Prof. Pinghui Wu | Technology | Best Researcher Award

Prof. Pinghui Wu | Technology | Best Researcher Award

Prof. Pinghui Wu | Technology – Division Chief of Scientific Research at Quanzhou Normal University, China

Prof. Wu Pinghui, a distinguished academic from Quanzhou Normal University, has made remarkable contributions to the fields of advanced optics, materials science, and thermal engineering. With a robust portfolio of research, Wu’s work reflects a passion for innovation and scientific exploration, particularly in areas like metamaterials and solar energy technologies. Known for a collaborative approach, Wu has worked with numerous international researchers, driving forward impactful studies that influence both theoretical and applied sciences.

Profile:

Orcid | Scopus | Google Scholar

Education:

Prof. Wu Pinghui pursued advanced studies in materials science and optical engineering, laying a strong foundation for a career marked by academic excellence and groundbreaking research. The educational journey involved rigorous training in both theoretical principles and practical applications, fostering expertise in cutting-edge technologies. This academic background has been pivotal in shaping Wu’s approach to complex scientific challenges and interdisciplinary collaborations. 🎓

Experience:

With years of dedicated academic service, Wu has held prominent research and teaching positions at Quanzhou Normal University. This experience includes mentoring graduate students, leading research projects, and contributing to curriculum development in scientific disciplines. Wu’s role extends beyond academia, with active participation in international conferences and collaborative research initiatives that span across institutions and countries. 🌍

Research Interests:

Wu’s research interests are diverse, encompassing optical materials, thermal energy systems, and metamaterial-based devices. Key areas include the development of ultra-broadband solar absorbers, terahertz smart devices, and advanced optical reinforcement materials. Wu’s work is characterized by a focus on sustainability, energy efficiency, and the application of novel materials to solve real-world technological problems. 🔬

Awards:

While specific awards are not detailed, Wu’s academic achievements, high citation count, and influential publications underscore a career recognized for excellence. The impact of Wu’s research is reflected in the widespread adoption of scientific findings and contributions to the academic community. 🏆

Selected Publications:

  1. “Highly Localized Linear Array of Optical Rings with Multiple Tunable Degrees of Freedom” (2025) – Optics Communications ✨
  2. “Highly Efficient Color Tuning of Lithium Niobate Nanostructures on Flexible Substrate” (2025) – Materials 🌈
  3. “Ultra-Broadband Solar Absorber and Near-Perfect Thermal Emitter Based on Columnar Titanium Micro-Structure” (2025) – Applied Thermal Engineering ☀️
  4. “Bi-Directional Metamaterial Perfect Absorber Based on Gold Grating and TiO₂-InAs Normal Hexagonal Pattern Film” (2025) – Solar Energy Materials and Solar Cells ⚡
  5. “Thermal Radiation Analysis of a Broadband Solar Energy-Capturing Absorber Using Ti and GaAs” (2025) – Dalton Transactions 🌞
  6. “Ultra-Broadband Absorber and Near-Perfect Thermal Emitter Based on Multi-Layered Grating Structure Design” (2025) – Energy 🔥
  7. “Terahertz Smart Devices Based on Phase Change Material VO₂ and Metamaterial Graphene” (2025) – Optics and Laser Technology 🌐

Cited By: Over 6,610 citations, reflecting the widespread influence and recognition of these works. 📚

Conclusion:

Prof. Wu Pinghui’s academic journey exemplifies a commitment to scientific excellence and innovation. The combination of extensive research output, impactful publications, and interdisciplinary collaborations highlights a career dedicated to advancing knowledge and technology. Wu’s contributions not only enrich the academic community but also inspire future generations of researchers. This nomination for the Best Researcher Award is a testament to the profound impact Wu has made in the scientific world. 🌟

