Scientific Computing with Python
Austin, Texas • July 6-12, 2015

SciPy 2015 Talk & Poster Presenters

Are you a talk or poster presenter? Please send a brief bio, title, organization, and photo (if desired) to so we can include you on the page! See the SciPy 2015 tutorial presenters here

See the talk and poster schedule here. 

Bagrat Amirbekian
University of California, San Francisco
Ankur Ankan
Tiago Antao
Damian Avila
Continuum Analytics
Michael Aye
Paige Bailey
James A. Bednar
University of Edinburgh
Cesar Beneti
SIMEPAR - Sistema Meteorológico do Paraná
Sebastian Benthall
Berkeley School of Information
Jean Bilheux
Oak Ridge National Laboratory
Evan Bolyen
Northern Arizona University
Blake Borgeson
Recursion Pharmaceuticals
Erik Bray
Space Telescope Science Institute
Lori Burns
Georgia Tech Chemistry
Howard Bushouse
Space Telescope Science Institute
Matthias Bussonnier
UC Berkeley BIDS / IPython / Jupyter
Chris Calloway
Luke Campagnola
University of North Carolina, Chapel Hill
Thomas Caswell
Brookhaven National Laboratory
Bryan Chastain
University of Texas, Dallas
Winnie Cheng
Chief Data Scientist
Phillip Cloud
Continuum Analytics
Rowan Cockett
The University of British Columbia
Roberto Colistete Junior
UFES - Federal University of Espirito Santo (Brazil)
Andrew Collette
University of Colorado, Boulder
Andrew Collette is a research scientist at the University of Colorado’s IMPACT accelerator facility, a NASA-funded research center for laboratory investigation of hypervelocity micrometeoroid impacts. He holds a Ph.D. in Physics from UCLA, and in 2013 founded Heliosphere Research, a consulting and software development company serving the Python and LabVIEW communities. Andrew wrote the O’Reilly book Python and HDF5, and is the lead developer of the h5py project.
Scott Collis
Argonne National Laboratory
Yannick Congo
NIST/Blaise Pascal University
I am currently a guest researcher at NIST and a PhD student in Software Engineering from the EDSPI doctoral school at the Blaise Pascal University in Clermont-Ferrand, France. I focus on standards to enhance the reproducibility of computational results and to bring more automation to all scientific computations. My previous work was on OOF (Object Oriented for Finite elements analysis) at NIST.
Carlos Cordoba
Continuum Analytics
Matthew Craig
Minnesota State University Moorhead
Nicola Creati
James Crist
Graduate Student
University of Minnesota
Jim is a graduate student at the University of Minnesota, studying Mechanical Engineering. He is a core contributor to both the SymPy and PyDy projects, and uses these packages in a workflow to do everything from modeling dynamic systems to testing estimation and control algorithms.
Mellissa Cross
David Dotson
Arizona State University
David Dotson is a Ph.D. student in Oliver Beckstein's computational biophysics lab in the Center for Biological Physics at Arizona State University. David specializes in deconstructing the detailed molecular mechanisms of membrane proteins using atomistic simulations, and spends much of his time writing code to distill useful information from the ever-growing volume of simulation data we can now produce. Although his background is in physics, his interests and strategies for dissecting problems in molecular mechanics are increasingly taking cues from the data science world. David is a contributor to MDAnalysis and the author of MDSynthesis, a new python package aimed at making interactive molecular dynamics data exploration efficient and fun.
Zubin Dowlaty
Mu Sigma
Allen Downey
Professor of Computer Science
Olin College
Allen Downey is a Professor of Computer Science at Olin College and author of Think Python, Think Stats, Think Bayes, Think Complexity, and several other computer science books. He holds B.S. and M.S. degrees from MIT and a Ph.D. in Computer Science from U.C. Berkeley. He has previously taught at Colby College and Wellesley College, and was a Visiting Scientist at Google, Inc.
Chris Drake
Prior to joining Google, Chris worked at Intel for nine years, doing various things related to chip design and validation. He graduated from University of Michigan, Ann Arbor, with an MS in computer engineering. Chris has a passion for Python, and anything related to digital logic. He created PyEDA ( as a hobby project, and hacks on it in his spare time. He lives in Mountain View, CA, with his wife and two children.
