This inventor holds 3 USPTO granted patents and 1 published patent application, plus 3 CIPO patents. Top assignees: University of Toronto, Nervex Neurotechnologies, Inc.. Active years: 2021-2026.
Company Filing History:
Years Active: 2021-2026
Title: Innovations of Gerard O'Leary
Introduction
Gerard O'Leary is a notable inventor based in Toronto, Canada. He has made significant contributions to the field of neural signal analysis and machine learning. With a total of 3 patents, O'Leary's work focuses on advanced methodologies for analyzing neural data and classifying time series data.
Latest Patents
O'Leary's latest patents include a "System, system architecture, and method for neural cross-frequency coupling analysis." This invention provides a comprehensive method for analyzing neural signals by extracting phase frequency signals and amplitude frequency envelope signals. The method determines a measure of cross-frequency coupling, which is crucial for understanding neural interactions.
Another significant patent is the "System and method for classifying time series data for state identification." This invention involves training a machine learning model to classify occurrences of specific states within time series data. The method utilizes a classified feature vector to determine whether a current sample represents an occurrence of the state, enhancing the accuracy of state identification.
Career Highlights
Gerard O'Leary is affiliated with the University of Toronto, where he conducts research and develops innovative solutions in his field. His work has garnered attention for its practical applications in neuroscience and data analysis.
Collaborations
O'Leary collaborates with Roman Genov, contributing to advancements in their shared research interests. Their partnership exemplifies the importance of teamwork in driving innovation.
Conclusion
Gerard O'Leary's contributions to neural signal analysis and machine learning demonstrate his commitment to advancing technology in these fields. His patents reflect a deep understanding of complex systems and their applications.