Scientific Computing with Python
Austin, Texas • July 10-16, 2017
 

SciPy 2017 Conference Presenters

Tutorial Presenters

Aron Ahmadia
Capital One
 
Lorena Barba
George Washington University
Lorena A. Barba is an Associate Professor of Mechanical and Aerospace Engineering at the George Washington University in Washington, DC. Prof. Barba is an advocate of open-source software for science and open educational resources, and shares her courseware on iTunesU and YouTube. She is also interested in education technology, social learning and the recent spread of massively open online courses, as well as innovations in STEM education, including flipped classrooms and other forms of blended learning.Her research includes computational fluid dynamics, high-performance computing, computational biophysics and animal flight.
 
Maxim Belkin
Software Carpentry
Maxim Belkin is an Education and Training Coordinator in the Blue Waters project at the National Center for Supercomputing Applications. Prior to his current position, he was a Postdoctoral Fellow in Computational Biophysics at the University of Illinois at Urbana-Champaign. He received his Ph.D. in Physics from the Illinois Institute of Technology in 2010. Currently, Maxim is working on developing and organizing scalable and extensible educational and training opportunities for the users of high-performance computing facilities in general and Blue Waters system in particular. Maxim is a certified Software Carpentry instructor.
 
Daniel Chen
Virginia Tech
 
Sylvain Corlay
Sylvain Corlay is an applied mathematician specializing in stochastic analysis and optimal control. He holds a PhD in applied mathematics from University Paris VI. As an open source developer, Sylvain contributes to Project Jupyter in the area of interactive widgets for the notebook, and is steering committee member of the Project. Besides Jupyter, Sylvain contributes to a number of scientific computing open-source projects such as bqplot, xtensor and ipyleaflet. Sylvain founded QuantStack in September 2016. Prior to founding QuantStack, Sylvain was a quant researcher at Bloomberg and an adjunct faculty member at the Courant Institute and Columbia University.
 
Matt Craig
Minnesota State University Moorhead
 
James Crist
Continuum Analytics
Jim Crist holds a Bachelors and a (tentative) Masters in Mechanical Engineering from the University of Minnesota. Whilst procrastinating on his thesis, he got involved in the scientific Python community. He is currently a software developer at Continuum Analytics.
 
Björn Dahlgren
KTH Royal Institute of Technology, SymPy
 
Allen Downey
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.
 
Martin Durant
Continuum Analytics
 
Gil Forsyth
George Washington University
Gil Forsyth is a graduate student at the George Washington University in Washington, D.C., studying mechanical engineering and computational fluid dynamics. He is a contributor to xonsh and a proud open-source advocate. With Professor Lorena Barba, he helped create and teach GW's first MOOC: Practical Numerical Methods with Python. He was awarded Outstanding Graduate Teaching Fellow of the year for 2014 by the BU College of Mechanical Engineering
 
Emmanuelle Gouillart
 
Alexandre Gramfort
INRIA, Université Paris-Saclay
Alexandre Gramfort is researcher at INRIA and formerly Assistant Professor at Telecom ParisTech, Université Paris-Saclay, in the image and signal processing department from 2012 to 2017. His field of expertise is signal and image processing, statistical machine learning and scientific computing applied primarily to functional brain imaging data (EEG, MEG, fMRI). His work is strongly interdisciplinary at the interface with physics, computer science, software engineering and neuroscience. He is a core developer of the Scikit-Learn machine learning software (http://scikit-learn.org) since 2010 and at the origin of the MNE-Python software (http://martinos.org/mne/) now used and developed across many labs worldwide. He started also the PySurfer package and contributed to various neuroscience Python packages (nilearn, nibabel).
 
Jason Grout
Bloomberg LP
Jason Grout is a Jupyter developer at Bloomberg, working primarily on JupyterLab and the interactive Jupyter widgets library. He has also been a major contributor to the open source Sage mathematical software system and co-organizes the PyDataNYC Meetup. Previously, Jason was an assistant professor of mathematics at Drake University in Des Moines, Iowa. He earned a PhD in mathematics from Brigham Young University.
 
