Prof. Magdalena Piasecka | Temperature Measurement | Excellence in Research

Posted on by ScienceFather

Prof. Magdalena Piasecka | Temperature Measurement | Excellence in Research 

Prof. Magdalena Piasecka, Kielce University of Technology, Poland

Dr. Magdalena Piasecka is a Full Professor and Head of the Department of Mechanics and Thermal Processes at Kielce University of Technology, Poland. She earned her Ph.D. from Kielce University of Technology in 2002, followed by a habilitation from Koszalin University of Technology in 2015. In 2020, she was awarded the title of Professor in technical sciences by the President of Poland. Her research focuses on flow boiling heat transfer in minigaps, investigating the effects of geometry, spatial orientation, and thermal parameters on boiling processes. She specializes in enhanced heat transfer surfaces, advanced temperature measurement techniques such as liquid crystal and infrared thermography, and mathematical modeling of heat and fluid flow. With over 230 scientific publications, she has an H-index of 24 and more than 1,100 citations. She has authored three monographs and holds two patents. Dr. Piasecka has participated in 12 research projects, serving as Principal Investigator in five. Her contributions to thermodynamics, fluid mechanics, and renewable energy have earned her multiple awards and distinctions for scientific excellence.

Professional Profile:

SCOPUS

Summary of Suitability for Excellence in Research 

Prof. Magdalena Piasecka is a highly deserving candidate for the Excellence in Research Award, given her outstanding contributions to heat transfer, thermodynamics, and fluid mechanics. Her extensive publication record, leadership in research projects, and impact on the scientific community demonstrate her exceptional research excellence.

🎓 Education & Academic Titles:

  • Ph.D. (2002) – Kielce University of Technology, Poland
  • Habilitation (2015) – Koszalin University of Technology, Poland
  • Professor Title (2020) – Conferred by the President of Poland in Technical Sciences

👩‍🏫 Work Experience:

  • Full Professor & Head of the Department of Mechanics and Thermal Processes – Kielce University of Technology, Poland

🏆 Achievements:

  • 📚 230+ Scientific Publications in peer-reviewed journals & international conferences
  • 📈 Web of Science Bibliometric Metrics:
    • H-index: 24
    • Total Citations: 1102 (480 excluding self-citations)
    • Total Impact Factor (IF): 108.6 (current), 108.89 (5-year IF)
  • 📖 Books & Patents:
    • 2 Monographs (Author), 1 Monograph (Co-author)
    • 1 Patent (Author), 1 Patent (Co-author)
  • 🔬 Research Projects:
    • Participated in 12 research projects (Principal Investigator in 5 projects)

🏅 Awards & Honors:

  • Multiple Awards & Distinctions for outstanding scientific achievements in heat transfer, thermodynamics, and renewable energy research

Publication Top Notes:

Laser Surface Texturing for the Intensification of Boiling Heat Transfer in a Minichannel

Contact temperature measurement using selected thermoelements for studies of heat transfer during fluid flow in minichannels – metrology investigations

Using the Monte Carlo method for estimation of temperature uncertainty due to infrared thermography and K-type thermoelement measurements

Homotopy Perturbation Method with Trefftz Functions and Simcenter STAR-CCM+ Used for the Analysis of Flow Boiling Heat Transfer

Using Quality Function Deployment to Assess the Efficiency of Mini-Channel Heat Exchangers

Investigations of Flow Boiling in Mini-Channels: Heat Transfer Calculations with Temperature Uncertainty Analyses

Mr. Chunhui Xu | Sensor Integration Awards | Best Researcher Award

Posted on by ScienceFather

Mr. Chunhui Xu | Sensor Integration Awards | Best Researcher Award

Mr. Chunhui Xu, Shenyang Institute of Automation, Chinese Academy of Sciences, China

Xu Chunhui is a distinguished male researcher and Master Supervisor at the Shenyang Institute of Automation, part of the Chinese Academy of Sciences. He holds a Master of Engineering and a Bachelor of Engineering from Harbin Engineering University. Xu has extensive experience in autonomous underwater vehicles (AUVs), specializing in areas such as software architecture, path planning, navigation control, and fault diagnosis. His professional journey includes roles as an Assistant Researcher and Research Intern at the Shenyang Institute, where he has made significant contributions to the field, earning several awards including the Special Prize for the Science and Technology Promotion Award of the Chinese Academy of Sciences. Xu has a robust patent portfolio with numerous inventions related to underwater robotics, including collision avoidance technologies and navigation methods. His research continues to advance the capabilities of AUVs, with a focus on applications in deep-sea exploration and resource management.

