Dr. Arul Elango | Satellite Tracking Awards | Best Researcher Award

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Dr. Arul Elango | Satellite Tracking Awards | Best Researcher Award 

Dr. Arul Elango, Vignan’s Foundation for Science, Technology and Research, India

Dr. G. Arul Elango is an accomplished academic and researcher specializing in GPS signal processing and advanced computer science. He currently serves as an Associate Professor in the Advanced Computer Science and Engineering Department at Vignan’s Foundation for Science, Technology & Research, where he applies his extensive expertise in spatial data analysis and algorithm design. Dr. Elango completed his postdoctoral research at the University of Helsinki, Finland, and previously held a postdoctoral fellowship at the École de Technologie Supérieure in Montreal, Canada. He earned his Ph.D. in Electronics and Communication Engineering from Pondicherry Engineering College, focusing on enhancing GPS receiver performance under degraded conditions. With a robust professional background that includes teaching roles at various institutions in India, he has actively contributed to numerous high-profile research projects, including collaborations with the Natural Sciences and Engineering Research Council of Canada and the European Space Agency. Dr. Elango’s work is widely recognized in the fields of deep learning and geospatial data security, and he has supervised multiple graduate students, fostering the next generation of engineers and researchers.

Professional Profile:

SCOPUS

Best Researcher Award

Based on Dr. G. Arul Elango’s impressive academic and professional credentials, I strongly recommend him for the Best Researcher Award. His qualifications and contributions to the field of GPS signal processing and geospatial data analysis demonstrate his suitability for this recognition. Below are the key highlights from his Curriculum Vitae that support this recommendation.

Education 🎓

  • Postdoctoral Research
    Spatiotemporal Data Analysis Group, Department of Computer Science, University of Helsinki, Finland
    April 2021 – April 2023
  • Post-Doctoral Research Fellow
    Laboratory of Space Technologies, Embedded Systems, Navigation, and Avionic (LASSENA), École de Technologie Supérieure, Montreal, Canada
    January 2020 – April 2021
  • Ph.D. in GPS Signal Processing
    Electronics and Communication Engineering, Pondicherry Engineering College (affiliated with Pondicherry Central University), India
    2017

    • Thesis: Software-Based GPS Receiver Acquisition and Positioning Performance Enhancement under Degraded Conditions.
  • Master of Engineering in Applied Electronics
    College of Engineering, Guindy, Anna University, Chennai, India
    June 2004

    • Achieved First Class Honors.
  • Bachelor of Engineering in Electronics and Communication
    National Engineering College (affiliated with Manonmaniam Sundaranar University), Tamil Nadu, India
    2000

    • Achieved First Class Honors.

Work Experience 💼

  • Associate Professor
    Advanced Computer Science and Engineering Department, Vignan’s Foundation for Science, Technology & Research
    July 2023 – Present
  • Associate Professor
    Electronics and Communication Engineering Department, Sree Vidyanikethan Engineering College, Tirupati, India
    January 2017 – November 2019
  • Research Scholar
    Electronics and Communication Engineering Department, Pondicherry Engineering College, Pondicherry, India
    January 2012 – June 2015
  • Associate Professor and Head
    Electronics and Communication Engineering Department, Renganayagi Varatharaj College of Engineering, Sivakasi, Tamil Nadu, India
    June 2015 – October 2016
  • Assistant Professor
    Electronics and Communication Engineering Department, National Engineering College, Kovilpatti, Tamil Nadu, India
    January 2010 – January 2012
  • Senior Lecturer
    Electronics and Communication Engineering Department, Kalasalingam University, Tamil Nadu, India
    June 2007 – January 2010
  • Design Engineer
    NewTech Software Private Limited, Bangalore, India
    July 2004 – June 2007

Achievements and Awards 🏆

  • Successfully designed algorithms for GNSS Software Defined Radio with anti-jamming capabilities under the Natural Sciences and Engineering Research Council of Canada.
  • Developed AI/Deep Learning algorithms for Ionospheric Anomaly Detection using GNSS SDR for the European Space Agency.
  • Contributed to resilience and security of geospatial data for critical infrastructures through deep learning algorithm design and deployment.

