EDEE - Electrical Engineering

This course introduces students to broad research directions in electrical and microengineering through a series of weekly, wide-audience seminars by invited distinguished speakers. The students practice transferable skills, including active listening, critical thinking, and scientific communication.

The Deep Learning for NLP course covers advanced topics in deep learning architectures for natural language processing.  The focus is on attention-based architectures (like Transformers), structure processing and variational-Bayesian approaches, and why these models are particularly suited to the properties of human language, such as categorical, unbounded, and structured representations.

This course describes theory and methods for decision making under uncertainty under partial feedback.

Block on course on optimal control. Taught by Prof. Timm Faulwasser & Dr. Yuning Jiang