Professional Profile:

SCOPUS

Xu Chunhui for the Best Researcher Award

Xu Chunhui is a distinguished male Master Supervisor at the Shenyang Institute of Automation, Chinese Academy of Sciences. His expertise lies in autonomous underwater vehicle (AUV) technologies, particularly in software architecture, path planning, navigation control, and fault diagnosis. His extensive educational background includes a Master of Engineering and a Bachelor of Engineering from Harbin Engineering University.

Education 🎓

  • Master of Engineering
    Harbin Engineering University
    September 2005 – March 2008
  • Bachelor of Engineering
    Harbin Engineering University
    September 2001 – August 2005

Work Experience 💼

  • Associate Researcher
    Shenyang Institute of Automation, Chinese Academy of Sciences
    April 2016 – Present
  • Assistant Researcher
    Shenyang Institute of Automation, Chinese Academy of Sciences
    October 2010 – March 2016
  • Research Intern
    Shenyang Institute of Automation, Chinese Academy of Sciences
    April 2008 – September 2010

Achievements 🏆

  • Science and Technology Promotion Award of the Chinese Academy of Sciences
    Special Prize, 2021
  • 3D Real-time Collision Avoidance Technology of Autonomous Underwater Robot
    Second Prize, Provincial Level, 2019
  • Research and Application of Key Technologies for Autonomous Exploration System of Deep-sea Resources
    First Prize, Ministry Level, 2018

Publication Top Notes:

Applications of Autonomous Underwater Vehicle in Submarine Hydrothermal Fields: A Review

Guided Trajectory Filtering for Challenging Long-Range AUV Navigation

A fault diagnosis method with multi-source data fusion based on hierarchical attention for AUV

Ocean Temperature Prediction Based on Stereo Spatial and Temporal 4-D Convolution Model

Accurate two-step filtering for AUV navigation in large deep-sea environment

A fault diagnosis method based on attention mechanism with application in Qianlong-2 autonomous underwater vehicle

Francesco Mercogliano | Electromagnetic Sensing System | Best Researcher Award

Posted on by ScienceFather

Francesco Mercogliano | Electromagnetic Sensing System | Best Researcher Award

Dr. Francesco Mercogliano, University of Naples Parthenope , Italy.

Dr. Francesco Mercogliano is a dedicated PhD student in Information and Communication Technology and Engineering at the University of Naples “Parthenope,” Italy. His research focuses on developing an integrated multiplatform electromagnetic sensing system for environmental characterization. With a Master’s degree in Geology and Applied Geology and a Bachelor’s degree in Geological Sciences, Francesco has demonstrated exceptional academic prowess, achieving cum laude honors. His internships with renowned institutes, including the National Research Council and the National Institute of Geophysics and Volcanology, have further honed his skills in satellite thermal imaging and geophysical data analysis. 🌍📚💻

Publication Profile

Googlescholar

Education and Experience

  • PhD Student in Information and Communication Technology and Engineering (39th Cycle)
    University of Naples “Parthenope,” Naples, Italy (2023 – Present)

    • Research Focus: Development of an integrated multiplatform electromagnetic sensing system for environmental characterization.
  • Master’s Degree in Geology and Applied Geology (LM-74)
    University of Naples “Federico II,” Naples, Italy (2021 – 2023)

    • Grade: 110/110 cum laude
    • Thesis: Analysis of Land Surface Temperature (LST) in the Campi Flegrei caldera.
  • Bachelor’s Degree in Geological Sciences (L-34)
    University of Naples “Federico II,” Naples, Italy (2018 – 2021)

    • Grade: 110/110 cum laude
    • Thesis: Remote sensing application to detect Land Surface Temperature in volcanic regions.
  • Internships:
    • National Research Council (CNR) – Institute for Electromagnetic Sensing of the Environment (IREA) (April 2023 – June 2023)
      • Analyzed satellite thermal images for LST mapping.
    • National Institute of Geophysics and Volcanology (INGV) (May 2022 – September 2022)
      • Processed GNSS-RTK data to monitor ground deformation.
    • CNR – IREA (October 2019 – January 2020)
      • Conducted geothermal monitoring using thermal remote sensors.