Scott Draves
Two Sigma Open Source
Michael Droettboom
Space Telescope Science Institute
Haitham Elmarakeby
Virginia Tech University
Philip Elson
Met Office
Loïc Estève
Carson Farmer
University of Colorado, Boulder
Filipe Fernandes
Chris Fonnesbeck
Assistant Professor, Department of Biostatistics
Vanderbilt University School of Medicine
Chris is an Assistant Professor in the Department of Biostatistics at the Vanderbilt University School of Medicine in Nashville, TN. He specializes in computational statistics, Bayesian methods, meta-analysis, and applied decision analysis. Chris started the PyMC project, a package for Bayesian statistical analysis in Python, and continues as a PyMC developer today. He originally hails from Vancouver, BC and received his Ph.D. from the University of Georgia.
Justin Foong
The Hospital for Sick Children
Anderson Gama
SIMEPAR - Sistema Meteorológico do Paraná
Eleftherios Garyfallidis
University of Sherbrooke
Scott Giangrande
Brookhaven National Laboratory
Robert Grant
Scientific Software Developer
Robert is a Scientific Software Developer at Enthought. He holds a B.S., an M.S.E., and a Ph.D. in Electrical Engineering from the University of Texas at Austin. Before joining Enthought, he was a researcher in the areas of wireless networking and software engineering, publishing on software-defined radio, rate-adaptation in wireless networks, and the evaluation of instructable software agents.
Perry Greenfield
Space Telescope Science Institute
Kevin Gullikson
University of Texas
Kevin Gullikson got a bachelors degree in Physics at Illinois Institute of Technology, and is currently pursuing a PhD in astrophysics from the University of Texas. His research focuses on searching for and characterizing companions to hundreds of nearby stars, as part of an effort to learn about how the companions may have formed. He maintains an active presence on github[1] and has developed a python package to fit and remove the absorption from the Earth's atmosphere in astronomical spectra[2]. Kevin plans to graduate with his PhD next Spring, and is interested in the field of data science and machine learning.
Nick Guy
University of Wyoming
Jonathan Guyer
Matt Hall
Agile Geoscience
Jessica Hamrick
University of California, Berkeley
Johanna Hansen
Woods Hole Oceanographic Institution
Lindsey Heagy
University of British Columbia: Geophysical Inversion Facility
Brian Helba
Kitware Inc
Jonathan Helmus
Argonne National Laboratory
Ian Henriksen
Brigham Young University
Maik Hiestermann
University of Potsdam
Bill Hoffman
Stephen Hoover
Data Scientist
Civis Analytics
Stephen Hoover is a Data Scientist at Civis Analytics, where he develops machine-learning algorithms to power the Civis cloud-based data science platform. His background is in physics and cosmology, where he used first C++ and then Python to build data analysis pipelines for astrophysical observations. His passion is building software tools to extract meaning from raw data.
Stephan Hoyer
The Climate Corporation
Jaime Huerta-Cepas
Kathryn Huff
University of California, Berkeley
Kathryn (Katy) Huff is a Fellow with the Berkeley Institute for Data Science and a postdoctoral scholar with the Nuclear Science and Security Consortium at the University of California Berkeley. In 2013, she received her Ph.D. in Nuclear Engineering from the University of Wisconsin Madison. She also holds a bachelor's degree in Physics from the University of Chicago. She has participated in varied research including experimental cosmological astrophysics, experimental non-equilibrium granular material phase dynamics, computational nuclear fuel cycle analysis, and computational reactor accident neutronics. She is a co-author of the new O'Reilly book "Effective Computation in Physics," was a co-founder of The Hacker Within, and has been an instructor for Software Carpentry since 2011. Among other professional service, she is the Chair of the Software Carpentry Foundation Steering Committee, a division officer in the American Nuclear Society, and has served three consecutive years as a SciPy organizer.
