Mubarak Albathan | AI | Best Researcher Award

Dr Mubarak Albathan | AI | Best Researcher Award

Dr Mubarak Albathan , Imam Mohammad Ibn Saud Islamic University (IMSIU) ,Saudi Arabia

Dr. Mubarak Albathan is the Head of the Computer and Information Sciences Research Center and an Assistant Professor at Imam Muhammad Ibn Saud Islamic University in Riyadh, Saudi Arabia. He has a robust academic background, holding a PhD in Data Mining from Queensland University of Technology (QUT). With over a decade of experience in higher education, Dr. Albathan has made significant contributions to the fields of computer science and data analytics. He serves as a consultant to the Vice Rector for Graduate Studies and Scientific Research and has held various leadership roles in academia. Dr. Albathan is passionate about integrating advanced technologies into educational frameworks and enhancing research capabilities in the region. His work aims to bridge the gap between theoretical research and practical applications, driving innovation in data-driven solutions across various industries.

Publication Profile

Google Scholar

Strengths for the Award

Dr. Mubarak Albathan has demonstrated exceptional academic and research capabilities, exemplified by his extensive publication record and impactful research contributions. His work spans various critical areas, including data mining, machine learning, and healthcare applications, showcasing his versatility and innovation. Notably, he has received accolades such as the Best Student Paper Award and the International Publication Award, affirming his standing in the research community. As Head of the Computer and Information Sciences Research Center, he leads initiatives that enhance research quality and foster collaboration. Dr. Albathan’s commitment to integrating advanced technologies into practical solutions further underscores his qualifications for this prestigious award.

Areas for Improvement

While Dr. Albathan has a robust publication record, increasing the frequency of solo-authored publications could enhance his visibility as an independent researcher. Additionally, engaging in more interdisciplinary collaborations could broaden his research impact and foster innovative approaches. Expanding his outreach efforts to disseminate research findings beyond academic circles may also enhance community engagement and application of his work.

Education 

Dr. Mubarak Albathan earned his PhD in Data Mining from Queensland University of Technology (QUT) in 2015. He completed his Master’s degree in Network Computing at Monash University in 2009, where he developed a strong foundation in network systems and computational techniques. Prior to that, he received his Bachelor’s degree in Computer Science from Al-Imam Muhammad Ibn Saud Islamic University in 2004. This comprehensive educational background has equipped Dr. Albathan with the skills and knowledge necessary to excel in both academic and practical applications of computer science. His studies have focused on various aspects of computing, data mining, and network systems, leading him to engage in cutting-edge research and contribute to significant advancements in technology and education.

Experience 

Dr. Mubarak Albathan has extensive experience in academia and research management. Currently, he is the Head of the Computer and Information Sciences Research Center, a position he has held since 2023. He has also served as a consultant to the Vice Rector for Graduate Studies and Scientific Research since 2019. His previous roles include Deputy Director of the Electronic Scientific Research Portal initiative at the Ministry of Education from 2017 to 2019 and Vice-Chair of the Computer Science Department at his university from 2016 to 2017. Dr. Albathan has been involved in several academic projects and has acted as a sessional academic at QUT. His earlier experience includes supervising a diploma program in Computer Applications, showcasing his commitment to education and professional development in the field of computer science.

Awards and Honors

Dr. Mubarak Albathan has received numerous accolades for his academic and research contributions. He was awarded the Best Student Paper Award at the 2014 IEEE/WIC/ACM International Conferences on Web Intelligence in Warsaw, Poland, recognizing his exceptional research in the field. In 2015, he was honored with the International Publication Award from Imam Muhammad Ibn Saud Islamic University for his prolific contributions to scholarly publications. Dr. Albathan’s work has been recognized internationally, with his participation in several prestigious conferences, including the IEEE International Conference on Data Mining and the Australasian Joint Conference on Artificial Intelligence. His commitment to advancing knowledge in computer science and data mining continues to be acknowledged through various awards, highlighting his impact on the academic community and his dedication to research excellence.

