Teaching
I am teaching two courses this semester. If you have any specific questions about course topics, feel free to write me, and I will respond as soon as possible.
Semester: 202351
This course introduces the mathematical and empirical foundations on which machine learning techniques are based to generate intelligent behaviors in engineering tasks. At the end of the course, students should be able to:
Utilize the different machine learning algorithms in classification, regression and generative tasks.
Adopt supervised, unsupervised and reinforced learning schemes according to the needs of the diverse applications.
Understand the advantages and disadvantages of the various deep learning strategies and their possible use in telecommunications.
Propose development projects that benefit from the use of machine learning techniques.
Semester: 202410
This course analyzes and contrasts the main knowledge representation methods and inference mechanisms, in order to implement and evaluate both classical and modern techniques for solving real-world problems. At the end of this course, students should be able to:
Understand the main methods for knowledge representation and inference mechanisms.
Apply and evaluate artificial intelligence techniques for solving real-world problems.
Develop and conduct appropriate experiments, analyze and interpret data, and use engineering judgment to draw conclusions.
Propose research and entrepreneurship projects that take advantage of the use of artificial intelligence.