Suitability For The Award

Dr. Francesco Mercogliano is an exemplary candidate for the Best Researcher Award, currently pursuing a Ph.D. in Information and Communication Technology and Engineering at the University of Naples “Parthenope.” His research focuses on developing an integrated electromagnetic sensing system for environmental characterization, showcasing his commitment to innovation. With top honors in both his Master’s and Bachelor’s degrees from the University of Naples “Federico II,” and hands-on experience at the National Research Council and the National Institute of Geophysics and Volcanology, Francesco’s academic excellence and technical skills position him as a promising researcher in environmental science.

Professional Development

Francesco Mercogliano has actively pursued professional development through hands-on internships and research projects in prestigious organizations such as the National Research Council (CNR) and the National Institute of Geophysics and Volcanology (INGV). His work includes analyzing satellite thermal images for land surface temperature mapping and monitoring ground deformation using GNSS-RTK data. Proficient in MATLAB, Python, and remote sensing techniques, Francesco combines his technical skills with a strong foundation in geology to contribute meaningfully to environmental studies. His dedication to advancing knowledge in geosciences exemplifies his commitment to professional excellence and innovation. 🌱🔍📊

Research Focus

Francesco Mercogliano’s research focuses on developing integrated electromagnetic sensing systems for environmental characterization. His work emphasizes the use of advanced remote sensing technologies to analyze land surface temperature, particularly in volcanic regions like the Campi Flegrei caldera. By employing methods such as Independent Component Analysis (ICA), Francesco aims to identify thermal anomalies that can inform geological studies and risk assessment. His interdisciplinary approach combines principles of geology, remote sensing, and data analysis, contributing significantly to environmental monitoring and understanding of geological phenomena. 🌋📈💡

Awards and Honors

  • Research Internship Recognition at the National Research Council (CNR) 🌟
  • Outstanding Contribution Award at National Institute of Geophysics and Volcanology (INGV) 🌌

Publication Top Notes

  • Thermal Patterns at the Campi Flegrei Caldera Inferred from Satellite Data and Independent Component Analysis (2024) 📡🌋
  • Remote detection of Thermal Anomalies at Campi Flegrei caldera via Independent Component Analysis (ICA) (2024) 🔍📊
  • Airborne Synthetic Aperture Radar and Electromagnetic Technologies of the Italian Earth Observation Platform ITINERIS  (2024) ✈️🛰️
  • Multiparametric and Multiplatform Detection of Ongoing Unrest Processes in Active Resurgent Calderas: A Case Study of the Campi Flegrei Caldera (2024) 🌍⚠️

Ms. Xinlu Bai | Sensing Awards | Best Researcher Award

Posted on by ScienceFather

Ms. Xinlu Bai | Sensing Awards | Best Researcher Award

Ms. Xinlu Bai, Changchun university, China

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, following an Engineering Degree from Zhengzhou University of Finance and Economics (2018-2022). Xinlu has made significant contributions to the field of computer vision, particularly in dense pedestrian detection. His research includes the development of the GR-YOLO algorithm, which improves detection performance over existing methods like YOLOv8, with notable advancements in accuracy across various datasets. Xinlu’s work has been published in Sensors and has been guided by esteemed professors Deyou Chen and Nianfeng Li. He has been recognized for his excellence in competitions, winning the first prize in the Jilin Province Virtual Reality Competition, the second prize in the China Virtual Reality Competition (Data Visualization Track), and the third prize in the Jilin Province Ruikang Robot Competition.

Professional Profile:

Orcid

Suitability Summary for Best Researcher Award

Researcher: Xinlu Bai

Summary:

Xinlu Bai is a highly qualified candidate for the Best Researcher Award, distinguished by his innovative research and significant contributions to the field of computer science, particularly in pedestrian detection technology. Bai’s work demonstrates a clear commitment to advancing technology through rigorous research and practical applications.

