Our Digital Life Podcast: A series by IEEE-SPS
As the world's largest professional organization, IEEE plays a significant role in enhancing the quality of our lives. Specifically, the IEEE signal processing society or SPS focuses on research and development of audio and speech processing, biomedical analysis, and wireless communication technologies, all of which are key enablers to today's modern society. In this series, we explore more about the works of signal processing and engage with various global speakers.
Our Digital Life Podcast: A series by IEEE-SPS
Signal Processing and AI Synergies
In this episode of the IEEE Signal Processing Society podcast, Dennis K. Chrogony, Education Board Outreach and Visibility Committee Member interviews Sergios Theodoridis, Professor Emeritus, Signal Processing and Machine Learning, National and Kapodistrian University of Athens, Greece, Aalborg University, Denmark, and Shenzhen Research Institute of Big Data, Chinese University of Hong Kong, China. They delve into the evolution and impact of signal processing and AI and machine learning on technological advancements.
Professor Sergios Theodoridis
Prof. Theodoridis has made countless contributions to the field of signal processing and machine learning. He has authored several books, received multiple awards, and earned prestigious accolades like the EURASIP Athanasios Papoulis Award and the IEEE Signal Processing Society Education Award. His leadership positions, including his role as Vice President of the IEEE Signal Processing Society highlight his significant influence and respect within the academic and professional community.
In this episode, Prof. Theodoridis discusses the advancements in various areas of signal processing, highlighting AI and machine learning as pivotal technologies in modern society. He explains how the seamless integration of machine learning into signal processing has led to significant improvements in areas like speech and audio recognition and natural language processing.
He also notes that while the core goals of signal processing remain unchanged, new techniques from the machine learning community have greatly enhanced its applications.