Publication Top Notes:

Design of a Smart Energy Meter and Monitoring System for Industrial and Residential Use Based on the Internet of Things

A new multipath channel estimation and mitigation using annihilation filter combined tracking loop implementation in software GPS receivers

Quasi-Real RFI Source Generation Using Orolia Skydel LEO Satellite Simulator for Accurate Geolocation and Tracking: Modeling and Experimental Analysis

Disruptive GNSS Signal detection and classification at different Power levels Using Advanced Deep-Learning Approach

A survey for recent techniques and algorithms of geolocation and target tracking in wireless and satellite systems

Prof. Dr. Xiaogang Lin | Biosensor Awards | Best Researcher Award

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Prof. Dr. Xiaogang Lin | Biosensor Awards | Best Researcher Award 

Prof. Dr. Xiaogang Lin, Chongqing University, China

Xiaogang Lin He earned his B.E. degree in Precision Instrument from Xi’an Technological University in 1998, followed by his M.A.Eng and Ph.D. degrees in Optical Engineering from Chongqing University in 2003 and 2008, respectively. Dr. Lin began his career as a technician at Mingguang Instrument Factory in 1998 before transitioning to academia as a Lecturer at Chongqing University’s College of Opto-electronic Engineering in 2003. He has since risen through the ranks, becoming an Assistant Professor, Associate Professor in 2010, and Professor in 2017. His research interests focus on photoelectric biosensing, biosensors, precision testing technology, and intelligent instruments, resulting in over 40 high-quality technical publications. Dr. Lin has also served as a visiting scholar at the University of Tennessee, Knoxville, in 2014 and 2017. He is an active member of the third Council of Opto-mechatronics Technology and Systems under the China Instrument and Control Society, as well as a senior member of the society. Additionally, he is an international TRIZ Association three-level certified expert and a national second-level innovation engineer. Dr. Lin has received the first prize of the Chongqing Science and Technology Progress Award and has hosted and participated in more than 20 provincial and ministerial research projects, including significant initiatives like the National Key R&D Program of China and the National Natural Science Foundation of China.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award: Xiaogang Lin

Dr. Xiaogang Lin is an outstanding candidate for the Best Researcher Award due to his extensive academic and professional achievements in the field of optical engineering and biosensing technologies. Born in Chongqing, China, in 1975, Dr. Lin has built a remarkable career, marked by significant contributions to research and education.

Education 🎓

  • B.E. in Precise Instrument
    Xi’an Technological University, Xi’an, China (1998)
  • M.A. in Optical Engineering
    Chongqing University, Chongqing, China (2003)
  • Ph.D. in Optical Engineering
    Chongqing University, Chongqing, China (2008)

Work Experience 💼

  • Technician
    Mingguang Instrument Factory, China (1998)
  • Lecturer
    College of Opto-electronic Engineering, Chongqing University (2003)
  • Assistant Professor
    College of Opto-electronic Engineering, Chongqing University (2003 – 2010)
  • Associate Professor
    College of Opto-electronic Engineering, Chongqing University (2010 – 2017)
  • Professor
    College of Opto-electronic Engineering, Chongqing University (2017 – Present)
  • Visiting Scholar
    University of Tennessee, Knoxville, USA (2014, 2017)

Achievements 🌟

  • Over 40 high-quality technical publications in the field of optical engineering and biosensing.
  • Member of the Third Council of Opto-mechatronics Technology and Systems, China Instrument and Control Society.
  • Senior member of the China Instrument and Control Society.
  • International TRIZ Association three-level certified expert.
  • National second-level innovation engineer.