🎓Education:

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, which he has been enrolled in since 2023. He previously completed his Engineering Degree at Zhengzhou University of Finance and Economics, where he studied from 2018 to 2022. Xinlu has made significant contributions to the field of computer vision, particularly in dense pedestrian detection. His development of the GR-YOLO algorithm, which enhances detection performance compared to YOLOv8, has been recognized through publications in Sensors and has been guided by esteemed professors Deyou Chen and Nianfeng Li. His excellence has been acknowledged in various competitions, including winning the first prize in the Jilin Province Virtual Reality Competition, the second prize in the China Virtual Reality Competition (Data Visualization Track), and the third prize in the Jilin Province Ruikang Robot Competition.

🏆Awards:

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, having previously completed his Engineering Degree at Zhengzhou University of Finance and Economics. His contributions to computer vision, particularly through the development of the GR-YOLO algorithm, have been published in Sensors and guided by Professors Deyou Chen and Nianfeng Li. Xinlu’s excellence in the field has been recognized with several prestigious awards: he won the First Prize in the Jilin Province Virtual Reality Competition, the Second Prize in the China Virtual Reality Competition (Data Visualization Track), and the Third Prize in the Jilin Province Ruikang Robot Competition.

Publication Top Notes:

Title: Dense Pedestrian Detection Based on GR-YOLO

 

 

 

Assoc Prof Dr. Jin Wang | Field Sensing Award | Best Researcher Award

Posted on by ScienceFather

Assoc Prof Dr. Jin Wang | Field Sensing Award | Best Researcher Award

Assoc Prof Dr. Jin Wang, China University of Geosciences, China

Dr. Jin Wang is an Associate Professor in the Department of Communication Engineering at China University of Geosciences (CUG) in Wuhan, China, where he has been a faculty member since May 2009. He earned his Doctoral Degree in Physical Electronics from Huazhong University of Science and Technology (HUST), and his research focuses on optical electric field sensors, fluorescence and Raman spectroscopy, and free-space optical communications systems. Dr. Wang’s expertise spans several areas including waveguide analysis, optical design, and multispectral fluorescence methods for environmental monitoring. His notable contributions include research on bismuth germanate (BGO) crystal sensors, oil pollution detection using multispectral techniques, and advancements in free-space optical communication technologies. Dr. Wang has held previous positions as a Postdoctoral Researcher at HUST and has worked in both industry and academic roles in the field of optical and electronic engineering.

Professional Profile:

Summary of Suitability for Best Researcher Award: 

Dr. Jin Wang is an accomplished Associate Professor at China University of Geosciences with a strong research portfolio spanning optical electric field sensors, free-space optical communication, and multispectral fluorescence detection methods. His research covers innovative topics such as waveguide fabrication using femtosecond lasers, oil pollution detection using multispectral fluorescence, and the development of robust communication systems for extreme environmental conditions.

Education:

  • Doctoral Degree in Physical Electronics (09/2000 – 09/2006)
    Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology (HUST), Wuhan, China
    Dissertation: “Studies on Adaptive Reception Technology in Optical Wireless Communication”
  • Master’s Degree in Electrical Engineering (09/1997 – 03/2000)
    Ordnance Engineering College, Shijiazhuang, China
    Thesis: “Design of Ultra Wideband Dipole Antenna in the Measurement of Electromagnetic Fields”
  • Bachelor’s Degree in Electrical Engineering (09/1993 – 07/1997)
    Ordnance Engineering College, Shijiazhuang, China

Work Experience:

  • Associate Professor and Associate Director (05/2009 – Present)
    Department of Communication Engineering, China University of Geosciences (CUG), Wuhan, China
    Responsible for teaching, research on optical electric field sensors, and overseeing research projects related to optical communication systems and multispectral fluorescence detection.
  • Postdoctoral Researcher in Communication Engineering (09/2006 – 04/2009)
    Huazhong University of Science and Technology (HUST), Wuhan, China
    Conducted research on free-space optical (FSO) communication systems and developed new techniques for adaptive reception over optical turbulence channels.
  • Photoelectric Design Engineer (11/2005 – 07/2008)
    Wuhan Mengxin Technology CO., LTD, Wuhan, China
    Worked on designing LCOS-based projectors, focusing on optical engine development, cooling systems, and enhancing LED brightness and contrast through optical designs.
  • Digital Circuit Design Engineer (11/1999 – 09/2000)
    Beijing University of Aeronautics and Astronautics, Beijing, China
    Designed digital circuits for fiber optic gyroscopes and worked on output signal simulation systems for fiber optics.