Research Focus 

Dr. Mubarak Albathan’s research focuses on data mining, machine learning, and their applications in various domains, including healthcare, agriculture, and cybersecurity. His work emphasizes the development of optimized algorithms for pattern recognition and classification, particularly in complex datasets. Dr. Albathan is particularly interested in leveraging advanced technologies such as deep learning to address real-world challenges, such as disease diagnosis through image analysis and enhancing security protocols in IoT networks. His collaborative research projects have led to significant advancements in understanding and improving data-driven systems. Dr. Albathan’s commitment to integrating theoretical research with practical applications makes him a key contributor to the field, driving innovation and supporting the development of efficient, scalable solutions that benefit multiple sectors.

Publications Top Notes

  • Mobile-HR: An Ophthalmologic-Based Classification System for Diagnosis of Hypertensive Retinopathy Using Optimized MobileNet Architecture. 🩺
  • Leveraging Ethereum Platform for Development of Efficient Tractability System in Pharmaceutical Supply Chain. 💊
  • EfficientPNet—An Optimized and Efficient Deep Learning Approach for Classifying Disease of Potato Plant Leaves. 🌾
  • Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier. 🦠
  • A Supervised Method to Enhance Distance-based Neural Networks’ Clustering Performance by Discovering Perfect Representative Neurons. 🧠
  • Effective 20 Newsgroups Dataset Cleaning. 📊
  • Relevance Feature Discovery for Text Mining. 📖
  • Using Extended Random Set to Find Specific Patterns. 🔍
  • Interpreting Discovered Patterns in Terms of Ontology Concepts. 📚
  • Enhanced N-gram Extraction Using Relevance Feature Discovery. 🌐
  • Using Patterns Co-occurrence Matrix for Cleaning Closed Sequential Patterns for Text Mining. 📈
  • A Deep Learning Framework for the Prediction and Diagnosis of Ovarian Cancer in Pre- and Post-Menopausal Women. 🎗️
  • Optimized Deep Learning Techniques for Disease Detection in Rice Crop Using Merged Datasets. 🌱
  • Detection of Depression Trends in Literary Cyber Writers Using Sentiment Analysis and Machine Learning. 📖
  • Deep-Ocular: Improved Transfer Learning Architecture Using Self-Attention and Dense Layers for Recognition of Ocular Diseases. 👁️
  • ROAST-IoT: A Novel Range-Optimized Attention Convolutional Scattered Technique for Intrusion Detection in IoT Networks. 🔒
  • Enhancing Cloud-Based Security: A Novel Approach for Efficient Cyber-Threat Detection Using GSCSO-IHNN Model. ☁️

Conclusion

Dr. Mubarak Albathan is a highly qualified candidate for the Best Researcher Award. His impressive educational background, extensive experience, and significant contributions to research make him a standout in his field. By focusing on areas for improvement, he can further solidify his impact on academia and industry. Recognizing his achievements through this award would not only honor his dedication but also inspire future researchers in the field.

 

 

Xiaodan Shi | Deep Learning | Best Researcher Award

Dr. Xiaodan Shi | Deep Learning | Best Researcher Award

Postdoctoral researcher, Malardalen University,

Congratulations to Dr. Xiaodan Shi for receiving the Best Researcher Award in Deep Learning! 🏆 As a postdoctoral researcher at Malardalen University in Sweden, Dr. Shi has demonstrated exceptional dedication and innovation in advancing the field of deep learning. Their contributions have not only expanded our understanding but also paved the way for groundbreaking applications across various domains. Dr. Shi’s expertise and commitment to excellence serve as an inspiration to peers and aspiring researchers alike. This prestigious recognition is a testament to their outstanding achievements and significant impact on the scientific community. 🌟

Profile

Orcid

Education Background 📚

Xiaodan Shi has pursued an impressive academic journey, including a Ph.D. in Center for Spatial Information Science from The University of Tokyo, Japan. With a Master’s in Photogrammetry and Remote Sensing from Wuhan University, China, and a Bachelor’s in Remote Sensing and Information Science, Xiaodan Shi has built a solid foundation in engineering and spatial information science.