Awards and Honors 🏆

  • First Prize of Chongqing Science and Technology Progress Award
    For significant contributions to the field of optical engineering and biosensing.
  • Hosted and participated in more than 20 provincial and ministerial research projects, including:
    • National Key R&D Program of China
    • National Natural Science Foundation of China

Publication Top Notes:

A Study on Pigment Composition of Buddhist Cave Paintings Based on Hyperspectral Technology

A Perovskite Material Screening and Performance Study Based on Asymmetric Convolutional Blocks

Advancements in Chemical and Biosensors for Point-of-Care Detection of Acrylamide

ACEK Biosensor for the Minute-Scale Quantification of Breast Cancer ctDNA

An alternating current electrokinetics biosensor for rapid on-site serological screening of Taenia solium cysticercosis infection

Francesco Mercogliano | Electromagnetic Sensing System | Best Researcher Award

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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) 🌍⚠️

Assoc. Prof. Dr. Jie Zhao | Remote Sensing Awards | Best Researcher Award

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Assoc. Prof. Dr. Jie Zhao | Remote Sensing Awards | Best Researcher Award

Assoc. Prof. Dr. Jie Zhao, Beijing University of Technology, China

  Dr. Jie Zhao is an Associate Professor at the School of Physics and Optoelectronic Engineering at Beijing University of Technology, China. She earned his Ph.D. in Optics from the university, where she also completed her Master’s degree. Dr. Zhao gained international research experience as a joint-cultured Ph.D. student at the University of Sheffield, UK. Her primary research interests include optical information processing, digital holographic microscopy, and Fourier ptychography imaging, with a focus on biological samples and terahertz wave phase-contrast imaging.She has contributed significantly to the advancement of diffraction tomographic imaging and continuous terahertz holography. Dr. Zhao has published numerous peer-reviewed articles in prominent journals and holds multiple patents.She is also an active member of the Society of Photo-Optical Instrumentation Engineers (SPIE) and has served as a postdoctoral researcher at the Henan Institute of Metrology.

Professional Profile:

SCOPUS

Summary of Suitability for the Best Researcher Award – Jie Zhao

Dr. Jie Zhao is an Associate Professor at Beijing University of Technology (BJUT), specializing in Optics and Optoelectronics. With a strong background in terahertz imaging, computational tomography, and optical information processing, Dr. Zhao has made significant contributions to both theoretical and applied optics. His extensive research output and collaborative efforts position him as an excellent candidate for the Best Researcher Award.

Education:

  • Sep. 2007 – July 2011: Ph.D. in Optics, College of Applied Sciences, Beijing University of Technology (BJUT), China.
    • Joint-cultured Ph.D. student at the College of Electronic and Electrical Engineering, The University of Sheffield, UK (Sep. 2008 – Sep. 2009).
  • Sep. 2005 – July 2007: Master’s in Optics, College of Applied Sciences, BJUT, China.
  • Sep. 2001 – July 2005: Bachelor’s in Science and Technology of Optical Information, College of Physics Science & Technology, Hebei University, China.

Professional Experience:

  • Aug. 2011 – Present: Associate Professor/Lecturer, School of Physics and Optoelectronic Engineering, BJUT, China.
    • Courses taught: Optics, College Physics, and Optical Information Processing.
  • Nov. 2017 – Nov. 2020: Postdoctoral Researcher, Henan Institute of Metrology, China.
  • Sep. 2011 – Present: Member of SPIE (International Society for Optics and Photonics).

Publication top Notes:

Continuous-wave terahertz in-line holographic diffraction tomography with the scattering fields reconstructed by a physics-enhanced deep neural network

High accuracy terahertz computed tomography using a 3D printed super-oscillatory lens

Binary diffractive lens with subwavelength focusing for terahertz imaging

Binocular full-color holographic three-dimensional near eye display using a single SLM

Diffraction tomography based on Fourier ptychographic microscopy with the multiple scattering model

Continuous-Wave Terahertz In-Line Digital Holography Based on Physics-Enhanced Deep Neural Network

Mr. Rashid Al-Shibli | Monitoring Awards | Best Researcher Award

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Mr. Rashid Al-Shibli | Monitoring Awards | Best Researcher Award

