NX-465: Computational neurosciences: neuronal dynamicsIn this course we study mathematical models of neurons and neuronal networks in the context of biology and establish links to models of cognition. The focus is on brain dynamics approximated by deterministic or stochastic differential equations. ...
NX-435: Systems neuroscienceThe course "Systems Neuroscience" explores neural circuits and networks to understand how groups of neurons process information and generate behavior. It integrates techniques from neurophysiology, anatomy, genetics, and computer science to investigate com ...
EE-511: Sensors in medical instrumentationFundamental principles and methods used for physiological signal conditioning. Electrode, optical, resistive, capacitive, inductive, and piezoelectric sensor techniques used to detect and convert physiological information to electrical signals. Medical dev ...
BIO-499: Neural circuits of motivated behaviorsMotivated behaviors fulfil the basic physiological needs of animals and enable their safety. In this course, you will learn about the neuronal circuits that sense and regulate internal states, detect dangers in the environment, and organize appropriate beh ...
DH-500: Computational Social MediaThe course integrates concepts from media studies, machine learning, multimedia, and network science to characterize social practices and analyze content in platforms like Twitter/X, Instagram, YouTube, and TikTok. Students will learn computational methods ...
CS-432: Computational motor controlThe course gives (1) a review of different types of numerical models of control of locomotion and movement in animals, from fish to humans, (2) a presentation of different techniques for designing models, and (3) an analysis of the use and testing of those ...
BIO-692: Symmetry and Conservation in the CellThis course shows students how the physical principles of conservation, symmetry, and locality influence the dynamics of living organisms at the molecular and cellular level. Computer simulations are used to explore examples of cellular dynamics and phase ...
CS-602: Foundation of probabilistic proofsProbabilistic proof system (eg PCPs and IPs) have had a tremendous impact on the theoretical computer science, and have also found practical uses. They underlie delegation of computation protocols and hardness of approximation. This course covers the found ...
CS-434: Unsupervised & reinforcement learning in neural networksLearning is observable in animal and human behavior, but learning is also a topic of computer science. This course links algorithms from machine learning with biological phenomena of synaptic plasticity. The course covers unsupervised and reinforcement le ...
