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

Published on by Network Awards

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:

 

 

 

 

Mrs. Marcia Baptista | Machine Learning and Prognostics | Best Researcher Award

Published on by Network Awards

Mrs. Marcia Baptista | Machine Learning and Prognostics | Best Researcher Award

Mrs. Marcia Baptista, Delft University of Technology

Mrs. Marcia Baptista, currently an Assistant Professor at TU Delft and soon joining NOVA IMS, completed her Ph.D. in Engineering Design and Advanced Manufacturing at MIT Portugal Program 📚. Her research in machine learning and deep learning for prognostics in aeronautics, conducted in collaboration with Rolls Royce and Embraer, has led to significant advancements in predictive maintenance technology 🔬. Marcia’s career spans leadership roles at NASA Ames Research Center and Instituto Tecnológico de Aeronáutica, focusing on technical prognostics and system engineering across continents. Her contributions have earned her Best Paper awards at esteemed conferences and recognition for teaching excellence 🏆. Beyond academia, Marcia chairs international conference sessions, serves editorial roles, and contributes to advanced engineering literature 🌐.

🌐 Professional Profile:

Orcid

Scopus

📚 Education & Academic Path

I completed my Ph.D. in Engineering Design and Advanced Manufacturing at MIT Portugal Program, focusing on machine learning and deep learning for prognostics in aeronautics. This research involved collaborations with Rolls Royce and Embraer, resulting in significant advancements in predictive maintenance technology.

🔬 Research & Professional Experience

Currently serving as an Assistant Professor at TU Delft and starting soon at NOVA IMS, I’ve been actively involved in teaching, research, and leadership roles. My work spans multiple continents, including positions at NASA Ames Research Center and Instituto Tecnológico de Aeronáutica, where I contributed to cutting-edge projects in technical prognostics and system engineering.

🏆 Achievements & Recognition

Throughout my career, I’ve been honored with numerous awards, including Best Paper accolades at prestigious conferences like WCE 2019 and ISM 2019. I’ve also received recognition for my teaching contributions and was awarded a Doctorate Scholarship from the Foundation for Sciences and Technology in Portugal.

🌐 Contributions & Outreach

Beyond academia, I’ve chaired sessions at international conferences and served as a web chair for the Intelligent Transport Systems Conference. My editorial roles include being a special issue editor for prominent journals and authoring chapters on advanced engineering topics.

Publication Top Notes:

  • Aircraft Engine Bleed Valve Prognostics Using Multiclass Gated Recurrent Unit
    • Year: 2023
    • Citations: 2
  • 1D-DGAN-PHM: A 1-D denoising GAN for Prognostics and Health Management with an application to turbofan
    • Year: 2022
    • Citations: 4
  • Relation between prognostics predictor evaluation metrics and local interpretability SHAP values
    • Year: 2022
    • Citations: 57
  • A self-organizing map and a normalizing multi-layer perceptron approach to baselining in prognostics under dynamic regimes
    • Year: 2021
    • Citations: 14
  • Classification prognostics approaches in aviation
    • Year: 2021
    • Citations: 15

 

 

Assoc Prof Dr. Huaqiao Xing | Big Data Analysis | Best Researcher Award

Published on by Network Awards

Assoc Prof Dr. Huaqiao Xing | Big Data Analysis | Best Researcher Award

Assoc Prof Dr. Huaqiao Xing, Shandong Jianzhu University, China

👨‍🎓 Assoc Prof Dr. Huaqiao Xing, a distinguished scholar at Shandong Jianzhu University in China, is a beacon of academic excellence. 🏛️ Navigating the scholarly terrain with determination and brilliance, he has cultivated a deep reservoir of knowledge and expertise. Driven by a fervor for learning and discovery, Dr. Xing stands as a paragon of dedication to education. 🌐 His educational journey at Shandong Jianzhu University has shaped him into a knowledgeable individual poised to contribute meaningfully to both his field and society at large. As a visionary researcher, his expertise delves into cutting-edge fields, notably land cover change detection, unraveling the dynamics of our planet’s surface in environmental studies. 🌍 Proficient in Geospatial web service and online geoprocessing, he champions the integration of technology to enhance geographical information systems (GIS). 💻🌱 Dr. Xing’s research not only reveals the evolving landscapes but also contributes to the advancement of digital tools, paving the way for a more informed and sustainable future.