Mr. Mohammad Mahdi Badami | Data Analysis | Young Scientist Award

Mr. Mohammad Mahdi Badami | Data Analysis | Young Scientist Award

Mr. Mohammad Mahdi Badami | University of Southern California | United States

Mehdi Badami is a dedicated Ph.D. candidate in Environmental Engineering at the University of Southern California (USC) under Prof. Constantinos Sioutas. His expertise lies in air quality improvement, with hands-on experience in air pollution monitoring using advanced instrumentation such as SMPS-CPC, OPS, and Aethalometer 51. He specializes in data-driven environmental assessments, employing Python for pollution source apportionment and emission trend analysis. His research contributes to community-centric environmental policies and sustainable air quality solutions. Passionate about environmental justice, he aims to bridge scientific research with real-world policy implementation. 🌱🔬

Professional Profile:

Google Scholar

Suitability for the Young Scientist Award

Mehdi Badami is a strong candidate for the Young Scientist Award due to his significant contributions to environmental engineering, particularly in air quality improvement. As a Ph.D. candidate at the University of Southern California (USC), his research focuses on air pollution monitoring and data-driven environmental assessments. His expertise in advanced instrumentation (e.g., SMPS-CPC, OPS, Aethalometer 51) and Python-based pollution source apportionment makes him a valuable asset to the field.

Education & Experience 🏢🎓

  • Ph.D. Candidate in Environmental Engineering (2022-Present) – USC, Los Angeles, USA 🇺🇸

    • GPA: 3.95/4
    • Advisor: Prof. Constantinos Sioutas
  • M.Sc. in Mechanical Engineering (Fluid Mechanics) (2017-2020) – University of Tehran, Iran 🇮🇷

    • GPA: 3.77/4
    • Supervisors: Dr. Alireza Riasi, Prof. Kayvan Sadeghy
  • B.Sc. in Mechanical Engineering (2012-2016) – K. N. Toosi University of Technology, Iran 🇮🇷

  • Research Assistant – USC Aerosol Lab (2023–Present) 🏭🌫️

    • Conducted air pollution measurements using state-of-the-art monitoring systems
    • Developed Python programs for data automation and pollution trend analysis
    • Led collaborations with institutions like Harvard, UCLA, and Dresden University
    • Mentored Ph.D. students on environmental research projects
  • Research Assistant – Hydro-kinetic Energy Lab, University of Tehran (2017–2022) 🔬💧

    • Investigated fluid mechanics phenomena related to blood hammer effects in arteries
  • Teaching Assistant – USC & University of Tehran (2018–2024) 📚👨‍🏫

    • Assisted in courses on climate change, air quality, fluid mechanics, and thermodynamics

Professional Development 🚀

Mehdi Badami has actively contributed to the field of environmental engineering through cutting-edge research on air pollution, sustainability, and emission control. His extensive knowledge of aerosol science, atmospheric chemistry, and data analysis allows him to assess air quality trends with precision. He has developed innovative models for pollution source apportionment, worked on real-time monitoring systems, and collaborated with leading institutions to improve urban air quality. His passion for environmental justice drives his work towards creating actionable solutions that ensure healthier air for communities. His dedication extends beyond academia, as he actively engages in outreach and policy-driven initiatives. 🌿📊

Research Focus 🔍

Mehdi’s research centers on air pollution control, environmental monitoring, and sustainable urban development. His work involves identifying and mitigating pollution sources through field measurements and computational models. He specializes in:

  • Air Quality Assessment 🌫️📊 – Studying PM2.5 and ultrafine particle pollution in urban environments
  • Pollution Source Apportionment 🏭⚖️ – Analyzing emissions from vehicles, industries, and natural sources
  • Aerosol Science 🌪️💨 – Investigating the toxicity and health impacts of airborne particles
  • Machine Learning in Environmental Studies 🤖📉 – Utilizing data science to model pollution trends
  • Climate and Environmental Justice 🌎⚖️ – Advocating for equitable air quality policies in urban communities