Jacob Hummel
University of Texas, Austin
Jeannie Irwin
University of Pittsburgh
Kelsey Jordahl
Scientific Software Developer
Kelsey is a geophysicist and scientific software developer who works on computational problems and data visualization. He has taught college courses from introductory science classes to graduate level seismology, and currently teaches weeklong python training courses for scientific and financial audiences. He holds a Ph.D. in marine geophysics from the MIT/Woods Hole Oceanographic Institution Joint Program in Oceanography.
Alec Kaija
Wei Kang
GeoDa Center for Geospatial Analysis & Computation
Kyle Kastner
Graduate Student
Université de Montréal
My passion is designing and analyzing cross-disciplinary scientific experiments and statistical models.
Jackie Kazil
Kyle Kelley
Hyungtae Kim
University of California, Irvine
Brad King
Joe Kington
Irma Kramer
PyLadies, Austin
Juliana Leonel
Universidade Federal da Bahia
Rich Lewis
University of Cambridge
David Lippa
Principal Software Engineer
As Principal Software Engineer at RealMassive, David Lippa has designed and implemented the search and recommendation engine of the RealMassive platform that currently covers over 4.5 billion square feet of commercial real estate inventory. Prior to joining RealMassive, Mr. Lippa was a Senior Software Engineer who was deeply involved in the development of algorithms, graphical user interfaces (GUIs), data structures in a variety of domains, programming languages, and environments. In his spare time, Mr. Lippa likes to volunteer his time in the industry as a closed beta tester and with non-profits to further the pursuit of Science, Technology, Engineering, and Math (STEM) fields for secondary school students. Mr. Lippa graduated with both a B.A. and M.A. in Computer Science from Brandeis University.
Margaret Mahan
Subir Mansukhani
Mu Sigma
David Masad
George Mason University
Ryan May
Amelia McBee Henriksen
Brigham Young University
Matthew McCormick
Brian McFee
New York University
Michael McKerns
UQ Foundation
Keynote Speaker: Wes McKinney
Software Engineer, author of pandas (Python Data Analysis Library)
Wes McKinney is a software engineer at Cloudera. Prior to that, Wes was co-founder of DataPad, and CTO and Cofounder of Lambda Foundry, Inc. From 2010 to 2012, he served as a Python consultant to hedge funds and banks while developing pandas, a widely used Python data analysis library. From 2007 to 2010, he researched global macro and credit trading strategies at AQR Capital Management. He graduated from MIT with an S.B. in Mathematics. Wes is author of the O'Reilly book Python for Data Analysis.
Aaron Meurer
Steve Miller
Oak Ridge National Laboratory
Michael Milligan
Minnesota Supercomputing Institute, University of Minnesota
Ross Mitchell
Professor of Radiology, Mayo Clinic College of Medicine
Mayo Clinic Arizona
Dr. Mitchell has a proven research track-record comprising 110 reviewed publications, including 25 patents and applications, 120 invited presentations, and over 200 published abstracts. His research is focused on new algorithms to extract information from medical images to improve the diagnosis, treatment, visualization and monitoring of disease. He was recruited from Canada to Mayo Clinic Arizona in 2011 to build a new Division of Medical Imaging Informatics. He is a Co-Founder and the Founding Scientist of Calgary Scientific Inc. (CSI). CSI manufactures the only cloud-based zero-footprint tele- radiology system cleared for diagnostic use with all medical imaging modalities (except mammography) on web browsers, iOS and Android devices. This technology is licensed by numerous companies and is available in over 30 countries around the world.
Jason Moore
Lead Developer
Jason is a lead developer with both the PyDy and SymPy projects. He utilizes both packages to run optimal control algorithms for biomechanical systems, in particular data driven powered prosthetic designs. He is a strong proponent for Open Science and has a PhD in Mechanical and Aerospace Engineering from UC Davis.
Kai Muehlbauer
University of Bonn
Andreas Mueller
New York University Center for Data Science
Andreas is an Assistant Research Scientist at the NYU Center for Data Science, building a group to work on open source software for data science. Previously he worked as a Machine Learning Scientist at Amazon, working on computer vision and forecasting problems. He is one of the core developers of the scikit-learn machine learning library, and maintained it for several years. His mission is to create open tools to lower the barrier of entry for machine learning applications, promote reproducible science and democratize the access to high-quality machine learning algorithms.
