Teaching

Introduction to Brain-Computer Interfacing (Fall 2016)

This course introduces the growing field of Brain-Computer Interfaces (BCI) from neuroscience and machine learning perspectives. It covers various topics including basic, building BCI, major types of BCIs, applications, and ethics.

Introduction to Neural and Cognitive Modeling CSE 486 (Spring 2016) 

This is an introductory course on computational models used in Neuroscience and Cognitive Science. The emphasis is on multiple scales (three levels) of modeling – Single Neuron-level, Network-level and Abstract (Connectionist and Bayesian) models. The course emphasizes the need for and role of theory and computation in Neuroscience and Cognitive Science. Within this course, we also explore Network Neuroscience which is a buzz word around the Cognitive Neuroscience community in the past few years which covers resting-state modeling using dynamical systems, Linear discriminant models, different connectivity schemes to quantify neural population activity in a given brain area, Hemodynamic modeling commonly encountered in the neuroimaging measurements. State-of-the-art methods are discussed.

Research methodology CSE 991 (Monsoon 2015)

This is a course on research methodology specifically focusing on behavioral research, experimental design, data acquisition, data validity and analysis of data using scientific methods, statistical interpretations and writing research reports. Following a brief overview, the course will broadly aim to cover key aspects in employed research methods from a scientific point of view.

Introduction to Neural and Cognitive Modeling CSE 486 (Spring 2015) 

Introduction to cognitive science (spring 2015)

The course will examine how modern cognitive neuroscientists explore the neural underpinnings of sensory information – vision, sound, touch leading to Visual/Auditory, Language, memory, emotion, and higher-order cognitive processes.