Awards & Honors 🏆

  • Outstanding Research Assistant Award – USC, Sonny Astani Department of Civil and Environmental Engineering (2024) 🏅
  • Fellowship Award – USC (2022-2023) 🎓💰 (Recognized for academic excellence in Environmental Engineering)
  • National Fellowship for Master’s Studies – University of Tehran (2017) 📖🏆
  • Top 0.15% Rank in National Entrance Exam – Iran (Competitive ranking in Mechanical Engineering)

Publication Top Notes:

📄 Design, optimization, and evaluation of a wet electrostatic precipitator (ESP) for aerosol collectionAtmospheric Environment (2023) – 📑 Cited by: 11
📄 Size-segregated source identification of water-soluble and water-insoluble metals and trace elements of coarse and fine PM in central Los AngelesAtmospheric Environment (2023) – 📑 Cited by: 7
📄 Numerical study of blood hammer phenomenon considering blood viscoelastic effectsEuropean Journal of Mechanics-B/Fluids (2022) – 📑 Cited by: 7
📄 Development and performance evaluation of online monitors for near real-time measurement of total and water-soluble organic carbon in fine and coarse ambient PMAtmospheric Environment (2024) – 📑 Cited by: 4
📄 Numerical analysis of laminar viscoelastic fluid hammer phenomenon in an axisymmetric pipeJournal of the Brazilian Society of Mechanical Sciences and Engineering (2021) – 📑 Cited by: 3
📄 Urban emissions of fine and ultrafine particulate matter in Los Angeles: Sources and variations in lung-deposited surface areaEnvironmental Pollution (2025) – 📑 Cited by: 1

 

 

 

Prof. Dr. Lei Geng | Data Analysis | Best Researcher Award

Prof. Dr. Lei Geng | Data Analysis | Best Researcher Award

Prof. Dr. Lei Geng, Tiangong University, China

Prof. Dr. Lei Geng is a distinguished professor at the School of Life Sciences, Tiangong University, with a focus on computer vision, machine learning, and measurement technology. He received his Ph.D. in 2012 from Tianjin University and has since made significant contributions to the fields of AI, machine vision, and medical technology. With over 80 published papers, Dr. Geng has played a pivotal role in the development of advanced imaging and measurement technologies for industrial and medical applications. His research includes applications in image analysis, 3D dimensional measurement, and hemostatic medical equipment. As a leader in his field, he has led more than 10 national and provincial-level projects and received numerous awards for his technological innovations. 🚀

Professional Profile:

Scopus
Orcid

Suitability for the Award

Prof. Dr. Lei Geng is highly suitable for the Best Researcher Award due to his groundbreaking work in AI, machine vision, and medical technology. His research has led to the development of advanced image analysis techniques and high-precision measurement tools, with far-reaching implications for both industrial and healthcare applications. Dr. Geng’s leadership in national and provincial projects, combined with his three provincial-level awards, highlights his ability to drive technological advancements that have a direct impact on society. His contributions to AI-based diagnostics, particularly in otolaryngology, underscore his dedication to improving healthcare through cutting-edge technologies. Prof. Geng’s consistent excellence in research, innovation, and application makes him an ideal candidate for this prestigious award. 🏅

Education

🎓 Dr. Lei Geng earned his Ph.D. in 2012 from Tianjin University, specializing in areas at the intersection of computer vision, machine learning, and measurement technology. His academic journey laid the foundation for his extensive contributions to these fields, including the development of cutting-edge applications in industrial and medical sectors. Dr. Geng’s deep understanding of both theoretical and practical aspects of machine vision and artificial intelligence has made him an expert in creating innovative solutions across multiple industries. His education has fueled his ongoing research and contributions to advancements in AI-driven healthcare and precision measurement technologies. 📘