Work Experiences 💼

Xiaodan Shi brings a wealth of experience to the table, serving as a PostDoc at the Future Energy Center, Malardalen University, and previously as a Researcher at the Center for Spatial Information Science, The University of Tokyo. With expertise in algorithm engineering and urban remote sensing image processing, Xiaodan Shi has made significant contributions to the field of spatial information science.

Research Interests 🔬

Xiaodan Shi’s research interests encompass deep learning in sequential prediction and clustering, as well as urban remote sensing image processing. With a focus on developing innovative solutions for complex spatial data analysis, Xiaodan Shi’s work addresses critical challenges in areas such as trajectory prediction and time series forecasting.

Awards 🏆

Xiaodan Shi’s academic achievements have been recognized through various awards and scholarships, including the ISPRS Best Young Author Award and the MEXT Scholarship from the Japanese Government. Xiaodan Shi’s dedication to research excellence is evident in their contributions to top-tier conferences and journals in the field of artificial intelligence and remote sensing.

 Publications Top Notes 📖

“Multivariate Time Series Prediction for CO2 Concentration and Flue Gas Flowrate from Biomass-Fired Power Plant” – Fuel, 2023

“MetaTraj: Meta-learning for Cross-scene Cross-object Trajectory Prediction” – IEEE Transactions on Intelligent Transportation Systems, 2023y

“MobCovid: Confirmed Cases Dynamics Driven Time Series Prediction of Crowd in Urban Hotspot” – IEEE Transactions on Neural Networks and Learning Systems, 2023

“PredLife: Predicting Fine-grained Future Activity Patterns” – IEEE Transactions on Big Data, 2023

“Mutual Adaptation: Learning from Prototype for Time Series Prediction” – IEEE Transactions on Artificial Intelligence, 2023

Gianpaolo Coro | Artificial Intelligence | Best Researcher Award

Dr. Gianpaolo Coro | Artificial Intelligence | Best Researcher Award

Researcher, National Research Council of Italy – CNR, Italy

🏆 Dr. Gianpaolo Coro, an esteemed researcher at the National Research Council of Italy – CNR, has been honored with the prestigious Best Researcher Award in the field of Artificial Intelligence. With a remarkable dedication to advancing AI technologies, Dr. Coro’s contributions have significantly enriched the scientific community. His innovative research initiatives have propelled the boundaries of AI, fostering breakthroughs that promise to reshape industries and improve societal well-being. Through his unwavering commitment and visionary insights, Dr. Coro continues to inspire and lead the way towards a future empowered by cutting-edge AI solutions. 🌟

Profile

Scopus

Research areas

Artificial Intelligence 🤖, Automatic Speech Recognition 🗣️, Cybernetics 🔍, Natural Language Processing 📝, Ecological Modelling 🌿, Cloud Computing ☁️, Research e-Infrastructures 🖥️, and Open Science 🔓 stand as the pillars of modern scientific exploration. These fields intertwine to push the boundaries of knowledge and innovation. From deciphering human speech to simulating complex ecosystems, each domain contributes uniquely to our understanding of the world. Moreover, advancements in cloud computing and e-infrastructures facilitate collaborative research on a global scale, fostering open science initiatives that promote transparency and accessibility. Together, these disciplines form a dynamic landscape of inquiry, driving forward progress and unlocking new realms of possibility. 🌐

Work experience

Gianpaolo Coro served as a dedicated Research Fellow from November 2012 to September 2013, marking the inception of his illustrious career journey. Employed at the Istituto di Scienza e Tecnologie dell’Informazione A. Faedo of the National Research Council of Italy (CNR-ISTI), Coro embarked on his exploration of Artificial Intelligence applications in computational biology and natural language processing. His endeavors were rooted in Open Science principles, utilizing innovative computer systems and cloud computing infrastructure. This period laid the groundwork for Coro’s subsequent advancements, shaping his expertise in interdisciplinary research domains. 🌱

Education

🎓 Gianpaolo Coro achieved his Doctor of Philosophy in Computer Science from the University of Naples Federico II, specializing in Cybernetics, Natural Language Processing, and Speech Processing. Under the guidance of Professors Ernesto Burattini and Francesco Cutugno, his groundbreaking thesis titled “A Step Forward in Multi-granular Automatic Speech Recognition” introduced a novel approach to speech recognition, integrating models operating at multiple temporal scales. This marked a significant advancement in the field. Coro’s academic journey also includes a degree in Physics, where he focused on similar subjects. Throughout his educational path, he exhibited exceptional prowess, earning top honors and recognition for his outstanding achievements. 🌟

