Summary
Kiret Dhindsa is a postdoctoral researcher in Berlin with 11 years of experience at the intersection of human and machine intelligence, specializing in brain-computer interfacing, neurofeedback, and machine learning for medical applications. With a PhD from McMaster in BCI and ML and an undergraduate double major in Psychology and Mathematical Statistics, he blends rigorous quantitative methods with cognitive science to design adaptive neurotechnologies. His work spans academia and applied research—recently at Charité and previously at McMaster and the Vector Institute—bringing HPC-aware approaches to real-world clinical and educational problems. Known for multidisciplinary collaboration, he pairs deep statistical and deep learning expertise with hands-on experimentation in human-in-the-loop systems. An underappreciated strength is his ability to translate psychological theory into practical ML features that improve interaction between people and algorithms.
11 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy (Ph.D.), Brain-Computer Interfacing and Machine Learning, Doctor of Philosophy (Ph.D.), Brain-Computer Interfacing and Machine Learning at McMaster University
Honors Double Major, Bachelor of Science, Psychology and Mathematical Statistics, Honors Double Major, Bachelor of Science, Psychology and Mathematical Statistics at York University