Experience

🧑‍🏫 Prof. Dr. Lei Geng has extensive teaching and research experience, currently serving as a professor at the School of Life Sciences at Tiangong University. He has been involved in both undergraduate and postgraduate education, teaching courses such as Machine Vision and Deep Learning. Over his career, Dr. Geng has undertaken more than 10 national, provincial, and ministerial-level projects, focusing on industrial and medical applications of machine vision and AI. His experience includes pioneering work in hemostatic medical equipment and high-precision 2D/3D measurement systems. This broad range of expertise positions Dr. Geng as a leader in his field, particularly in the integration of AI technologies with practical, real-world applications. 🌍

Awards and Honors

🏅 Dr. Lei Geng’s excellence in research and technological innovation has been recognized through several prestigious awards. He has received three provincial-level awards, including the Tianjin Second Prize for Technological Invention and the Special Prize of the National Award for Business Science and Technology Progress. These accolades are a testament to his significant contributions to the fields of AI, computer vision, and medical technology. Dr. Geng’s ability to bridge the gap between advanced scientific research and practical applications in industries such as healthcare and manufacturing has made him a highly respected figure in the scientific community. 🌟

Research Focus

🔬 Dr. Lei Geng’s research focuses on four key areas:

  1. Image Analysis & Understanding: Developing AI-based systems for image classification, object detection, and segmentation for industrial and medical applications.
  2. Dimensional Measurement: Applying machine vision and 3D scanning technology for high-precision industrial measurement and target positioning.
  3. Hemostatic Medical Equipment: Innovating in extracorporeal compression and intravascular interventional devices for medical bleeding control.
  4. AI in Otorhinolaryngology: Applying deep learning for disease diagnosis in ear, nose, and throat (ENT) medicine.

His work in these areas aims to integrate AI and machine vision to solve real-world problems, particularly in medical diagnostics and industrial automation. 💡

Publication Top Notes:

  • Direct May Not Be the Best: An Incremental Evolution View of Pose Generation
    • Year: 2024
    • Citations: 1
  • Multi-parametric investigations on the effects of vascular disrupting agents based on a platform of chorioallantoic membrane of chick embryos
    • Year: 2024
  • Label-Aware Dual Graph Neural Networks for Multi-Label Fundus Image Classification
    • Year: 2024
  • Cross-scale contrastive triplet networks for graph representation learning
    • Year: 2024
    • Citations: 4
  • Objective rating method for fabric pilling based on LSNet network
    • Year: 2024
    • Citations: 3

Shadi Atalla | Data Science | Best Researcher Award

Shadi Atalla | Data Science | Best Researcher Award

Dr. Shadi Atalla, University of DUbai, United Arab Emirates.

Publication profile

Googlescholar

Education:

  • Ph.D. in Computer Networks, Politecnico di Torino, Italy (2012) 🎓🇮🇹
  • M.Sc. in Computer and Communication Networks, Politecnico di Torino, Italy (2008) 💻📡
  • B.Sc. in Computer Engineering, An-Najah National University, Palestine (2004) 🖥️🇵🇸

Experience:

  • Associate Professor & Director, Computing & Information Systems, University of Dubai (2021–Present) 🏫💼
  • Assistant Professor, University of Dubai (2016–2021) 🏫📚
  • Visiting Professor, Al Ghurair University, Dubai (2014–2016) 🌍🎓
  • Post-Doctoral Researcher, Istituto Superiore Mario Boella, Italy (2012–2014) 🧑‍💻🇮🇹
  • Researcher, Istituto Superiore Mario Boella, Italy (2008–2009) 🔬🇮🇹
  • Teaching Assistant, An-Najah National University, Palestine (2004–2006) 📚🇵🇸
  • Network Architect, Net Point Company for Wireless Communication, Palestine (2004) 🌐🔧

Suitability For The Award

Dr. Shadi Atalla is an outstanding candidate for the Best Researcher Award due to his significant contributions to the fields of computing, information systems, and data science. With a proven track record of high-impact research, leadership in academic programs, and a commitment to advancing cutting-edge technologies, Dr. Atalla has consistently demonstrated excellence in his field. His involvement in internationally recognized projects, coupled with his ability to secure substantial research funding, positions him as a leading researcher in his domain.

