Understanding and predicting human behavior in dynamic, multisensory environments is one of the central challenges in neuroergonomics and human-centered artificial intelligence. Computational neuroscience provides mechanistic theories of perception, attention, and decision-making, but these insights have not yet been f...
T. A. Chowdhury, Alexander L. Francis, Daniel J. Strauss· Frontiers in Neuroergonomics· 0 citations
The debate about the future of artificial intelligence (AI) runs along a single axis: cognitive capability and its projected culmination in superintelligence. We argue that this framing leaves a complementary axis unexamined and propose the goal of
Super-Emotional Intelligence
(SEI): systems that perceive, model, r...
Sophie Bonnaire, F. I. Corona-Strauss, Daniel J. Strauss· Frontiers in Artificial Inte...· 0 citations
Human–robot collaboration in industrial and semi-structured environments imposes significant attentional demands on the human operator, particularly during complex or time-sensitive tasks. While these collaborative robots are designed to assist the human operator, they can also introduce attentional fragmentation for h...
T. A. Chowdhury, Jose A. Trapero, F. I. Corona-Strauss et al.· Companion Publication of the...· 0 citations
Previous works that have analyzed electroencephalographic (EEG) speech envelope encoding in hearing-aid users using stimulus reconstruction (SR) approaches have shown that noise reduction (NR) algorithms can improve the neural tracking of speech in noise. Beyond enhancing speech envelope encoding, NR may also restore t...
Adrian Mai, Tanja Biehl, M. Latzel et al.· Trends in Hearing· 0 citations
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