Mr. Rashid Al-Shibli, Sultan Qaboos University, Oman

Rashid Salim Al-Shibli is a dedicated and ambitious 5th-year medical student at Sultan Qaboos University in Muscat, Oman. With a strong commitment to enhancing health outcomes and quality of life, he is passionate about advancing his knowledge and expertise in neurology and neurosurgery, focusing on understanding and treating complex neurological disorders. Rashid’s academic excellence has been recognized through multiple Dean’s List distinctions, and he has contributed to the medical field with several research publications on topics such as multiple sclerosis relapses and pediatric neurology. His work earned him First Place in a poster presentation at the Third Neurology Conference in Salalah, Oman, in 2023.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award: Rashid Salim Al-Shibli

Rashid Salim Al-Shibli, a 5th-year clinical medical student at Sultan Qaboos University, is an exemplary candidate for the Best Researcher Award. His profile reflects a strong commitment to both academic excellence and cutting-edge medical research, particularly in neurosurgery and neurology. Rashid has consistently demonstrated high academic achievement, being on the Dean’s List for four consecutive years (2020-2023), and has been involved in significant publications and presentations within the medical field.

🎓 Education

  • Dean’s List 🎖️: 2020, 2021, 2022, 2023

🏆 Awards

  • First Place in Poster Presentation 🥇: Third Neurology Conference, Salalah, Oman, 2023

📄 Publications

  • ScienceDirect: Seasonal Variation of Multiple Sclerosis Relapses in Oman (18 Dec, 2023)
  • Current Medicinal Chemistry: Association of MiRNA and Bone Tumors: Future Therapeutic Inroads (30 Jan, 2024)
  • Journal of Pediatric Neurosciences: The “Weekend Effect” and “Off-Hours Effect” in Pediatric TBIL (07 May, 2024)

📜 Courses

  • Basic Life Support (2023)
  • Data Analysis (SPSS) (2022-2023)
  • COVID-19 Infection Control (2020)

🎙️ Attendance & Conferences

  • Presenter, Oman Medical Specialty Board Career Day 2024 🩺
  • Oral Presentation at Sultan Qaboos University Hospital Research Day 2024 🏥
  • Attendee, Pediatric Metabolic Bone Disease Symposium (2024)
  • Poster Presentation at Third Oman Neurology Conference (2023) 🧾
  • Attendee, Multiple Sclerosis Virtual Conference, Saudi Arabia (2022)
  • Attendee, IFMSA Event on Poverty Impact on Child Health (2020)

💼 Training & Internships

  • Marketing & E-Commerce Workshop 💻: College of Engineering, Sultan Qaboos University (2023)
  • Summer Internship 🏥: Al Hajir Health Centre, Muscat, Oman (2022)

🔧 Skills

  • Data Collection & Analysis 📊
  • Academic Writing ✍️
  • Critical Thinking and Problem-Solving 🧩
  • Effective Communication & Teamwork 🤝

Publication top Notes:

Seasonal Variations in Multiple Sclerosis Relapses in Oman: A Single Tertiary Centre Experience

Association of MiRNA and Bone Tumors: Future Therapeutic Inroads

Mr. Sahngzhe Sun | Monitoring Awards | Excellence in Research

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Mr. Sahngzhe Sun | Monitoring Awards | Excellence in Research 

Mr. Sahngzhe Sun, Wuhan University, China

Shangzhe Sun is a researcher affiliated with Wuhan University, specializing in computer vision, deep learning, and unmanned aerial vehicle (UAV) technology. His expertise includes 3D image processing, point clouds, LiDAR data analysis, and intelligent unmanned systems. Sun has contributed to significant advancements in UAV-based applications, particularly in power transmission line detection, insulator defect detection, and real-time 3D mapping. His notable works include “DCPLD-Net: A diffusion coupled convolution neural network for real-time power transmission lines detection from UAV-Borne LiDAR data,” published in the International Journal of Applied Earth Observation and Geoinformation, and collaborative projects like OR-LIM and LUOJIA Explorer for exploration and mapping. Through his research, Sun aims to improve UAV capabilities in high-precision mapping, surveillance, and defect detection, contributing to the safety and efficiency of power transmission facilities and intelligent mapping.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Excellence in Research Award: Shangzhe Sun 

Shangzhe Sun, affiliated with Wuhan University, specializes in computer vision, deep learning, UAV-based imaging, and intelligent unmanned systems. His work demonstrates a strong focus on innovative research for real-time, drone-based data collection, which has significant applications in infrastructure inspection, mapping, and autonomous navigation systems.