🎓 Education :

👨‍🎓 Dr. Huaqiao Xing is a distinguished scholar hailing from China, with his educational roots firmly grounded in the prestigious Shandong Jianzhu University. 🏛️ Armed with knowledge and expertise, he has undoubtedly navigated the academic landscape with determination and brilliance. 🌐 Driven by a passion for learning and discovery, he represents the epitome of dedication and excellence in education. 🌟 His journey at Shandong Jianzhu University has undoubtedly shaped him into a knowledgeable individual ready to contribute meaningfully to his field and society as a whole. 🚀🌏

🌐 Professional Profiles : 

Google Scholar

Scopus

🧠 Research Interests 🔬🌐 :

🌐 Dr. Huaqiao Xing, a visionary researcher, specializes in cutting-edge fields that redefine our understanding of the world. 🌍 His expertise spans across land cover change detection, a crucial aspect in environmental studies, unraveling the dynamics of our planet’s surface. 📊 In addition, his proficiency in Geospatial web service and online geoprocessing propels the integration of technology to enhance geographical information systems (GIS). 💻 Dr. Xing’s research not only unveils the evolving landscapes but also contributes to the advancement of digital tools that facilitate efficient geospatial analysis. 🌱 His work embodies the intersection of technology and environmental science, paving the way for a more informed and sustainable future. 🚀🔍

📚 Publication Impact and Citations : 

Scopus Metrics:

  • 📝 Publications: 52 documents indexed in Scopus.
  • 📊 Citations: A total of 287 citations for his publications, reflecting the widespread impact and recognition of Dr. Huaqiao Xing’s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 379 📖
    • h-index: 11 📊
    • i10-index: 14 🔍
  • Since 2018:
    • Citations: 346 📖
    • h-index: 11 📊
    • i10-index: 14 🔍

👨‍🏫 A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. 🌐🔬

Publications Top Notes  :

1.  Analysis of carbon emissions from land cover change during 2000 to 2020 in Shandong Province, China

Published in Scientific Reports (2022)

Cited by 28 articles

2.  V-RSIR: An open access web-based image annotation tool for remote sensing image retrieval

Published in IEEE Access (2019)

Cited by 27 articles

3.  A stacking ensemble deep learning model for building extraction from remote sensing images

Published in Remote Sensing (2021)

Cited by 22 articles

4.  Integrating change magnitude maps of spectrally enhanced multi-features for land cover change detection

Published in International Journal of Remote Sensing (2021)

Cited by 17 articles

5.  O-LCMapping: A Google Earth Engine-based web toolkit for supporting online land cover classification

Published in Earth Science Informatics (2021)

Cited by 15 articles

6.  A service relation model for web-based land cover change detection

Published in ISPRS Journal of Photogrammetry and Remote Sensing (2017)

Cited by 15 articles

7.  An adaptive change threshold selection method based on land cover posterior probability and spatial neighborhood information

Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2021)

Cited by 14 articles

8.  Exploiting low dimensional features from the MobileNets for remote sensing image retrieval

Published in Earth Science Informatics (2020)

Cited by 13 articles

9.  An attention-enhanced end-to-end discriminative network with multiscale feature learning for remote sensing image retrieval

Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2022)

Cited by 12 articles

10.  Two novel benchmark datasets from ArcGIS and Bing World Imagery for remote sensing image retrieval

Published in International Journal of Remote Sensing (2021)

Cited by 12 articles