Ana Nelson
Cosmify, Dexy
Stephen Nesbitt
University of Illinois
Tim O'Donnell
Mount Sinai School of Medicine
Richard Otis
Pennsylvania State University
Michael Pacer
Graduate Student
University of California, Berkeley
Mike Pacer is a graduate student at the University of California at Berkeley. He studies how people think and behave in order to embed that thinking and behavior in computational systems. Mike specializes in finding new kinds of problems inspired by human cognition, and developing the formal tools for encoding those problems. For example, he studies continuous-time causal induction, formal models of causal explanation, and computational approaches to the history and philosophy of science.
Randy Paffenroth
Worcester Polytechnic Institute
Abinash Panda
Franco Pestilli
Indiana University
Michka Popoff
Cory Quammen
Min Ragan-Kelley
John Readey
HDF Group
Andrew Reid
Sergio Rey
GeoDa Center for Geospatial Analysis and Computation
Jai Ram Rideout
Northern Arizona University
Adam Robbins-Pianka
University of Colorado, Boulder
Ariel Rokem
The University of Washington eScience Institute
Benjamin Root
Gudni Rosenkjaer
University of British Columbia
Phil Roth
As a data scientist at Endgame, Phil develops data products that help security analysts find and respond to threats. This work has ranged from tuning a machine learning algorithm to best identify malware to building a data exploration platform for HTTP request data. Previously, he developed image processing algorithms for a small defense contractor. While in graduate school for physics, Phil used a machine learning algorithm and the IceCube detector at the south pole to search for neutrinos from other galaxies.
Alex Rubinsteyn
Mount Sinai School of Medicine
Philipp Rudiger
University of Edinburgh
Stanley Seibert
Continuum Analytics
Elizabeth Seiver
Sebastian Sepulveda
Universidad de Valaparaiso
Richard Shaw
National Optical Astronomy Observatory
Richard Signell
Brian Smith
Ball State University - Deptartment of Political Science
Kurt Smith
Scientific Software Developer
Kurt has been using Python in scientific computing for nearly ten years, and has developed tools to simplify the integration of performance-oriented languages with Python. He has contributed to the Cython project, implementing the initial version of typed memoryviews and native cython arrays. He uses Cython extensively in his consulting work at Enthought. Throughout his undergraduate and graduate studies he used Python and Cython at every opportunity. Cython was particularly useful when developing high-performance parallel simulations of plasma turbulence for his doctoral research. Dr. Smith recently authored a book on Cython with O'Reilly and he has also trained hundreds of scientists, engineers, and researchers in Python, NumPy, Cython, and parallel and high-performance computing as part of Enthought's extensive on-site and on-line Python training
Nathaniel Smith
University of California, Berkeley
Krishna Sridhar
Paolo Sterzai
Jean-Luc R. Stevens
University of Edinburgh
Kristen Thyng
Assistant Research Scientist
Texas A&M University
Kristen Thyng is an assistant research scientist in Oceanography at Texas A&M University. Her research areas include transport processes and the physics of flows (particularly in estuaries and coastal seas), and tidal energy. She is enthusiastic about Python and computational science, and a proponent of clear and beautiful visualizations.
Erik Tollerud
Hubble Fellow
Astropy/Yale University
Erik is a Hubble (Postdoctoral) Fellow at Yale University in New Haven, CT. His research interests focus on both observational and theoretical aspects of using nearby dwarf galaxies to determine the nature of dark matter and galaxy formation. He is one of the founders and coordinators of the Astropy Project, as well as author of and contributor to a variety of of other python software packages for astrophysics. He received his undergrad degree at the University of Puget Sound, and MS and PhD from the University of California, Irvine.
