Affective Computing Course | Emotion AI | NPTEL | Prof. Jainendra Shukla | Prof. Abhinav Dhall
Course Details
| Exam Registration | 5007 |
|---|---|
| Course Status | Ongoing |
| Course Type | Elective |
| Language | English |
| Duration | 12 weeks |
| Categories | Computer Science and Engineering, Artificial Intelligence |
| Credit Points | 3 |
| Level | Undergraduate/Postgraduate |
| Start Date | 19 Jan 2026 |
| End Date | 10 Apr 2026 |
| Enrollment Ends | 02 Feb 2026 |
| Exam Registration Ends | 20 Feb 2026 |
| Exam Date | 17 Apr 2026 IST |
| NCrF Level | 4.5 — 8.0 |
Affective Computing: Bridging the Gap Between Humans and Machines
In an era where technology is increasingly intertwined with daily life, the next frontier is not just intelligent machines, but emotionally intelligent ones. Affective Computing, often termed Emotion AI, is the revolutionary field dedicated to enabling machines to recognize, interpret, process, and simulate human emotions. This interdisciplinary domain sits at the confluence of Computer Science, Human Psychology, and Design, aiming to create more natural, empathetic, and adaptive interactions between humans and technology.
A comprehensive understanding of this field is now accessible through a meticulously designed 12-week course offered by leading Indian institutes. This course provides a deep dive into the theories, technologies, and ethical frameworks that underpin the future of human-machine collaboration.
Meet Your Distinguished Instructors
The course is led by two eminent researchers and academics at the forefront of Affective Computing and AI research in India.
Prof. Jainendra Shukla (IIIT Delhi)
Prof. Shukla is the founder and director of the Human-Machine Interaction research group and an Assistant Professor jointly affiliated with the Department of Computer Science and Engineering and the Department of Human-Centered Design at IIIT-Delhi. He heads the Centre for Design and New Media and is associated with the Infosys Centre for Artificial Intelligence. His research passionately explores how social robots and machines with adaptive interaction capabilities can enhance quality of life, particularly in health and social care.
His work is published in top-tier forums like CHI, IMWUT, and IEEE Transactions on Affective Computing. A recipient of numerous accolades including the SERB-DST startup research grant, the IIIT-Delhi research excellence award, and the prestigious Industrial Doctorate grant by the Government of Spain, Prof. Shukla holds a Ph.D. from Universitat Rovira I Virgili, Spain. He is an active member of both ACM and IEEE.
Prof. Abhinav Dhall (IIT Ropar)
Prof. Abhinav Dhall is an Assistant Professor of Computer Science & Engineering and the Head of the Centre for Applied Research in Data Science at IIT Ropar. He also holds adjunct positions at Monash University and IIIT-Delhi. With a Ph.D. from the Australian National University and postdoctoral experience at the University of Waterloo and University of Canberra, his expertise lies at the intersection of computer vision and affective computing. Prof. Dhall contributes to the field as an Associate Editor for the IEEE Transactions on Affective Computing, ensuring the course content is aligned with the latest academic and industry standards.
Course Overview: What You Will Learn
This undergraduate/postgraduate level course is structured to provide a holistic view of Affective Computing, from foundational theories to advanced applications and critical ethical considerations.
ABOUT THE COURSE: The curriculum focuses on empowering machines with emotion recognition and adaptive interaction abilities. It covers emotion theory, computational modeling, and the analysis of emotions using various modalities like voice, facial expressions, text, and physiological signals. The course also delves into the associated machine learning and signal processing techniques, concluding with a crucial discussion on the ethical, legal, and social implications (ELSI) of this technology.
Detailed 12-Week Course Layout
| Week | Topic |
|---|---|
| Week 1 | Fundamentals of Affective Computing |
| Week 2 | Emotion Theory and Emotional Design |
| Week 3 | Experimental Design: Affect Elicitation; R&D Tools |
| Week 4 | Emotions in Facial Expressions |
| Week 5 | Emotions in Voice |
| Week 6 | Emotions in Text |
| Week 7 | Emotions in Physiological Signals |
| Week 8 | Multimodal Emotion Recognition |
| Week 9 | Emotional Empathy in Agents/Machines/Robots |
| Week 10 | Online and Adaptive Recognition: Challenges & Opportunities |
| Week 11 | Case Study (Updated periodically) |
| Week 12 | Ethical, Legal and Social Implications (ELSI) |
Who Should Enroll and Prerequisites
INTENDED AUDIENCE: Senior Undergraduate and Postgraduate students.
PREREQUISITES:
- Mandatory: Programming, Artificial Intelligence, Machine Learning.
- Desirable: Human-Computer Interaction, Deep Learning, Natural Language Processing (NLP), Computer Vision (CV).
The course builds upon fundamental concepts, making it ideal for students looking to specialize in the cutting-edge applications of AI.
Industry Relevance and Support
The skills acquired in this course are highly sought after in the tech industry. Any company working with AI/ML will recognize the value of this specialization. Leading organizations at the forefront of AI research and development, such as those below, are actively investing in affective computing technologies:
- Amazon
- Apple
- Meta
- Microsoft
Recommended Reading & Resources
To complement the course material, instructors recommend several authoritative texts:
- Affective Computing by Rosalind Picard (MIT Press).
- The Oxford Handbook of Affective Computing (Oxford University Press).
- The Encyclopedia of Human-Computer Interaction, 2nd Ed.
- Interaction Design: Beyond Human-Computer Interaction (5th Ed.) by Preece, Sharp, & Rogers.
This course represents a unique opportunity to learn from pioneering researchers and gain expertise in one of the most human-centric branches of artificial intelligence. Whether you aim to build empathetic chatbots, develop healthcare robots, or create adaptive learning systems, mastering affective computing is your gateway to shaping the future of human-machine interaction.
Enroll Now →