Professional Development 

Dr. Shadi Atalla has participated in numerous professional development programs to enhance his expertise in the ever-evolving fields of computing and data science. He has completed certifications in Applied Data Science, Machine Learning, and Python from the University of Michigan and IBM, showcasing his commitment to continuous learning. He has also participated in training on program assessment and accreditation (ABET), Generative AI, and various data science applications. His focus on innovation is evident from his active engagement in professional development programs that enable him to integrate new technologies such as AI, cloud computing, and big data analytics into academic curricula. 🧑‍🏫💡📊

Research Focus 

Awards and Honors

  • Excellence in Research Award, University of Dubai (2022, 2019) 🏆📚
  • Best Paper Award, ICSPIS 2022 🥇📑
  • Honours College, An-Najah National University 🏅🎓
  • TopMed 2nd Level Master Scholarship (2 years) 🎓🌍
  • Full Politecnico di Torino PhD Scholarship (3 years) 🎓🇮🇹

Publoication Top Notes

  1. Smart real-time healthcare monitoring and tracking system using GSM/GPS technologies
    K Aziz, S Tarapiah, SH Ismail, S Atalla | Cited by: 167 | Year: 2016 📡🏥
  2. Decoding ChatGPT: a taxonomy of existing research, current challenges, and possible future directions
    SS Sohail, F Farhat, Y Himeur, M Nadeem, DØ Madsen, Y Singh, S Atalla, … | Cited by: 157 | Year: 2023 🤖📚
  3. A comprehensive review of recent research trends on unmanned aerial vehicles (UAVs)
    K Telli, O Kraa, Y Himeur, A Ouamane, M Boumehraz, S Atalla, … | Cited by: 117 | Year: 2023 🚁🔍
  4. An innovative deep anomaly detection of building energy consumption using energy time-series images
    A Copiaco, Y Himeur, A Amira, W Mansoor, F Fadli, S Atalla, SS Sohail | Cited by: 83 | Year: 2023 🏠⚡
  5. Scientometric Analysis and Classification of Research Using Convolutional Neural Networks: A Case Study in Data Science and Analytics
    M Daradkeh, L Abualigah, S Atalla, W Mansoor | Cited by: 56 | Year: 2022 📊🧠
  6. IoT-enabled precision agriculture: Developing an ecosystem for optimized crop management
    S Atalla, S Tarapiah, A Gawanmeh, M Daradkeh, H Mukhtar, Y Himeur, … | Cited by: 55 | Year: 2023 🌾📡
  7. Social Media for Teaching and Learning within Higher Education Institution: A Bibliometric Analysis of the Literature (2008-2018)
    KF Hashim, A Rashid, S Atalla | Cited by: 54 | Year: 2018 📱📚

 

Prof. Wan Quan Liu | Big Data Analysis | Best Researcher Award

Prof. Wan Quan Liu | Big Data Analysis | Best Researcher Award

Prof. Wan Quan Liu, Sun Yat-sen University, China

Prof. Wan Quan Liu is a prominent professor at the School of Intelligent System Engineering at Sun Yat-sen University, where he has been serving since 2021. He earned his Ph.D. in Electrical Engineering from Shanghai Jiaotong University (1991-1993) and holds a Master of Science in Operational Research and Control from the Institute of Systems Science at the Chinese Academy of Science (1985-1988), as well as a Bachelor’s degree in Mathematics from Qufu Normal University (1981-1985). Previously, he was an ARC Fellow and Senior Lecturer at Curtin University of Technology from 2000 to 2021. Prof. Liu’s research focuses on computer vision, deep learning networks, optimization, and intelligent control systems, where he has made significant contributions that advance these fields.

Professional Profile

Scopus
Orcid

Suitability for the Best Researcher Award:

Prof. Wan Quan Liu’s combination of an extensive educational background, significant research contributions, and recognition in the form of awards makes him an excellent candidate for the Best Researcher Award. His work in computer vision, deep learning, and intelligent control systems is highly relevant in today’s technology-driven landscape, with implications for various sectors including robotics, automation, and artificial intelligence.