Kester Tong
Jordi Torrents
Mattheus Ueckermann
Bharat Upadrasta
Mu Sigma
Bryan Van de Ven
Continuum Analytics
Stefan van der Walt
University of California, Berkeley
Stefan van der Walt is an assistant researcher at the Berkeley Institute for Data Science and a senior lecturer in applied mathematics at Stellenbosch University, South Africa. He has been an active member of the scientific Python community since 2006, and frequently teaches Python at workshops and conferences. He is the founder of scikit-image and a contributor to numpy, scipy and dipy.
Keynote Speaker: Jake VanderPlas PhD
Director of Research – Physical Sciences
eScience Institute, University of Washington
Jake VanderPlas is the Director of Research in the Physical Sciences at the University of Washington's eScience Institute, an interdisciplinary program designed to support data-driven discovery in a wide range of scientific fields. His own research is in astronomy, astrophysics, machine learning, and scalable computation. In addition, he is a maintainer and/or frequent contributor to many open source Python projects, including scikit-learn, scipy, mpld3 and others. He occasionally blogs about Python, machine learning, data visualization, open science, and related topics at
Yoshiki Vazquez-Baeza
University of California, San Diego
Jason Vertrees
Chief Technology Officer
As Chief Technology Officer at RealMassive, Jason Vertrees, Ph.D, leads the company’s team of scientists and engineers to ensure that RealMassive’s commercial real estate customers are receiving best-of-breed technology solutions customized to their specific business needs. Prior to joining RealMassive, Dr. Vertrees was Director of Core Modeling Products at Schrodinger. He is focused on leveraging his expertise in product strategy and user experience (UX) to best serve each of RealMassive’s customers. Dr. Vertrees graduated from the University of Texas with two Bachelor of Arts degrees: one in Computer Science and one in Japanese. He received his Ph.D. in Structural and Computational Biology and Theoretical and Computational Biophysics from the University of Texas Medical Branch.
Roberto Vidmar
Josh Walawender
Instrument Astronomer
Subaru Telescope
Josh Walawender is an Instrument Astronomer at the Subaru Telescope on Maunakea in Hawai’i working on maintenance and upgrades for Subaru’s FMOS and MOIRCS instruments. He has a strong interest in small robotic telescopes and time domain astronomy. Josh received his undergraduate degree from the University of California at Berkeley and his PhD from the University of Colorado at Boulder.
Brian Wandell
Stanford University
Jonathan Whitmore
Silicon Valley Data Science
Jonathan Whitmore, PhD, is a Data Scientist at Silicon Valley Data Science. He has a diverse range of interests and is excited by the challenges in data science and data engineering. Before moving into the tech industry, Dr. Whitmore worked as an astrophysicist in Melbourne, Australia, researching whether the fundamental physical constants have changed over the age of the universe. He has a long-standing commitment to the public understanding of science and technology, and has contributed to FOSS projects. He co-starred in the 3D IMAX film Hidden Universe, which is currently playing in theaters around the world, and is a sought after conference speaker on science and technical topics. Dr. Whitmore received his PhD in physics from the University of California, San Diego, and graduated magna cum laude from Vanderbilt University with a Bachelor of Science triple major in physics (with honors), philosophy, and mathematics.
Mark Wickert
University of Colorado
Mark Wiebe
Thinkbox Software
Keynote Speaker: Chris Wiggins
Chief Data Scientist; Associate Professor of Applied Mathematics
The New York Times & Columbia University

Chris Wiggins is Chief Data Scientist at The New York Times, an associate professor of applied mathematics at Columbia University, and the co-founder and co-organizer of hackNY. At Columbia he is faculty in the Department of Applied Physics and Applied Mathematics, a founding member of the Department of Systems Biology, a founding member of the Data Science Institute, affiliated faculty in the Department of Statistics, and an instructor in the School of Journalism. His research focuses on applications of machine learning to real-world data, particularly biology. Prior to joining the faculty at Columbia he was a Courant Instructor at NYU and earned his PhD at Princeton University in theoretical physics. In 2014 he was elected Fellow of the American Physical Society and is a recipient of Columbia's Avanessians Diversity Award.

Kyle Wilcox
Axiom Data Science
Christopher Wilmer
University of Pittsburgh
Andrew Yan
Wenduo Zhou
Oak Ridge National Laboratory
En Zyme
Proteasome Digest