EDEE - Electrical Engineering

EE-629 Network Neuroscience: Methods & Applications

EE-625(b) Research seminars in Electrical and Micro Engineering - SPRING

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.

EE-625(a) Research seminars in Electrical and Micro Engineering - FALL

EE-626 Graph representations for biology and medicine

EE-600 Usability engineering

EE-608 Deep Learning For Natural Language Processing

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.

EE-618 Theory and Methods for Reinforcement Learning

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

EE-736 Optimal Control for Dynamic Systems

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

EE-726 Sparse stochastic processes

EE-805 Fundamentals of Image Analysis

Summary

This summer school is an hands-on introduction on the fundamentals of image analysis for scientists. A series of lectures provide students with the key concepts in the field, and are followed by practical sessions with popular software on the participants' own image-analysis software.