In this episode, guest Jose Unpingco sits down with TDS to discuss Data sensitivity and defects as well as defining a health data paradox. Dr. Jose Unpingco is currently the Senior Director for Data Science/Machine Learning at West Health Institute in La Jolla, a nonprofit medical research organization. Dr. Unpingco earned his Ph.D. in 1997 from the Electrical and Computer Engineering Department at the University of California, San Diego. Prior to joining West Health, Dr. Unpingco worked with the SSC Pacific High-Performance Computing Center as an on-site Director for the DoD High-Performance Computing Modernization Program (HPCMP) in the PETTT component of HPCMP where he helped develop large scale file transfer technology that is still used today, as well as encouraging the DoD to adopt open-source technology such as Python for scientific computing.In addition to his work at SSC Pacific, Dr. Unpingco has extensive industrial experience as a research engineer and technical director at Hughes Aircraft Co., Raytheon, Mission Research, and ATK, working on a wide range of systems -- underwater acoustics, adaptive antennas, radar detection, and imaging, and modern target tracking. Dr. Unpingco is the author of two internationally published books by Springer titled “Python for Signal Processing” and “Python for Probability, Statistics and Machine Learning.” In addition to his duties at West Health, Dr. Unpingco is an invited lecturer at UCSD, teaching undergraduate/graduate Data Science classes. He also sits on the industry advisory council for UCSD Extension's Data Science and Machine Learning program.
Connect with Jose on LinkedIn
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
You Might Like