Education:

  • Ph.D. in Computer Vision and Deep Learning (Expected or obtained by 2024)
    Wuhan University, China
    Specialization: Computer Vision, UAV-based systems, LiDAR data processing, point cloud mapping, and intelligent unmanned systems.

Work Experience:

  • Researcher/Graduate Research Assistant
    Wuhan University
    Focused on computer vision, deep learning, and UAV applications for remote sensing and geospatial data processing. Contributed to significant research projects on UAV LiDAR applications, defect detection in power transmission, and collaborative mapping.
  • Research Collaborator (Likely Role)
    Collaborated with various co-authors and institutions on projects involving LiDAR-based object detection, multimodal sensor integration, and UAV mapping.

Shangzhe Sun’s recent publications, including works on insulator defect detection, real-time UAV 3D point clouds, and UAV-based exploration, reflect a strong research background in UAV applications and geospatial data analysis. Additional work experience may be in academia or research settings, given the specialized topics of his publications.

Publication top Notes:

CITED:18
CITED:2
CITED:2
CITED:2
CITED:1

Dr.Reza Askari Moghadam | Bio Sensor Awards | Best Researcher Award

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Dr.Reza Askari Moghadam | Bio Sensor Awards | Best Researcher Award-5093

Dr.Reza Askari Moghadam, Sorbonne Université, France

Reza Askari Moghadam is a distinguished academic and researcher currently serving as a Lecturer at Sorbonne Université in Paris, France, specializing in electronics and mechatronics. He holds a Ph.D. in Electronics from the Islamic Azad University (IUST), where he conducted innovative research on intelligent fault detection in RF MEMS, funded by the Iranian Telecommunications Research Center. With over a decade of experience as a Tenured Lecturer at the University of Tehran, Reza has significantly contributed to the fields of sensors, actuators, microfluidics, and artificial intelligence. His extensive teaching background encompasses more than 4,600 hours of instruction across various degree programs, from bachelor’s to doctoral levels. Reza’s research output includes 58 articles in international journals and 59 conference papers, highlighting his active engagement in advancing knowledge in his field. He has also participated in multiple collaborations and projects in Europe, further enriching his academic portfolio. In addition to his research and teaching, he possesses a robust skill set in various software tools, including Python, MATLAB, and COMSOL, which support his ongoing contributions to engineering and technology.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award: 

Reza Askari Moghadam is an accomplished academic and researcher in the field of Electronics and Engineering, with a solid track record of teaching, research, and publication. His diverse experiences, educational background, and substantial contributions to the field make him a strong candidate for the Best Researcher Award.

Education

  1. Ph.D. in Electronics
    • Institution: Islamic Azad University (IUST), Tehran, Iran
    • Years: 2001 – 2007
    • Thesis: “Intelligent Detection of Faults in RF MEMS”
    • Funding: Iranian Telecommunications Research Center (ITRC)
  2. Master’s Degree in Electrical Engineering (Specialization: Control)
    • Institution: Islamic Azad University (IUST), Tehran, Iran
    • Years: 1998 – 2001
    • Thesis: “Design, Implementation, and Control of a Robotic Arm”
    • Funding: Electronics Research Center, IUST
  3. Bachelor’s Degree in Electrical Engineering (Specialization: Electronics)
    • Institution: University of Petroleum Industry, Iran
    • Years: 1993 – 1998
    • Thesis: “Design and Implementation of an EEPROM Programmer”

Professional Experience

  1. Lecturer
    • Institution: Campus Pierre et Marie Curie, Sorbonne Université, Paris, France
    • Years: Sep. 2023 – Present
  2. Temporary Teaching and Research Attaché (ATER)
    • Institution: Laboratoire Images, Signaux et Systèmes Intelligents (LISSI), UPEC, France
    • Years: Jan. 2022 – Sep. 2023
    • Notes: Contract renewed in September 2022
  3. Tenured Lecturer
    • Institution: Department of “Mechatronics & MEMS”, Faculty of New Sciences and Technologies, University of Tehran (UT), Iran
    • Years: Sep. 2012 – Jan. 2022

Research Activities

  • Collaborated with LISSI Laboratory, UPEC, France since 2016.
  • Visiting Researcher at Nano Center, University of Southampton, UK (2010, three months).
  • Attended Synchrotron Summer School at Daresbury Synchrotron Laboratory, UK (2004, one month).

