Alex Gaudio's research focuses on explainable machine learning for analysis of medical images and signals. His research focuses on explanations of bias and predictions in context of privacy, compression, and prediction. He is a dual degree PhD candidate at Carnegie Mellon University and at the University of Porto. He co-founded a non-profit, NYC Makerspace, to instill in regular people from diverse and disadvantaged backgrounds, that they can innovate with advanced technology and become community leaders. Previously, he worked as a data scientist and engineer in New York City for 7 years. He studied in jazz performance and composition at Bard College, during which he briefly worked as an Emergency Medical Technician in ambulances and in a hospital.
Advice to myself and to my friends and colleagues: The way people create and interpret their life paths is fascinating. Visionary people embrace challenge by inventing opportunities and pursuing ideas. Their success is achieved not by meeting requirements or emphasizing credentials, but by giving others the ability to appreciate, use and adapt the things they love most. Think big, then go a lot bigger, and find clever ways to make it happen. People will follow and support you when they can see, understand, and believe in what you are doing. Just do it!
Ph.D. Candidate in Electrical Computer Engineering (expected 2023)
Advisors: Prof. Asim Smailagic, Prof. Aurelio Campilho
Ph.D. Candidate in Electrical Computer Engineering (expected 2023)
(via CMU Portugal dual PhD degree program)
M.S. in Electrical Computer Engineering (expected 2021)
Bachelor of Arts in Music, 2010
I am interested in collaborations of many kinds and with people of a wide variety of different experiences and skill-sets. I'm especially focused on academic collaboration. I am also usually looking for students to help with research projects. I am also interested in industry collaborations related to digital stethoscopes.
Email: click@to.reveal.com