Doctor, Gaziantep Islam Science and Technology University, Faculty of Engineering and Natural Sciences, Department of Industrial Engineering, 27010 Gaziantep, Turkey

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Strengths for the Award

Dr. Yusuf Karadede’s research in stochastic processes, heuristic algorithms, and stochastic optimization underscores his deep expertise and innovative approach in industrial engineering. His doctoral thesis and subsequent work have made significant contributions to the fields of simulation and stochastic modeling. Notably, his publications in esteemed journals like Soft Computing and Energy highlight his ability to tackle complex problems with advanced computational techniques.

Dr. Karadede’s diverse range of scientific activities demonstrates his commitment to advancing both theoretical and applied aspects of his field. His development of novel models such as the ProFiVaS model for financial indicators, showcased in his recent publication in Expert Systems with Applications, exemplifies his forward-thinking approach and impact on financial modeling.

Areas for Improvement

While Dr. Karadede’s research is highly impactful, expanding the scope of his research to include interdisciplinary approaches could further enhance the applicability of his work. For instance, integrating his stochastic models with emerging technologies like machine learning could offer new insights and broaden the impact of his research. Additionally, increasing collaboration with international research groups might provide new perspectives and enhance the global reach of his contributions.

Academic Background:

Bachelor’s Degree: Mathematics, Suleyman Demirel University, 2006-2010
Master’s Degree: Industrial Engineering, Suleyman Demirel University, 2011-2014
Doctorate (Ph.D.): Industrial Engineering, Suleyman Demirel University, 2015-2020

Professional Experience:

Kafkas University: Faculty of Engineering and Architecture, Department of Industrial Engineering (2014-2015)
Suleyman Demirel University: Faculty of Engineering, Department of Industrial Engineering (2015-2020)
Gaziantep Islam Science and Technology University: Department of Industrial Engineering (2020-Present)

Research Interests:

Stochastic Processes and Models
Simulation
Heuristic Algorithms
Stochastic Optimization

Awards and Scholarships:

TÜBİTAK 2210-C Program Scholarship (2013-2014)
TÜBİTAK 2211-C Program Scholarship (2018-2020)

Publications Top Notes:

Karadede, Y., Özdemir, G. (2018). A hierarchical soft computing model for parameter estimation of curve-fitting problems. Soft Computing, 22(20), 6937-6964.

Karadede, Y., Ozdemir, G., Aydemir, E. (2017). Breeder Hybrid Algorithm Approach for Natural Gas Demand Forecasting Model. Energy, 141, 1269-1284.

Akdeniz, F., Biçil, M., Karadede, Y., Özbek, F. E., Özdemir, G. (2018). Application of real valued genetic algorithm on prediction of higher heating values of various lignocellulosic materials. Energy, 160, 1047-1054.

Karadede, Y. (2024). A novel stochastic ProFiVaS model based on decomposition of stochastic Vasicek differential equation for modeling and simulating financial indicators. Expert Systems with Applications

Conclusion

Dr. Yusuf Karadede’s distinguished research in stochastic processes and optimization positions him as a strong candidate for the Best Researcher Award. His innovative contributions, including high-impact publications and successful research projects funded by prestigious institutions like TÜBİTAK, highlight his significant achievements and potential for future breakthroughs. His work not only advances theoretical understanding but also offers practical solutions to real-world problems, making him a deserving nominee for this esteemed accolade.

Abu Bakar Siddique | Artificial Intelligence | Best Researcher Award

Posted on 24/06/202424/06/2024 by ScienceFatherLeave a Comment

Mr. Abu Bakar Siddique | Artificial Intelligence | Best Researcher Award

MS Scholar, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Pakistan

Abu Bakar Siddique, a Pakistani national born on 03/07/1997, is currently pursuing his Master’s degree in Computer Engineering at Ghulam Ishaq Khan Institute of Engineering Sciences and Technology (GIKI). He holds a BS degree in Computer Software Engineering from the University of Engineering and Technology, Peshawar. Abu Bakar specializes in Machine/Deep Learning and Quantum Computing, with a research focus on Quantum Machine Learning.

Education 🎓

Abu Bakar completed his BS in Computer Software Engineering from UET Peshawar and is currently in his fourth semester of MS in Computer Engineering at GIKI. His coursework spans advanced topics in AI, Quantum Computing, and Neural Networks.

Experience 💼

As a Graduate Research Assistant at GIKI, Abu Bakar contributes to both academic courses and research projects. He has also freelanced on Fiverr, specializing in programming and machine learning solutions.

Research Interests 🧠

Abu Bakar’s research interests include Quantum Machine Learning, Deep Learning, and Computer Vision, exploring applications of quantum computing in enhancing machine learning algorithms.

