Abu Bakar Siddique | Artificial Intelligence | Best Researcher Award

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.

Francisco Javier BECERRA SANCHEZ | Artifical Intelligence | Science Visionary Award

Mr. Francisco Javier BECERRA SANCHEZ | Artifical Intelligence | Science Visionary Award

Doctoral Researcher, University of Luxembourg, Luxembourg

Mr. Francisco Javier BECERRA SANCHEZ, a dedicated doctoral researcher at the University of Luxembourg, has been honored with the prestigious Artifical Intelligence Science Visionary Award 🏆. His groundbreaking work in the realm of artificial intelligence has captivated the scientific community, pushing the boundaries of innovation and exploration. With unwavering dedication and unparalleled vision, Mr. BECERRA SANCHEZ is paving the way for the future of AI research. His contributions are not only shaping the present landscape but also promising transformative advancements that will redefine the way we perceive and utilize artificial intelligence technology.

Profile

Scopus

Education 🎓

Francisco Javier BECERRA SANCHEZ pursued his academic journey with dedication and excellence. He obtained his Bachelor of Engineering in Computer Sciences from Instituto Tecnológico de Ciudad Guzmán – TecNM, followed by a Master’s degree in the same field. Currently, he is pursuing a PhD in Computer Sciences, specializing in Computer Systems Networking and Telecommunications at the University of Luxembourg.

Experience 💼

Throughout his career, Francisco showcased versatility and proficiency. He served as a Full-stack Developer at JECOR SA DE CV, contributing significantly to front-end development and database management. As a Freelance Web Developer, he honed his skills in web application development and digital marketing, providing innovative solutions to clients worldwide. Presently, as a Doctoral Researcher at the University of Luxembourg, he delves into cutting-edge AI techniques for audio signal processing in agriculture.

Research Interests 🧠

Francisco’s research interests converge on the intersection of artificial intelligence and agricultural technology. With a focus on audio signal processing, he explores the application of RNA, MP, SVM, KNN, and other AI techniques to revolutionize farming practices. His work aims to optimize crop management, enhance yield prediction, and contribute to sustainable agriculture practices, thereby addressing global food security challenges.

Publications 📚

  • Title: “Development of non-destructive system for estimating avocado quality parameters” Year: 2024

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