Awards

Gianpaolo Coro’s exceptional contributions have been recognized through numerous prestigious awards and accolades. His achievements include receiving the Abilitazione Scientifica Nazionale as Associate Professor, affirming his expertise in Systems for Information Processing. Coro’s dedication to research excellence was further underscored by his receipt of the EOSC Secretariat COVID-19 Fast Track Funding Award for his project on modeling SARS-CoV-2 spread. Additionally, he was honored with the Best Paper Award by the ICES Journal of Marine Science and received grants from NVIDIA Corporation for his research endeavors. Furthermore, Coro’s early career was distinguished by successive Young Researcher Awards from the ISTI-CNR, highlighting his promising trajectory in academia. 🌟

Publications Top Notes

  1. An exploratory approach to data driven knowledge creation
    • Year: 2023
    • Authors: Thanos, C.; Meghini, C.; Bartalesi, V.; Coro, G.
    • Journal: Journal of Big Data
    • Article Type: Article (Open access)
  2. Global-scale parameters for ecological models
    • Year: 2023
    • Authors: Coro, G.; Bove, P.; Kesner-Reyes, K.
    • Journal: Scientific Data
    • Article Type: Data Paper (Open access)
  3. Virtual research environments co-creation: The D4Science experience
    • Year: 2023
    • Authors: Assante, M.; Candela, L.; Castelli, D.; Piccioli, T.; Sinibaldi, F.
    • Journal: Concurrency and Computation: Practice and Experience
    • Article Type: Conference Paper
  4. A simple framework for the exploration of functional biodiversity | Un cadre pour l’exploration de la biodiversité fonctionnelle
    • Year: 2023
    • Authors: Froese, R.; Coro, G.; Palomares, M.L.D.; Garilao, C.; Pauly, D.
    • Journal: Cybium
    • Article Type: Article
  5. A self-training automatic infant-cry detector
    • Year: 2023
    • Authors: Coro, G.; Bardelli, S.; Cuttano, A.; Scaramuzzo, R.T.; Ciantelli, M.
    • Journal: Neural Computing and Applications
    • Article Type: Article (Open access)

 

 

Everton Tetila | Artificial intelligence | Scientific Breakthrough Award

Assoc Prof Dr. Everton Tetila | Artificial intelligence | Scientific Breakthrough Award

professor/researcher, Universidade Federal da Grande Dourados – UFGD/FACET, Brazil

Assoc. Prof. Dr. Everton Tetila of Universidade Federal da Grande Dourados (UFGD), FACET, Brazil, stands at the forefront of artificial intelligence (AI) research, earning acclaim with the prestigious Scientific Breakthrough Award 🏆. His groundbreaking contributions to the field have propelled advancements in AI, reshaping industries and pioneering innovative solutions. With a keen focus on pushing the boundaries of technological innovation, Dr. Tetila’s work represents a fusion of academic rigor and real-world impact. As a respected professor and researcher, he continues to inspire future generations, fostering a culture of excellence and discovery in AI research.

Profile

Orcid

Academic graduation

In 2019, I obtained my PhD in Local Development from Dom Bosco Catholic University, Brazil, focusing on the innovative use of unmanned aerial vehicles and computer vision techniques for detecting and classifying soybean diseases and pests 🌱🔍. Prior to that, I completed my Master’s degree in Production Engineering at Universidade Paulista in 2007, where my research centered on software estimation processes. My academic journey began with a Bachelor’s degree in Computer Science from the State University of Mato Grosso do Sul in 2004, where I delved into bioinformatics and biological sequence analysis under the guidance of André Chastel Lima 🧬