Tom Kooij
 
Kenneth Lyons
University of California, Davis
 
Eric Ma
MIT
 
Michael McKerns
UQ Foundation
Mike has been a research scientist at Caltech since 2002, and is co-founder of the UQ Foundation, a non-profit for the advancement of predictive science. Mike is the author several python packages, including mystic (highly-constrained non-convex optimization and uncertainty quantification), pathos (parallel graph management and execution in heterogeneous computing), and dill (serialize all of python). His software is the backbone of several research projects on risk analysis and predictive science, and is leveraged by several third-party packages in machine learning and parallel computing.
 
Claire McQuin
Broad Institute
Claire McQuin is a software engineer at the Broad Institute, where she works on the popular CellProfiler package, and interacts with scikit-image on a daily basis. She recently presented a well-received tutorial on image segmentation and 3D data analysis in Python at the ImageXD 2017 workshop, held at the University of Washington's e-Science Institute.
 
Aaron Meurer
University of South Carolina, SymPy
Aaron Meurer is a research scientist at the University of South Carolina in the ERGS research group. He is also the lead developer for the SymPy project.
 
Jason Moore
PyDy and SymPy
 
Andreas Mueller
Columbia University
I'm a lecturer at the Data Science Institute at Columbia University and author of the O'Reilly book "Introduction to machine learning with Python", describing a practical approach to machine learning with python and scikit-learn. I am one of the core developers of the scikit-learn machine learning library, and I have been co-maintaining it for several years. I'm also a Software Carpentry instructor. In the past, I worked at the NYU Center for Data Science on open source and open science, and as Machine Learning Scientist at Amazon. You can find my full cv hereMy 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.
 
Dillon Niederhut
Enthought
Dillon Niederhut holds a Ph.D. in Anthropology from the University of California at Berkeley. His graduate research was in computational semantics and advanced neuroimaging applications, and he taught graduate-level classes in R and Python. Prior to joining Enthought, Dillon developed heterogeneous processing and analytics pipelines for Berkeley's Data Lab. Outside of the office, he contributes to several open-source initiatives, including Mozilla Science Lab, Bayes Impact, and Open Austin.
 
Matthew Rocklin
Continuum Analytics
Matthew is a computational scientist at Continuum Analytics and full time open source developer within the scientific python ecosystem. He holds a PhD in Computer Science from the University of Chicago and undergraduate degrees in Mathematics and Physics from the University of California at Berkeley. His research crosses numerical linear algebra, computer algebra, and distributed systems. He builds libraries for out-of-core and distributed computing that target non-expert users.
 
Ben Root
Atmospheric and Environmental Research, Inc/Matplotlib
Ben Root is a member of the Matplotlib development team. Ben works as a scientific programmer using Python for Atmospheric and Environmental Research, Inc. He has written a book, "Interactive Applications with Matplotlib", and has given multiple presentations in the past, particularly the O'Reilly webinar, "Introduction to the SciPy ecosystem".
 
Philipp Rudiger
Continuum Analytics
Philipp works on developing open source and client specific software solutions for data management, visualization and analysis at Continuum Analytics and is the co-creator of Holoviews. Additionally, Philipp is interested in computational modeling of the brain and is currently still working on completing his PhD in the field. Philipp's main research area is in understanding the mammalian visual system through computational modeling. In particular, his research explores how cortical circuits self-organize through activity dependent processes, encode the visual statistics of the environment and give rise to the functional properties of the cortex.
 
Skipper Seabold
 
Chiranth Siddappa
 
Kurt Smith
HomeAway
Kurt Smith has a breadth of experience at the interface between programming languages, data science, machine learning, and HPC. While at Enthought and Continuum Analytics he provided expert Python consulting and training for clients in Oil & Gas, financial services, and national labs. A Cython contributor, Kurt is the author of "Cython" with O'Reilly Media, and has developed several in-depth Cython courses and tutorials. Kurt currently works for HomeAway as a Research Data Scientist.
 
