng Kexue Yu Jishu/Advanced Engineering Science
    • DOI: 10.15961/j.jsuese.201801163

“Time-Varying Nonlinear Parametric Identification of Isolated Structure Based on Wavelet Multiresolution Analysis”

    • Year: 2019
    • Journal: Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis
    • DOI: 10.16450/j.cnki.issn.1004-6801.2019.03.024

“Welding Residual Stress Simulation and Experimental Verification in Beam-to-Column Joints of Q345B Steel”

    • Year: 2019
    • Journal: Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science)
    • DOI: 10.12141/j.issn.1000-565X.190044

 

Prof Dr. Zhongwei Jiang | Intelligent sensing | Best Researcher Award

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Prof Dr. Zhongwei Jiang | Intelligent sensing | Best Researcher Award 

Prof Dr. Zhongwei Jiang, Yamaguchi University, Japan

Professor Zhongwei Jiang is a distinguished academic and researcher in the field of Mechanical Engineering. He currently serves as a Professor at the Graduate School of Sciences and Technology for Innovation at Yamaguchi University in Japan. Born on [insert date of birth], he began his academic journey at Northeastern University in China, where he earned his Bachelor of Engineering degree in Mechanical Engineering in 1982. He then pursued further studies in Japan, obtaining both his Master of Engineering in 1987 and Doctor of Engineering in 1990 from Tohoku University. Professor Jiang’s professional career commenced as a research assistant in the Department of Mechanical Engineering at Tohoku University from 1990 to 1993. He then advanced to the role of Associate Professor within the same department, a position he held until 1999. In July 1999, he joined Yamaguchi University as a Professor in the Department of Mechanical Engineering, where he has significantly contributed to the academic community. In April 2024, he was honored with the title of Honorary Professor at Yamaguchi University.

Professional Profile:

SCOPUS

 

👨‍🎓 Education:

  • 📚 Bachelor of Engineering (1978.9 – 1982.8) – Dept of Mechanical Engineering, Northeastern University, China
  • 📚 Master of Engineering (1985.4 – 1987.3) – Dept of Mechanical Engineering, Tohoku University, Japan
  • 📚 Doctor of Engineering (1987.4 – 1990.3) – Dept of Mechanical Engineering, Tohoku University, Japan

👨‍🏫 Employment:

  • 🔬 Research Assistant (1990.4 – 1993.2) – Dept of Mechanical Engineering, Tohoku University, Japan
  • 👨‍💼 Associate Professor (1993.3 – 1999.6) – Dept of Mechanical Engineering, Tohoku University, Japan
  • 👨‍🏫 Professor (1999.7 – 2024.3) – Dept of Mechanical Engineering, Yamaguchi University, Japan
  • 🎓 Honorary Professor (2024.4 – Present) – Yamaguchi University, Japan

Work Experience:

Research Assistant, Department of Mechanical Engineering, Tohoku University, Japan
April 1990 – February 1993

  • Conducted research in mechanical engineering, focusing on advanced manufacturing techniques.
  • Assisted in teaching undergraduate and graduate courses.
  • Published research papers in reputable journals.

 

Publication top Notes:

Compensation Method for Missing and Misidentified Skeletons in Nursing Care Action Assessment by Improving Spatial Temporal Graph Convolutional Networks

Research on analytical models for reducing friction heat for flexible ultrasonic propagation using stranded wire

Visualization of Caregiving Posture and Risk Evaluation of Discomfort and Injury

Development of invitro blood vessel coagulation-incision experimental method and characterization of opposite-phase vibration type ultrasonic scalpel

Tidal Volume Level Estimation Using Respiratory Sounds

Monitoring of Sleep Breathing States Based on Audio Sensor Utilizing Mel-Scale Features in Home Healthcare

Intelligent sensing

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Introduction of Intelligent Sensing

Intelligent sensing is a dynamic field at the intersection of sensor technology, artificial intelligence, and data analytics. It aims to develop sensors and sensing systems that not only collect data but also possess the capability to process and interpret that data intelligently.

Smart Sensor Development:

Investigating the design and fabrication of smart sensors that incorporate Embedded intelligence allowing them to adapt to changing conditions filter noise and optimize data collection.

Sensor Data Analytics:

Focusing on advanced data analytics techniques including machine Learning and deep learning applied to sensor data for pattern recognition, anomaly detection, and predictive modeling.

Sensor Fusion:

Addressing Sensor Fusion strategies that combine data from multiple sensors to provide a more comprehensive and accurate view of the environment leading to improved situational awareness.

Context-Aware Sensing:

Analyzing the development of Sensors and systems that can adapt their sensing modalities and Parameters based on the context and user requirements enhancing their versatility and effectiveness.

IoT and Intelligent Sensing:

Exploring how intelligent sensing technologies are integrated into the Internet of Things IoT ecosystem enabling real-time data processing remote monitoring and smart decision-making in connected environments.