The recognition he has received, both at the national and provincial levels, further solidifies his status as a leading researcher in his field. His ongoing research and publications contribute to advancements in critical technologies, making a tangible impact on both academia and industry.

Educational Background:

Prof. Wan Quan Liu earned his PhD in Electrical Engineering from Shanghai Jiaotong University (1991-1993). He holds a Master of Science in Operational Research and Control from the Institute of Systems Science at the Chinese Academy of Science (1985-1988) and a Bachelor’s degree in Mathematics from Qufu Normal University (1981-1985).

Academic Experience:

Currently, Prof. Liu is a professor at the School of Intelligent System Engineering at Sun Yat-sen University (2021-present). Prior to this, he held various positions, including ARC Fellow and Senior Lecturer at Curtin University of Technology (2000-2021).

Research Interests:

Prof. Liu specializes in computer vision, deep learning networks, optimization, and intelligent control systems, contributing significantly to advancements in these fields.

Awards and Recognition:

His exceptional work has earned him several accolades, including:

  • 2023: National Talented Researcher from the National Education Committee
  • 2022: Pearl Leading Researcher from Guangdong Province

Publication Top Notes:

  • Title: AFS-FCM with Memory: A Model for Air Quality Multi-dimensional Prediction with Interpretability
    • Publication Year: 2024
  • Title: Efficient and Fast Joint Sparse Constrained Canonical Correlation Analysis for Fault Detection
    • Publication Year: 2024
  • Title: Efficient and Robust Sparse Linear Discriminant Analysis for Data Classification
    • Publication Year: 2024
  • Title: FedREM: Guided Federated Learning in the Presence of Dynamic Device Unpredictability
    • Publication Year: 2024
  • Title: Invertible Residual Blocks in Deep Learning Networks
    • Publication Year: 2024

 

Prof. Jianfeng Guo | Big Data Analysis in Innovation | Best Researcher Award

Prof. Jianfeng Guo | Big Data Analysis in Innovation | Best Researcher Award

Prof. Jianfeng Guo, University of Chinese Academy of Sciences, China

Prof. Jianfeng Guo is a distinguished professor at the Energy and Environmental Policy Research Center of the Institute of Policy and Management, Chinese Academy of Sciences (CAS), where he has been a key figure since 2010 and has served as a professor since 2018. He earned his Ph.D. in Mechanical Engineering and Automation from Zhejiang University in 2007 and completed postdoctoral research at Tsinghua University. Jianfeng’s research spans Energy and Environmental Policy, Big Data Analysis, Technology Foresight, Decision Support Systems, and Knowledge Management. He has led over 60 significant projects, including collaborations with Baidu Big Data Lab and Ant Financial Services Group, and has published more than 90 papers and holds multiple patents and software copyrights. His international experience includes visits to top institutions and collaborations with global software companies.

🌍 Professional Profile

Scopus

🎓 Education

Jianfeng Guo earned his Ph.D. in Mechanical Engineering and Automation from Zhejiang University in December 2007. He completed postdoctoral research at the CIMS Engineering Research Center of Tsinghua University from January 2008 to December 2009. He was a Senior Visiting Scholar at NEC China Research Institute from August 2009 to March 2010.

🔬 Research Interests

Jianfeng specializes in Energy and Environmental Policy, Big Data Analysis, Technology Foresight, Decision Support Systems, and Knowledge Management.

🏢 Current Position

Since March 2010, Jianfeng has been with the Energy and Environmental Policy Research Center of the Institute of Policy and Management, Chinese Academy of Sciences (CAS), where he has served as a professor since 2018. He is also the Director of the Research Department for Think Tank Construction at the Institutes of Science and Development, CAS.

🌐 Notable Projects & Collaborations

Jianfeng has led over 60 projects, including NSFC projects, national programs, and enterprise-commissioned projects. He has collaborated with Baidu Big Data Lab and Ant Financial Services Group, contributing to advancements in big data and financial security.

