Newtonville, MA, United States of America

Thomas Francis Quatieri, Jr

USPTO Granted Patents = 7 



Average Co-Inventor Count = 6.6

ph-index = 2

Forward Citations = 16(Granted Patents)


Company Filing History:


Years Active: 2016-2023

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7 patents (USPTO):Explore Patents

Title: Innovations of Thomas Francis Quatieri, Jr.

Introduction

Thomas Francis Quatieri, Jr. is a notable inventor based in Newtonville, MA (US). He has made significant contributions to the field of auditory attention decoding and speech dynamics. With a total of 7 patents, Quatieri's work has advanced our understanding of how auditory signals can be processed and analyzed.

Latest Patents

One of his latest patents is titled "End-to-end deep neural network for auditory attention decoding." This method involves receiving neural data that reflects a listener's auditory attention and an acoustic signal from multiple sources. The process includes generating audio data from the acoustic signal, combining it with neural data, and using a classification network to calculate similarity scores. These scores help identify which acoustic source is associated with the listener's attention. Another significant patent is "Using correlation structure of speech dynamics to detect neurological changes." This method assesses conditions such as Major Depressive Disorder (MDD) by measuring speech-related variables and analyzing their correlation structure to generate an assessment of the subject's condition.

Career Highlights

Quariteri is affiliated with the Massachusetts Institute of Technology, where he continues to innovate and contribute to research in auditory processing and speech analysis. His work has implications for both clinical assessments and advancements in artificial intelligence.

Collaborations

Some of his notable coworkers include Christopher J. Smalt and Nicolas Malyska, who have collaborated with him on various projects related to auditory attention and speech dynamics.

Conclusion

Thomas Francis Quatieri, Jr. is a pioneering inventor whose work in auditory attention decoding and speech dynamics has the potential to impact both technology and healthcare. His contributions continue to shape the future of auditory processing research.

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