Adenilton José da Silva

Computer Science

Mathematician Adenilton Silva applies his research to the field of computing. He holds a master’s and Ph.D. in computer science from the University of Pernambuco and is committed to exploring how quantum computers can learn from society-generated data. Machine learning, a process where computers acquire new information from raw data, is a key area of his research. His work in quantum processing is crucial to areas beyond the reach of classical processing capacity. For instance, he is involved in studies that utilize quantum computing to develop artificial neural networks, another area that has piqued his interest.

His work pushes the boundaries of computing. Despite the challenges, Adenilton is investigating whether quantum computers can learn more efficiently or faster than current computers. Outside his teaching and research commitments, Adenilton enjoys hiking and immersing himself in nature.

Lattes

Open Calls

Science Call 1

Projects

Quantum Machine Learning: Learning models and algorithms
Science / Computer Science

Machine learning, a branch of computer science, is characterized by algorithms that can ‘learn’ from data. With the vast amount of information being stored daily, it has facilitated the development of applications across a wide range of fields, including disease diagnosis and voice recognition, among others. While the potential of machine learning is often highlighted, this project aims to focus on the limitations of the field and the challenges that a computer cannot currently overcome. By employing a novel computing model, quantum computing, we aim to explore the creation of more efficient algorithms. These enhanced algorithms would not only have improved learning capabilities but also the potential to solve problems currently deemed intractable.

Amount invested

Grant Serrapilheira: R$ 98.200,00
  • Topics
  • Algorithm
  • artificial inteligence
  • Machine learning
  • Quantum computing