📝 Publications & Patents

He has published more than 90 papers, including over 60 in international journals, and holds 4 invention patents and 15 computer software copyrights.

🌍 International Experience

Jianfeng has visited prestigious institutions such as the University of Oldenburg, Imperial College, and Cambridge University, and worked with international software companies like ASCORA and TIE.

Publication Top Notes:

  • Title: Graph-based algorithm for exploring collaboration mechanisms and hidden patterns among top scholars
    • Cited by: 1
    • Year: 2024
  • Title: A framework of cloud-edge collaborated digital twin for flexible job shop scheduling with conflict-free routing
    • Cited by: 3
    • Year: 2024
  • Title: Simulation research on the evolution pathway planning of energy supply and demand in China under the dual carbon targets
    • Cited by: 2
    • Year: 2023
  • Title: Electric vehicle adoption and local PM2.5 reduction: Evidence from China
    • Cited by: 7
    • Year: 2023
  • Title: Pathways for municipalities to achieve carbon emission peak and carbon neutrality: A study based on the LEAP model
    • Cited by: 53
    • Year: 2023

 

 

 

Prof. Mamede de Carvalho | Big Data Awards | Best Researcher Award

Prof. Mamede de Carvalho | Big Data Awards | Best Researcher Award

Prof. Mamede de Carvalho, Faculdade de Medicina , Universidade de Lisboa, Portugal

Prof. Mamede de Carvalho is a distinguished medical professional renowned for his contributions to neurology and physiology. He obtained his MD from Nova Lisbon University in 1985, specializing in Neurology at the University Hospital in Lisbon in 1993. He earned his PhD in Neurology from the University of Lisbon in 2000, followed by a Habilitation in Neurosciences in 2007. Since 2010, he has served as a Full Professor of Physiology at the University of Lisbon, where he has made significant advancements in clinical neurology, particularly in ALS and neuromuscular disorders. Prof. de Carvalho’s leadership roles include Vice-Dean at the Faculty of Medicine and President of the Reynaldo dos Santos Technological Center in Lisbon. He also directed the Neuromuscular Unit at CHLN – Hospital de Santa Maria from 2009 to 2019, further cementing his impact on neurology research and practice.

🌐 Professional Profile:

Scopus

Orcid

Google Scholar

🎓 Education

Prof. Mamede de Carvalho is a distinguished medical professional with a robust academic background. He obtained his MD from Nova Lisbon University in Lisbon, Portugal, in 1985, followed by specialization in Neurology at the University Hospital in Lisbon in 1993. He earned his PhD in Neurology from the University of Lisbon in 2000 and completed his Habilitation in Neurosciences at the same institution in 2007. Since 2010, he has served as a Full Professor of Physiology at the University of Lisbon, contributing significantly to the fields of neurology and neuroscience through his research and academic leadership.

🌐 Professional Experience & Leadership

Prof. Mamede de Carvalho is a distinguished figure in neurology and physiology, having served as the President of the Reynaldo dos Santos Technological Center in Lisbon, Portugal, from 2017 to 2022. Prior to this, he held the position of Vice-Dean at the Faculty of Medicine – University of Lisbon from 2015 to 2022. With extensive expertise, he also served as the Director of the Neuromuscular Unit at CHLN – Hospital de Santa Maria in Lisbon from 2009 to 2019, contributing significantly to advancements in clinical neurology and neuromuscular disorders.

🔬 Clinical Research & Funding

Prof. Mamede de Carvalho is a pioneering figure in clinical neurology research, renowned for his contributions to advancements like Transcranial Magnetic Stimulation and the Threshold Technique for Axonal Excitability. His leadership has been instrumental in securing significant funding for projects focused on amyotrophic lateral sclerosis (ALS) and other neurodegenerative diseases, including grants from JPND and FCT.

Publication Top Notes: