Pascal Bugnion is a data scientist with a strong analytical background as well as a passion for software development. He pursued a materials science undergraduate degree at Oxford University. He then went on to complete a PhD in computational physics at Cambridge University, during which he developed and applied the quantum Monte Carlo methods to solidstate physics. This resulted in four publications, including an article in Physical Review Letters, the leading physics journal. He now works as a database architect for SCL Elections, a company that specializes in predicting voter behavior.
Pascal is strongly interested in contributing to open source software, especially the Python scientific stack. He has contributed to NumPy, matplotlib, and IPython, and maintains ScikitMonaco, a Python library for Monte Carlo integration as well as GMaps, a Python module for embedding Google maps in IPython notebooks.
Michael Otte has interests that include the application of artificial intelligence to robotics, with a focus on path planning algorithms and multirobot systems. He has been using the Julia language since 2012 to implement motion planning, graph search, and other algorithms, many of which have appeared in top peer-reviewed publications. See www.ottelab.com for more details. He is currently a research associate with the Department of Aerospace Engineering Sciences at the University of Colorado at Boulder. Prior to this, he was a postdoctoral associate with the Laboratory for Information and Decision Systems (LIDS) at the Massachusetts Institute of Technology. He received his PhD and MS degrees at the University of Colorado at Boulder in computer science and a BS degree in aeronautical engineering and computer science from Clarkson University.
Dustin Stansbury received his BS degree in both physics and psychology from Appalachian State University and his PhD degree in vision science from the University of California, Berkeley. His graduate research focused on developing hierarchical statistical models of the mammalian visual and auditory systems. He currently works in the field of music retrieval and regularly contributes to his machine learning blog, theclevermachine.
Dustin has contributed a chapter to the text book, Scene Vision: Making sense of what we see, MIT Press 2014, Cambridge MA.