Episode 54: Information Retrieval Research, Data Science For Space Missions, and Open-Source Software with Chris Mattmann

Chris Mattmann is the Chief Technology and Innovation Officer at NASA JPL. He was also JPL's first Principal Scientist in the area of Data Science. He has over 19 years of experience at JPL and has conceived, realized, and delivered the architecture for the next generation of reusable science data processing systems for NASA's Orbiting Carbon Observatory, NPP Sounder PEATE, and the Soil Moisture Active Passive (SMAP) Earth science missions. His work has been funded by NASA, DARPA, DHS, NSF, NIH, NLM, and private industry and commercial partnerships. He was the first Vice President (VP) of Apache OODT (Object Oriented Data Technology), the first NASA project at the Apache Software Foundation (ASF), and he led the project's transition from JPL to the ASF. He contributes to open source and was a former Director at the Apache Software Foundation (2013-18). He was one of the initial contributors to Apache Nutch as a member of its project management committee, the predecessor to Apache Hadoop. He is the progenitor of the Apache Tika framework, the digital "babel fish," and the de-facto content analysis and detection framework that exists. Today he contributes to TensorFlow and all things machine learning. Finally, he is the Director of the Information Retrieval & Data Science (IRDS) group at USC and Adjunct Associate Professor. He teaches graduate courses in Content Detection & Analysis & Search Engines & Information Retrieval. He has materially contributed to understanding the Deep Web and Dark Web through the DARPA MEMEX project. His work helped uncover the Panama Papers scandal.