Advanced Analytics Roundtable - Sensor Showdown 2020

There is much excitement generated about the advent of new capabilities in space. The recent NASA SpaceX launch seemingly captured the attention of the world. In terms of remote sensing capabilities, it is indeed an exciting time as new and more advanced capabilities are arriving in space at a remarkable pace. With less fanfare, an equally important revolution is taking place on the ground with regard to managing the increasing volumes of data being produced by these new space platforms. The panel will feature four thought leaders in the field of advanced analytics in a unique gathering of industry luminaries.

Mr. Masback is the Owner of Plum Run, LLC, providing advisory and consulting services to leading-edge companies and government organizations working in geospatial intelligence and related fields. He is also an active early stage investor. He is a member of the Federal Advisory Board of Orbital Insight, a member of the Advisory Boards of Hermeus and Anno.Ai, and a strategic advisor to HySpecIQ, OmniSci, ICEYE, and two stealth startups. He was recognized as the Geospatial Ambassador of the Year at the 2019 Geospatial World Forum. Prior to founding Plum Run, Mr. Masback spent over a decade as the President / Chief Executive Officer of the United States Geospatial Intelligence Foundation (USGIF) and over 20 years combined as an officer in the U.S. Army and as a government civilian employee, culminating as a member of the Defense Intelligence Senior Executive Service at the National Geospatial-Intelligence Agency (NGA).

David Potere is currently Head of GeoInnovation at Indigo. He was CEO and co-founder of TellusLabs, Co-dounder of BCG Gamma, and was a US Navy Surface Warfare Officer. David has an AB from Harvard University, MA Remote Sensing from Boston University, and a Ph.D in Geo-Demography from Princeton University.

Jimi is founder & CEO of Orbital Insight. Orbital Insight helps business and policy decision makers understand economic and societal trends through geospatial analytics. His corporate focus is to develop artificial intelligence, machine learning, and computer vision, creating a new source of market data for diverse industries. Jimi was the SVP of Science and Engineering at the Climate Corporation. Prior to that, he was CTO and Software Architect at Moon Express whose goal was putting the first commercial robot on the moon. As the Engineering Director for Google Book Search, he was in charge of Google’s project to scan, index, and make searchable all the world’s books. He also served as EVP of Engineering at Composite Software, a startup focusing on data virtualization. At Nasa Ames Research Center, Jimi led Autonomy and Robotics projects. He has authored over 15 peer reviewed publications, resulting in five patents.

Todd is the CEO and co-founder of OmniSci. Todd originally conceived of the idea of a GPU-accelerated analytics platform while conducting graduate research at Harvard on the role of social media in the Arab Spring, after tiring of waiting hours or sometimes days for traditional CPU-based platforms to run analytic workflows over hundreds of millions of tweets. He later joined MIT’s CSAIL as a research fellow, under the supervision of Sam Madden and Turing Award winner Michael Stonebraker, before founding OmniSci.

Daniela serves as the Chief Technology Officer at Ursa Space Systems (Ursa). Her focus at Ursa is growing a strong engineering team and a software infrastructure for advanced machine learning and computer vision algorithms that provide business intelligence and solutions from Synthetic Aperture Radar (SAR) satellite data. Previously, Daniela worked at Descartes Labs and at Los Alamos National Laboratory, working on remote sensing and machine learning applications in various research areas, including space systems, astronomy, on-orbit RF and radar systems, and nuclear non-proliferation. She received her M.S and Ph.D. in Electrical Engineering from the University of Maryland, College Park in 2012 with a focus in signal processing, computer vision, and machine learning.