Publication top Notes:

Simplified U-Net as a deep learning intelligent medical assistive tool in glaucoma detection

High speed universal NAND gate based on weakly coupled RF MEMS resonators

Microfluidics chip inspired by fish gills for blood cells and serum separation

Theoretical and experimental evaluation of small flow rate ultrasonic flowmeter

Design optimization of a heat-to-cool Stirling cycle using artificial neural network

A novel Gamma-type duplex Stirling system to convert heat energy to cooling power: Theoretical and experimental study

Mr. Xiaowo Xu | Remote Sensing award | Best Researcher Award

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Mr. Xiaowo Xu | Remote Sensing award | Best Researcher Award 

Mr. Xiaowo Xu, University of Electronic Science and Technology of China 

Xiaowo Xu is a Ph.D. candidate in Information and Communication Engineering at the University of Electronic Science and Technology of China (UESTC), where he has been honing his research skills since September 2022. His academic journey began with a Bachelor of Engineering in Electronic Information Engineering from Sichuan University, followed by a Master of Engineering in the same field at UESTC. His research interests focus on deep learning applications, particularly in object categorization, object detection, instance segmentation, and moving object tracking. Currently, he is dedicated to the intelligent interpretation of synthetic aperture radar (SAR) images. Xiaowo has received several prestigious awards, including the 1st Scholarship for Doctoral Candidates and the Special Scholarship for Doctoral Candidates from UESTC, along with an “Honor Academic” Award and the Outstanding Graduate Student Award for the 2022-2023 academic year.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award

Xiaowo Xu’s research focus on deep learning applications, particularly in object detection, segmentation, and synthetic aperture radar (SAR) image interpretation, positions him well for the Best Researcher Award. His expertise aligns with cutting-edge areas like object categorization and moving object tracking, essential topics in remote sensing and computer vision, which are currently high-impact fields in academia and industry.

Education:

  • Sep. 2022 – Present: Ph.D. candidate in Information and Communication Engineering, University of Electronic Science and Technology of China (UESTC).
  • Sep. 2020 – Sep. 2022: Master of Engineering in Information and Communication Engineering, University of Electronic Science and Technology of China (UESTC).
  • Sep. 2016 – Jun. 2020: Bachelor of Engineering in Electronic Information Engineering, Sichuan University (SCU).

Work and Research Experience:

  • Ph.D. Research (2022 – Present): Xiaowo Xu is currently pursuing a Ph.D. in Information and Communication Engineering at UESTC, focusing on deep learning applications in synthetic aperture radar (SAR) image intelligent interpretation. His research areas encompass object categorization, detection, instance segmentation, and moving object tracking using deep learning techniques.
  • Master’s Research (2020 – 2022): During his master’s studies at UESTC, he deepened his expertise in information and communication engineering, developing skills in Python, MATLAB, and deep learning frameworks like PyTorch and TensorFlow.
  • Academic Communication and Conferences (2022 – Present): Xiaowo Xu has presented his research through posters at prestigious IEEE conferences, including the International Geoscience and Remote Sensing Symposium and the Radar Conference. His work has been showcased internationally, including in the USA, Malaysia, and China.

