Reverse-engineering data: Explaining data and diagnosing errors
Online repositories, marketplaces, and other sharing platforms have facilitated the dissemination, availability, and sharing of data. At the same time, sources of data are becoming more diverse, more complex, and more interconnected. In this new data-producing and data-sharing world, most data is not curated and data origin and derivation are often obscured. Yet, now more than ever, applications are heavily data-driven and important decisions are made based on data (e.g., what infrastructure should the government invest in, or who gets a mortgage). In this talk, I will discuss new evolving needs of data analysis, including providing explanations and facilitating data understanding, and diagnosing problems in data.
Anticipating, avoiding, and sometimes embracing our failures
Failure is a normal part of life and of academia. More often than not, what we consider failures are not dreadful disasters, but rather, missed opportunities. I will talk about my own experiences with failure, the opportunities I missed, in particular during my graduate career, and the lessons I learned.
Alexandra Meliou is an Assistant Professor in the College of Information and Computer Science, at the University of Massachusetts, Amherst. She has held this position since September 2012. Prior to that, she was a Post-Doctoral Research Associate at the University of Washington, working with Dan Suciu. Alexandra received her PhD and MS degrees from the Electrical Engineering and Computer Sciences Department at the University of California, Berkeley, in 2009 and 2005, respectively. She is the recipient of a 2015 NSF CAREER Award, a 2013 Google Faculty Research Award, and a 2008 Siebel Scholarship.