Teaching

Affective Computing: CSE661/DES507

Affective Computing focuses on enabling machines with emotion recognition and adaptive interaction. It lies in the intersection of Computer Science and human Psychology. This course will overview the emotion theory, computational modelling of emotions, analysis of emotions using different modalities (such as voice, facial expressions, physiological signals etc) and related machine learning and/or signal processing techniques. We will also discuss ethical, legal and social implications of affective computing particularly in relation to Human-Machine Interaction.

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Machine Learning: CSE343

This is an introductory course on Machine Learning (ML) that is offered to undergraduate students. The contents are designed to cover both theoretical and practical aspects of several well-established ML techniques. The assignments contain theory and programming questions that help strengthen the theoretical foundations as well as learn how to engineer ML solutions to work on simulated and publicly available real datasets. The project(s) will require students to develop a complete Machine Learning solution requiring preprocessing, design of the classifier/regressor, training and validation, testing and evaluation with quantitative performance comparisons.

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Social Robotics: CSE5SR

The aim of this course is to introduce social robotics and human-robot interaction. It looks at the distinctiveness, application domains, and interaction methods of social robots. This course also discusses the challenges and opportunities that are specific to this growing field.

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