Technical PhD Seminar Series
Machine Learning and EnGINEERING APPLICATIONS
Spring SEMESTER 2018
Machine Learning together with data streams offer a new and universal way of looking at the world phenomena, which is radically different than classical disciplinary and theory based approaches. Opposite to theory driven approaches, machine learning, which is a relatively new field of research inverts the process of scientific modeling. By asking a proper question and having a lot of observations around that question, machine learning promises to learn good answers from the provided data sets. Therefore, the trained models have a larger capacity to deal with unique and complex problems that have no a priori descriptive theories.
However, while new machine learning algorithms such as deep learning have created a new wave of applications in computer vision and natural language translation, there are a lot of complex engineering applications, yet to be investigated.
Therefore, while during the last semesters our main focus has been mainly on machine learning techniques and concepts, this semester we focus at the intersection of several specific applications and machine learning techniques.
Expectations From The Participants
Everybody is welcome to attend to (any-all of) the lectures. But those who register for this course are highly encouraged to actively participate in the discussions and bring their own problems/projects that can be approached by machine learning.
Also, all the participants are highly encouraged to check the presentations of the last semesters:
Dates: Tuesdays 14:00-15:30
Introduction: Tuesday, February 20, 2018
Place: Chair for CAAD, D-ARCH/ITA/CAAD HIB E16
Course tutor: Vahid Moosavi