Jean-Luc Stevens
Continuum Analytics
 
Bryan Van de Ven
Continuum Analytics
Bryan studied undergraduate Computer Science and Mathematics at UT Austin, and earned a Master's degree in Physics at UCLA. Currently he leads the technical effort for work done on the Bokeh project at Continuum Analytics. Previously, he has worked on feature detection and classification systems for submarine platforms, automated tools for financial risk modeling, and workflow optimization for fluid mixing simulations. He has also taught Basic, Advanced, and Scientific Python courses to more than 1500 students in the last four years.
 
Stéfan van der Walt
University of California, Berkeley
Stéfan van der Walt is a researcher at the Berkeley Institute for Data Science, UC Berkeley. He has been a part of the scientific Python developer community since 2006, and is the founder of scikit-image. He has taught Python in various capacities, including workshops at various scientific Python conferences, user groups, and summer schools.
 
Mark Wickert
University of Colorado
Dr. Mark Wickert is a full professor in the Electrical and Computer Engineering Department at the University of Colorado Colorado Springs. He received his BS and MS in Electrical Engineering from Michigan Technological University and his Ph.D. from Missouri University of Science and Technology. In 2013 he published the book Signals and Systems for Dummies, featuring the using of open source Python for signal modeling and simulation. His primary teaching and research interests are in communications and signal processing, such as digital communications, sensor networks, cognitive radio, software defined radio, digital signal processing, and statistical signal processing. He has worked as a consultant to many local companies in a variety signal processing topics, both commercial and government. He has a great passion for teaching, and for well over ten years has taught courses in real-time digital signal. Recently he started teaching real-time DSP using the ARM Cortex-M family. In his consulting work and teaching he enjoys using open-source design and analysis tools, such as Python via the Jupyter notebook.
 
Ben Zaitlen
Continuum Analytics
 

Conference Speakers and Authors

Erin Arai
Boston University
 
Lakshmi Navin Arbatti
University of San Francisco
 
Jaime Arias
Inria Grenoble Rhône-Alpes
 
Lorena Barba
George Washington University
Lorena A. Barba is an Associate Professor of Mechanical and Aerospace Engineering at the George Washington University in Washington, DC. Prof. Barba is an advocate of open-source software for science and open educational resources, and shares her courseware on iTunesU and YouTube. She is also interested in education technology, social learning and the recent spread of massively open online courses, as well as innovations in STEM education, including flipped classrooms and other forms of blended learning.Her research includes computational fluid dynamics, high-performance computing, computational biophysics and animal flight.
 
Will Barnes
Department of Physics and Astronomy, Rice University
 
James A. Bednar
Continuum Analytics
Dr. Jim Bednar is a Solutions Architect at Continuum Analytics. He is also an Honorary Fellow in the School of Informatics at the University of Edinburgh, Scotland.
 
Michael Beyeler
Department of Psychology, University of Washington, Institute for Neuroengineering (UWIN)
 
Geoffrey M. Boynton
Department of Psychology, University of Washington
 
Robert Bradshaw
 
Christian Brodbeck
New York University
 
Teon B Brooks
Stanford University
 
Eric Bruning
Texas Tech University
Eric Bruning is an Associate Professor of Atmospheric Science in the Department of Geosciences at Texas Tech University. He specializes in the relationship of storm electrification and lightning to the thermodynamics, microphysics, kinematics, and dynamics of thunderstorms. He couples lightning observations from numerous sources with weather radar datasets to explore how the fluid flows and turbulence in thunderstorms control where lightning begins and how far it travels within a thundercloud.
 
Matthias Bussonnier
IPython/Jupyter, University of California, Berkeley
Matthias is a member of the core IPython/Jupyter developer team. He also works full time for a postdoc on at the University of California, Berkeley. Matthias is working on integrating the notebook front end with real time collaboration tools like Google Drive to allow users to collaboratively edit notebook documents.
 
