DX-2016 Invited Talks
Kansas City Royals
The knowledge and experience gained in Dr Mack's projects in Diagnostics and and Anomaly Detection for Aircraft provided a unique look at player performance analytics, that goes beyond the data-driven tools used. In this talk, Dr Mack will discuss a bit about a domain transformation that is inspired from the diagnostics work, and what the future might hold for sports analytics in this mold. With that link in place, Dr Mack will then touch upon how he would bring information back across that transformation into PHM.
Bio: Dr. Daniel Mack enters his fourth season with the Royals and second with the title of Director of Baseball Analytics/Research Science, being promoted on January 5, 2015. He was originally hired by the organization in 2013 as an Analyst in Baseball Analytics. Mack works closely with the Baseball Analytics staff to assist with quantitative research and development of analytics in support of all areas of Baseball Operations. Prior to accepting the job with Kansas City, Mack obtained a doctorate in Computer Science from Vanderbilt University. At Vanderbilt, Mack's dissertation focused on Machine Learning and Anomaly Detection. While pursuing his doctorate, Mack worked as a research assistant at the Institute for Software Integrated Systems where he and his research group won the NASA Associate Administrator Award for Technology and Innovation for work combining machine learning with fault diagnosis. He was also a teaching assistant while completing his master's degree in computer science with a concentration in machine learning at Columbia University in New York. Mack graduated with a bachelor's degree in computer science from the University of Notre Dame in 2006. A native of Reno, Nev., he resides in Kansas City, Mo.
Although considerable effort has been invested in developing methods for testing and failure detection, synthesis of programs from abstract models and verification of programs (and models), techniques for locating the root cause of observed program failures are still relatively immature. Therefore, the utility for general testing and debugging techniques remain limited to specific programs, execution environments, and problem contexts. Furthermore, no plug and play toolset exists providing state-of-the-art techniques to help developers with testing and debugging.
In this talk, we will discuss current state-of-the-art techniques for testing and debugging and how the combination of all these techniques helps to gain a better understanding of the software application. The techniques discussed in the talk are available within a plugin for the Eclipse IDE, coined GZoltar.
Bio: Dr. Rui Abreu holds a Ph.D. in Computer Science - Software Engineering from the Delft University of Technology, The Netherlands, and a M.Sc. in Computer and Systems Engineering from the University of Minho, Portugal. His research revolves around software quality, with emphasis in automating the testing and debugging phases of the software development life-cycle as well as self-adaptation. Dr. Abreu has extensive expertise in both static and dynamic analysis algorithms for improving software quality. He is the recipient of 5 Best Paper Awards, and his work has attracted considerable attention. He is currently a member of the Model-Based Reasoning group at PARC's System and Sciences Laboratory.