Awards 🏆

Abu Bakar has received the Dean’s Honor Roll and multiple High Distinction Awards for his academic achievements at GIKI. He also earned a Speaker Award at the International Symposium on AI and Quantum Computing.

Profile

Abu Bakar Siddique on scopus

Publications

“Prediction of Magnetic Nature of Oxide Composition by using Machine Learning Models” – 2024, Journal of Materials Science.

“Performance Evaluation of Popular Deep Neural Networks for Neural Machine Translation” – 2023, IEEE Transactions on Neural Networks.

“Detecting Cyberbullying using Machine Learning Approaches” – 2023, ACM Transactions on Cyberbullying.

“Studying the effects of feature selection approaches on machine learning techniques for Mushroom classification problem” – 2023, Journal of Machine Learning Research.

Gyuho Choi | Artificial Intelligence | Best Researcher Award

Posted on 18/05/202418/05/2024 by ScienceFatherLeave a Comment

Prof Dr. Gyuho Choi | Artificial Intelligence | Best Researcher Award

Assistant Professor, Chosun University, South Korea

Gyuho Choi is an accomplished researcher and academic specializing in artificial intelligence and biometrics. He has held various prestigious positions in renowned Korean universities, contributing significantly to the fields of AI and computer engineering. His dedication and innovative work have garnered him multiple accolades and a strong reputation in the scientific community.

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Education 🎓

Gyuho Choi’s educational journey began with a Bachelor’s degree in Electronics Engineering from Chosun University (2008-2015). He continued at the same institution for an integrated M.S.-Ph.D. program in Control and Instrumentation Engineering, which he completed in February 2021. His academic path further included post-doctoral research at Chosun University and research professor positions at Yonsei University and Gachon University. Since March 2023, he has been serving as an Assistant Professor in the Department of Artificial Intelligence Engineering at Chosun University.

Experience 💼

Gyuho Choi has extensive experience in academia and research. He began as a post-doctoral researcher at Chosun University’s IT Research Institute (2021-2022) and then served as a Research Professor at Yonsei University’s Barun ICT Research Center (2022) and Gachon University’s Department of Computer Engineering (2022-2023). Currently, he is an Assistant Professor at Chosun University, where he continues to explore advanced topics in artificial intelligence and biometrics.

Research Interests 🔬

Gyuho Choi’s research interests lie at the intersection of artificial intelligence, biometrics, and signal processing. He focuses on developing advanced user identification systems using biometric signals such as ECG and EMG, contributing to the fields of intelligent vehicles and secure authentication systems.

Awards 🏆

Gyuho Choi’s innovative research has been recognized with several prestigious awards. He received the Best Paper Award at the Korea Multimedia Society Spring Conference in 2016 and the Korean Institute of Smart Media Spring Conference in 2018. Additionally, he was honored with the Best Researcher Award at the 7th Edition of Global Research Awards on Artificial Intelligence and Robotics in May 2023.

Publications Top Notes 📚

Refereed Journal Papers (SCI / SCIE Indexed)

Choi, G. H., et al. (2019). User authentication system based on baseline-corrected ECG for biometrics. Intelligent Automation and Soft Computing, 25(1), 193-204. Link – Cited by: 12 articles

Choi, G. H., et al. (2019). User identification system using 2D resized spectrogram features of ECG. IEEE Access, 7, 34862-34873. Link – Cited by: 15 articles

Choi, G. H., et al. (2020). ECG-based human identification system by temporal-amplitude combined feature vectors. IEEE Access, 8, 42217-42230. Link – Cited by: 8 articles

Choi, G. H., et al. (2020). Recognition system using fusion normalization based on morphological features of post-exercise ECG for intelligent biometrics. Sensors, 20(24), 1-16. Link – Cited by: 5 articles

Choi, G. H., et al. (2020). Driver identification system using normalized electrocardiogram based on adaptive threshold filter for intelligent vehicles. Sensors, 21(1), 1-17. Link – Cited by: 7 articles

Choi, G. H., et al. (2022). Identification system based on resolution adjusted 2D spectrogram of driver’s ECG for intelligent vehicles. Mobile Information Systems, 2022, 1-13. Link – Cited by: 4 articles

Xiaodan Shi | Deep Learning | Best Researcher Award

Posted on 25/04/202425/04/2024 by ScienceFatherLeave a Comment

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. 🌟

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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

Everton Tetila | Artificial intelligence | Scientific Breakthrough Award

Posted on 20/02/202420/02/2024 by ScienceFatherLeave a Comment

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.

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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

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
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
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
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
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
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
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
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