Abu Bakar Siddique | Artificial Intelligence | Best Researcher Award

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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.

Souhail Dhouib | Artificial Intelligence | Best Researcher Award

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Prof Dr. Souhail Dhouib | Artificial Intelligence | Best Researcher Award

Full Professor, Higher Institute of Industrial Management, University of Sfax, Tunisia

 

Prof. Souhail Dhouib, a Tunisian national born on June 18, 1972, is a distinguished figure in the realms of Artificial Intelligence and Operations Research. With over two decades of experience in academia and industry, he stands as a pioneering figure in decision making and planning methodologies, notably recognized for inventing the Dhouib-Matrix optimization concept.

Profile

Orcid

Education 🎓

Prof. Dhouib pursued his academic journey at the Faculty of Management and Economics Sciences, Sfax University, Tunisia, where he earned his Ph.D. in Quantitative Methods, his Master’s degree in Operations Research and Production Management, and his Bachelor’s degree in Management Information Systems.

Experience 💼

With a rich blend of academic prowess and practical acumen, Prof. Dhouib has served in various capacities. From being a General Manager to founding companies specializing in business software development, his expertise spans across industries. Moreover, his proficiency extends to consultancy for businesses and industries, shaping his role as a seasoned Operations Research Analyst.

Research Interests 🔍

Prof. Dhouib’s research interests revolve around Artificial Intelligence, Operations research, Optimization algorithms, Logistic, Supply Chain Management, Business Intelligence Systems, and Enterprise Resource Planning (ERP). His innovative approaches have garnered recognition in academia and industry alike.

Awards 🏆

Prof. Dhouib’s contributions have been acknowledged through numerous awards and accolades, symbolizing his impact and influence in the field of decision making and planning methodologies.

Publications Top Notes📚

Intelligent Path Planning for Cognitive Mobile Robot Based on DhouibMatrix-SPP Method – Cognitive Robotics, 2024.

Multi-Start Constructive Heuristic through Descriptive Statistical Metrics: The Dhouib-Matrix-4 Metaheuristic – International Journal of Operational Research, 2024.

Innovative Method to Solve the Minimum Spanning Tree Problem: The Dhouib-Matrix-MSTP (DM-MSTP) – Results in Control and Optimization, 2024.

Enhancing the Dhouib-Matrix-4 Metaheuristic to Generate the Pareto Non-Dominated Set Solutions for Multi-objective Travelling Salesman Problem: The DM4-PMO Method – Results in Control and Optimization, 2024.

Faster than Dijkstra and A* Methods for the Mobile Robot Path Planning Problem Using Four Movement Directions: The Dhouib-Matrix-SPP-4 – Advances in Transdisciplinary Engineering, Mechatronics and Automation Technology, 2024.

Gyuho Choi | Artificial Intelligence | Best Researcher Award

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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.

Profile

Google Scholar

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

Everton Tetila | Artificial intelligence | Scientific Breakthrough Award

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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