Professional performance

In the realm of environmental sustainability and academic prowess, I’ve traversed diverse roles and responsibilities with unwavering dedication. From steering projects as a Coordinator at SEMADESC to delving into doctoral pursuits at UCDB, and nurturing minds as a Professor at UFGD, my journey embodies a mosaic of commitment and expertise. Whether it’s crafting innovative solutions in Vision Computing or delving into the depths of Database intricacies, my passion resonates across varied domains. Additionally, collaborations with esteemed institutions like UFMS and IEEE-GRSS underscore my commitment to scholarly contributions. Each engagement, be it as a Collaborator, Professor, or Reviewer, fuels my resolve to champion sustainable development and technological advancement. 🌱🎓

Publications Top Notes

  1. YOLO performance analysis for real-time detection of soybean pests
    • Authors: Tetila, Everton Castelão; Godoy da Silveira, Fábio Amaral; Da Costa, Anderson Bessa; Amorim, Willian Paraguassu; Astolfi, Gilberto; Pistori, Hemerson; Barbedo, Jayme Garcia Arnal
    • Journal: Smart Agricultural Technology
    • Year: 2024
  2. Classificação e monitoramento de áreas urbanizadas usando técnicas de visão computacional
    • Authors: Tetila, E. C.; Moraes, P. M.; Constantino, M.; Costa, R. B.; Ayres, F. M.; Reynaldo, G. O.; Colman, N. A.; Machado, F. C. A. P.; Soares, K. G.; Greco, M. M. D. M.; Pistori, H.
    • Journal: Desenvolvimento e Meio Ambiente (UFPR)
    • Year: 2023
  3. Pseudo-label Semi-supervised Learning for Soybean Monitoring
    • Authors: Menezes, Gabriel Kirsten; Astolfi, Gilberto; Martins, José Augusto Correa; Castelão Tetila, Everton; da Silva Oliveira Junior, Adair; Gonçalves, Diogo Nunes; Marcato Junior, José; Silva, Jonathan Andrade; Li, Jonathan; Gonçalves, Wesley Nunes; Pistori, Hemerson
    • Journal: Smart Agricultural Technology
    • Year: 2023
  4. System for quantitative diagnosis of COVID-19 associated Pneumonia based on Superpixels with deep learning and chest CT
    • Authors: Tetila, E. C.; Bressem, K. K.; Astolfi, G.; Sant’Ana, D. A.; Pache, M. C. B.; Wirti Junior, G.; Barbedo, J. G. A.; Pistori, H.
    • Journal: Observatorio de la Economía Latinoamericana
    • Year: 2023
  5. Desenvolvimento de uma plataforma web para sensoriamento remoto com VANT
    • Authors: Terenciani, Marcelo Figueiredo; Tetila, Everton Castelão; da Silva, Igor Donatti Gonçalves; Tetila, Juliana Queiroz da Silva; Barbedo, Jayme Garcia Arnal
    • Journal: Observatorio de la Economía Latinoamericana
    • Year: 2023
  6. Um sistema de visão computacional para reconhecimento de doenças da soja usando VANTs: resultados preliminares
    • Authors: Tetila, E. C.; Machado, B. B.; Silva, G. G.; Pistori, H.; Belete, N. A. S.; Tetila, J. Q. S.; Barbedo, J. G. A.
    • Journal: Revista Caribeña de Ciencias Sociales
    • Year: 2023
  7. An approach for applying natural language processing to image classification problems
    • Authors: Astolfi, Gilberto; Sant’Ana, Diego André; Porto, João Vitor de Andrade; Rezende, Fábio Prestes Cesar; Tetila, Everton Castelão; Matsubara, Edson Takashi; Pistori, Hemerson
    • Journal: Neurocomputing
    • Year: 2022
  8. Combining Syntactic Methods With LSTM to Classify Soybean Aerial Images
    • Authors: Astolfi, Gilberto; Pache, Marcio Carneiro Brito; Menezes, Geazy Vilharva; Oliveira Junior, Adair da Silva; Menezes, Gabriel Kirsten; Weber, Vanessa Aparecida de Moares; Castelao Tetila, Everton; Belete, Nicolas Alessandro de Souza; Matsubara, Edson Takashi; Pistori, Hemerson
    • Journal: IEEE Geoscience and Remote Sensing Letters
    • Year: 2021