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Interviews are organized by the month and year in which they first appeared. To find an interviewee by name, use the search bar (at upper right).

Interviews

  • Computing a landing spot on Mars: an interview with Victor Pankratius

    The purpose of the Mars rover is in its name---to rove, explore, study Martian geology, look for signs of water, look for signs of life (past or present), etc. However, achieving these and other objectives requires putting the rover down on a suitable landing site, i.e. a site suitable for searching for the desired information and safe to land and function without hindrance or breaking down.

    The data for making these decisions comes from prior Mars missions. Selecting a suitable landing site is a complex process typically taking several years. Researchers at MIT's Kavli Institute for Astrophysics and Space Research prototyped a new software that can help NASA mission planners to more rapidly and reliably find landing sites, potentially reducing the total time required to weeks. In this interview, Victor Pankratius, leader of the research team, shares some insight into the project.

  • An interview with Jason Ernst: incentives of a decentralized networking infrastructure

    In this series of interviews with innovation leaders, Ubiquity Associate Editor and software engineer, Dr. Bushra Anjum, sits down with Jason Ernst, CTO of RightMesh, to discuss how his company is using mobile mesh networks to decentralize existing network infrastructure in areas where it doesn't exist or is too expensive to maintain--effectively putting the control of data in the hands of the people.

  • An interview with Indrajit Roy: toward self-correcting systems

    Indrajit Roy is a staff engineer at Google. He is currently working on peta-scale distributed databases. Previously, he was a principal researcher at HP Labs where he led the development of Distributed R, an open source HP product that brings the benefits of parallelism to data scientists. Roy received his Ph.D. in computer science from UT Austin. He is also an inaugural member of the ACM Future of Computing Academy.

  • An interview with Lauren Maffeo: understanding the risks of machine learning bias

    Lauren Maffeo is a research analyst who joined the global technology sector in 2012. She started her career as a freelance journalist covering tech news for The Next Web and The Guardian. She has also worked with CEOs of pre-seed to profitable SaaS startups on media strategy. Lauren joined GetApp, a Gartner company, as a content editor in 2016. She covers the impact of emerging tech like AI on small and midsize business owners.

    Lauren has been cited by sources including Forbes, Fox Business, DevOps Digest, The Atlantic, and Inc.com. In 2017, Lauren was named to The Drum's 50 Under 30 list of women worth watching in digital. She holds an M.Sc. from The London School of Economics and a certificate in Artificial Intelligence: Implications for Business Strategy from MIT's Sloan School of Management.