SciPy 2018 Schedules

Tutorial Schedule




We are thrilled to announce our Keynote Speakers


 Ralf Gommers is currently a senior data scientist in the forestry industry, at FP Innovations (Vancouver, Canada) and Scion (Rotorua, New Zealand). His research interests there include modelling of forest diseases and productivity, and scaling up remote sensing forestry applications - mainly using tools in the scientific Python ecosystem. He has previously worked on cold atom physics, MRI systems and lithography machines. Ralf  is a core developer of SciPy, NumPy and PyWavelets, and is a board member of NumFOCUS. His focus over the last decade has been on growing the scientific Python ecosystem and making its core projects more sustainable.
 Leo Singer earned his Bachelor's degree in 2009 at the University of Maryland and his Ph.D. in physics from the California Institute of Technology in 2014. He is currently a Research Astrophysicist at NASA's Goddard Space Flight Center. By day, he works on real-time detection and real-time Bayesian inference in data from the Laser Interferometer Gravitational-wave Observatory (LIGO). By night, he tracks down optical and infrared signatures of these events using the Zwicky Transient Facility (ZTF) and a host of other ground- and space-based astronomical facilities.
  

Tracy Teal is a co-founder and the Executive Director of Data Carpentry. Prior to Data Carpentry she was an Assistant Professor at Michigan State University in Microbiology and Molecular Genetics. She has a PhD from California Institute of Technology in Computation and Neural Systems and was an NSF Postdoctoral Fellow in Biological Informatics. She began work in computing as a Linux systems administrator and has since developed several open source bioinformatics tools. She has developed and taught short courses in bioinformatics and is on the programming committee for SciPy. She believes that advancing computing involves both tools and people and is focused on training researchers in data analysis and programming to empower researchers and enable data-driven discovery.