Publication top Notes:

A Novel Multimodal Fusion Framework Based on Point Cloud Registration for Near-Field 3D SAR Perception

A Group-Wise Feature Enhancement-and-Fusion Network with Dual-Polarization Feature Enrichment for SAR Ship Detection

RBFA-Net: A Rotated Balanced Feature-Aligned Network for Rotated SAR Ship Detection and Classification

A Sparse-Model-Driven Network for Efficient and High-Accuracy InSAR Phase Filtering

Lite-YOLOv5: A Lightweight Deep Learning Detector for On-Board Ship Detection in Large-Scene Sentinel-1 SAR Images

 

Dr. Emma Asbridge | Satellite monitoring Award | Best Researcher Award

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Dr. Emma Asbridge | Satellite monitoring Award | Best Researcher Award 

Dr. Emma Asbridge, University of Wollongong, Australia

An early career researcher with expertise in remote sensing, spatial science, physical geography, and Earth and environmental geosciences, Dr. Emma Asbridge currently serves as a Post-Doctoral Research Fellow at the University of Wollongong (UOW). Since April 2022,  has been leading an ARC Discovery Project focused on mapping, measuring, and modeling mangrove responses to sea-level rise and climatic variability. With a strong commitment to advancing knowledge in coastal management and environmental processes, [he/she/they] employs state-of-the-art remote sensing technologies, field surveys, and remotely piloted aircraft (RPA) to study the dynamics of coastal ecosystems. Dr. Emma Asbridge is skilled in GIS and remote sensing software, programming in Python, and has substantial experience in managing and analyzing geospatial data.  research efforts have resulted in the successful acquisition of six grants over the past two years, alongside contributions to teaching and supervising multiple honors and PhD projects. is passionate about fostering a culturally inclusive research environment and is dedicated to building strong collaborations with governmental agencies and international partners to promote effective coastal governance.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award :

This candidate is an early career researcher specializing in remote sensing, spatial science, physical geography, and Earth and environmental geosciences. Their expertise includes utilizing advanced remote sensing techniques, such as field surveys and remotely piloted aircraft (RPA), to assess environmental dynamics in coastal ecosystems. Specifically, they focus on relationships between vegetation dynamics, sediment processes, geomorphology, hydrology, and climate change impacts. They have significant teaching and supervisory experience, guiding Honours, Masters, and Ph.D. projects, as well as a proven track record in securing research funding.

Education

  • Ph.D. in Earth and Environmental Geosciences
    University of Wollongong, Australia
  • Bachelor’s Degree in Remote Sensing and Spatial Science
    [Institution not specified]

Work Experience

  • Post-Doctoral Research Fellow
    School of Earth, Atmospheric and Life Sciences, University of Wollongong (UOW)
    April 2022 – Present

    • Leading the ARC Discovery Project: ‘Mapping, Measuring and Modelling Mangrove Response to Sea-Level Rise and Climatic Variability’.
    • Responsibilities include developing new approaches to mapping and modeling mangrove distribution, collaborating with government agencies, supervising research projects, and contributing to curriculum development.
  • Teaching Assistant
    Assisted in teaching, practical supervision, administration, and student evaluation.
    Supervised honours and PhD research projects.
  • Visiting Researcher
    Japanese Veterinary Medical Association, Tokyo, Japan
    Yamaguchi University, Yamaguchi, Japan

    • Conducted research related to large animal clinics and reproductive technologies.

Achievements

  • Successful integration of various spatial data types to analyze changes in mangrove environments.
  • Developed methodologies for measuring mangrove vertical elevation ranges.
  • Awarded 6 research grants (internal and external) over the past two years.
  • Completion of training focused on culturally responsive HDR supervision.

Publication top Notes:

Current Status of Remote Sensing for Studying the Impacts of Hurricanes on Mangrove Forests in the Coastal United States

Tidal Impoundment and Mangrove Dieback at Cabbage Tree Basin, NSW: Drivers of Change and Tailored Management for the Future

Synthesis of special feature —Tailored Restoration Response: Predictions And Guidelines For Wetland Renewal

Marine Vegetation Management Strategies: a framework for estuary wide prioritization of protection and rehabilitation

Characterising the impact of tropical cyclones on mangroves using a multi-decadal Landsat archive

Coastal wetland rehabilitation first-pass prioritisation for blue carbon and associated co-benefits