Celso M. de Melo

Computer Scientist
Associate Editor, IEEE Transactions on Affective Computing
Associate Editor, Frontiers in Psychology
Contact: celso.miguel.de.melo@gmail.com
Scholar | LinkedIn | @Celso_M_de_Melo

Trends in Cognitive Sciences
1. Next-generation deep learning based on simulators and synthetic data
Deep learning models learn in a most artificial way: they require large quantities of labeled data to grasp even simple concepts. We highlight a solution to this challenge: synthetic data. Synthetic data are becoming accessible due to progress in rendering and generative pipelines. Paradoxically, this artificial solution will enable more natural learning, as seen in biological systems. Read the paper.
Proceedings of the National Academy of Sciences U.S.A.
2. Human cooperation when acting through autonomous machines
Autonomous machines that act on our behalf are bound to face situations where individual interest conflicts with collective interest, and we must understand if people will cooperate when acting through them. We show, in the increasingly popular domain of autonomous vehicles, that people program machines to cooperate more than they would when acting directly with others. Read the paper.
Scientific Reports
3. Joint Effect of Emotion Expressions and Strategy on Cooperation
The research provides novel insight into the combined effects of strategy and emotion expressions on cooperation. The research has important practical application for the design of autonomous systems, suggesting that a proper combination of action and emotion displays can maximize cooperation from humans. Read the paper.
Frontiers in Robotics and AI
4. Risk of Injury Shapes Choices in Moral Dilemmas with AVs
Our shows that moral choices are shaped by risk of injury for involved parties in dilemmas involving autonomous machines. Read the paper.
Journal of Personality and Social Psychology
5. Reading People's Minds From Emotion Expressions
Emotion expressions can be windows into other people's minds. This research shows that people make inferences about how others are appraising the ongoing interaction from emotion expressions and, from this information, about others' beliefs, desires, and intentions. Read the paper.
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I am interested in creating machines that show the kind of intelligence we see in humans, with a particular focus on embodied intelligence. My research and applied work has focused on (a) synthetic data for AI/ML, (b) simulators to enable the next generation of deep learning (e.g., embodied learning), (c) human behavior with autonomous machines (e.g., human-machine cooperation), (b) AI models for complex human behavior (e.g., emotion), (c) multimodal expression in machines through face, voice, and body; and, (d) new media that push the boundaries for human-machine interaction (e.g., augmented/virtual reality).

I am a computer scientist with a research focus on artificial intelligence and human-machine interaction.

I finished a postdoc at the USC Marshall School of Business. I earned my Ph.D. in Computer Science at the University of Southern California. This work consisted of creating cognitive computational models of emotion and decision making using various artificial intelligence techniques (e.g., machine learning). This work was done at the Institute for Creative Technologies with Jonathan Gratch.I received a M.Sc. in Computer Science at the Technical University of Lisbon (IST) with Ana Paiva at the Synthetic Characters and Intelligent Agents Group (GAIPS).

I was born in beautiful Mozambique and also am proud to be Portuguese.

Last updated: February 20, 2023