Jaspreet Sahota started his research career in theoretical physics, studying the quantum mechanical properties of light-matter interactions that enable next generation technologies: e.g. gravitational wave detection, quantum metrology, and quantum lithography. During his PhD at the University of Toronto, he showed that quantum-enhanced optical interferometry is enabled by particle entanglement as opposed to mode entanglement, thus correcting an erroneous long-held belief in the field.
Jaspreet transitioned to working in AI by building and implementing machine learning solutions for businesses through a start-up that he co-founded. He joined Borealis AI as a researcher where he is currently building cutting-edge machine learning solutions for various RBC businesses. He has worked on enhancing deep learning architectures for time series analysis and making supervised learning more robust to realistic label noise. In his pastime, Jaspreet enjoys working on quantum machine learning, playing competitive basketball, and spending quality time with his daughter.
Bias in Machine Learning
Time Series Analysis