Publication top Notes:

 

Integrated Optical Waveguide Electric Field Sensors Based on Bismuth Germanate

Best Industrial Sensing Technology

Posted on by ScienceFather

Introductio Best Industrial Sensing Technology

Welcome to the Best Industrial Sensing Technology Award, recognizing excellence in the development and application of sensor technologies across industries. This prestigious award aims to honor individuals and organizations pushing the boundaries of sensing technology to drive innovation and efficiency in industrial processes.

About the Award:

The Best Industrial Sensing Technology Award is open to individuals and organizations worldwide who have made significant contributions to the field of industrial sensing technology. There are no age limits for eligibility, and both professionals and academics are encouraged to apply. Qualifications should demonstrate a deep understanding of sensing technologies and their applications in industrial settings. Publications related to sensing technology are considered a strong indicator of eligibility.

Requirements:

Applicants are required to submit a detailed description of their work in the field of industrial sensing technology, including relevant publications and qualifications. Evaluation criteria include the originality, impact, and feasibility of the proposed technology, as well as its potential for advancing industrial processes. Submissions should adhere to the submission guidelines outlined below.

Submission Guidelines:

Submissions should include a biography of the applicant, an abstract of the sensing technology project, and supporting files such as publications or patents. The abstract should clearly describe the technology, its application, and its potential impact on industrial processes. Supporting files should provide evidence of the technology’s effectiveness and relevance.

Evaluation Criteria:

Submissions will be evaluated based on the originality, impact, and feasibility of the proposed technology, as well as the applicant’s qualifications and publications in the field of industrial sensing technology. Preference will be given to technologies that have the potential to significantly improve industrial processes and efficiency.

Recognition:

Winners of the Best Industrial Sensing Technology Award will receive a certificate of recognition and will be featured on our website and social media channels. They will also have the opportunity to present their work at an industry conference or seminar.

Community Impact:

The Best Industrial Sensing Technology Award aims to promote innovation and collaboration in the field of industrial sensing technology, ultimately leading to advancements that benefit industries and society as a whole.

 

 

Best Nanotechnology for Sensing

Posted on by ScienceFather

Introduction Best Nanotechnology for Sensing

The Best Nanotechnology for Sensing Award recognizes outstanding contributions in the field of nanotechnology for sensing applications. This prestigious award aims to honor individuals who have made significant advancements in sensor technology using nanomaterials.

Award Eligibility:

The award is open to researchers, scientists, engineers, and innovators worldwide. There is no age limit for eligibility. Applicants must have a background in nanotechnology or a related field.

Qualifications:

Applicants should possess a Ph.D. or equivalent qualification in a relevant field. They should also have a strong publication record in the area of nanotechnology for sensing.

Requirements:

Submissions must include a detailed research proposal outlining the use of nanotechnology in sensing applications. Applicants should also provide a list of publications related to their work in this field.

Evaluation Criteria:

Submissions will be evaluated based on the significance of the research, the innovation of the approach, and the potential impact on the field of sensing technology.

Submission Guidelines:

All submissions must be sent via email to the award committee. The deadline for submissions is [insert deadline date].

Recognition:

The recipient of the Best Nanotechnology for Sensing Award will receive a cash prize and a certificate of recognition. They will also be invited to present their research at a prestigious conference.

Community Impact:

Winners of the award are expected to contribute to the community by sharing their knowledge and expertise with other researchers in the field.

Biography:

Applicants should provide a brief biography highlighting their academic and professional achievements in the field of nanotechnology for sensing.

Abstract and Supporting Files:

Submissions must include an abstract of the research proposal and any supporting files, such as graphs, charts, or images, that illustrate the research.