Abigail Cabunoc Mayes
 
Fernando Chirigati
New York University
Fernando Chirigati is a Research Assistant and Doctoral Candidate at the Department of Computer Science and Engineering at NYU Tandon School of Engineering. His research interests are mainly in the area of scientific data management, including provenance management and analytics, large-scale data analysis, computational reproducibility, and data visualization. He has received several awards, including the SIGMOD 2017 Most Reproducible Paper Award, the Pearl Brownstein Doctoral Research Award, and the Deborah Rosenthal MD Award. He is also the Reproducibility Editor of Elsevier's Information Systems Journal, and one of the architects of ReproZip, a tool that facilitates reproducibility of existing computational experiments. He has a BE in Computer and Information Engineering from the Federal University of Rio de Janeiro, Brazil.
 
Yongjun Choi
Michigan State University
I am in Professor Michael S. Murillo's group in the Computational Mathematics, Science and Engineering department at Michigan State University. My current research interest is computational plasma physics. More information on me can be found here: https://murillogroupmsu.com/dr-yongjun-choi/
 
Philippe Ciuciu
 
Alicia Clark
University of Washington
 
Natalia Clementi
George Washington University
 
Rowan Cockett
 
Roberto Colistete Jr
Physicist in theoretical Physics, Gravitation and Cosmology. Developer of mobile softwares for handheld computers and smartphones Python professor in university courses
 
Alex Companioni
 
Carlos Cordoba
 
Sylvain Corlay
QuantStack
Sylvain Corlay is an applied mathematician specializing in stochastic analysis and optimal control. He holds a PhD in applied mathematics from University Paris VI. As an open source developer, Sylvain contributes to Project Jupyter in the area of interactive widgets for the notebook, and is steering committee member of the Project. Besides Jupyter, Sylvain contributes to a number of scientific computing open-source projects such as bqplot, xtensor and ipyleaflet. Sylvain founded QuantStack in September 2016. Prior to founding QuantStack, Sylvain was a quant researcher at Bloomberg and an adjunct faculty member at the Courant Institute and Columbia University.
 
James Crist
Continuum Analytics
Jim Crist holds a Bachelors and a (tentative) Masters in Mechanical Engineering from the University of Minnesota. Whilst procrastinating on his thesis, he got involved in the scientific Python community. He is currently a software developer at Continuum Analytics.
 
Kenneth Dere
College of Science, George Mason University
 
Gautham Dharuman
Michigan State University
I am a graduate student in Professor Michael S. Murillo's group in the Computational Mathematics, Science and Engineering department at Michigan State University. My interest is in computational plasma physics with a focus on studying strongly coupled plasmas using large-scale molecular dynamics simulations. More information on me can be found here: https://murillogroupmsu.com/gautham-dharuman/
 
Hung Do
University of San Francisco
 
Michel Dojat
 
Denis Engemann
INRIA
 
Ione Fine
Department of Psychology, University of Washington
 
Florence Forbes
 
Gilbert Forsyth
George Washington University
Gil Forsyth is a graduate student at the George Washington University in Washington, D.C., studying mechanical engineering and computational fluid dynamics. He is a contributor to xonsh and a proud open-source advocate. With Professor Lorena Barba, he helped create and teach GW's first MOOC: Practical Numerical Methods with Python. He was awarded Outstanding Graduate Teaching Fellow of the year for 2014 by the BU College of Mechanical Engineering
 
Patricia Francis-Lyon
University of San Francisco
 
Aina Frau-Pascual
 
Jonathan Frederic
 
Michelle Gill
Metis
Michelle Gill is a Senior Data Scientist at Metis, where she teaches quarterly bootcamps and conducts corporate training focused on data science, machine learning, big data, and related technologies. Her career as a data scientist has spanned from basic research to management consulting. As a scientist at the National Cancer Institute, she developed machine learning algorithms and software that increased experimental throughput up to 10X. Michelle was also a consultant for The Boston Consulting Group, where she advised clients in industries ranging from the pharmaceutical to financial services on strategic growth and organizational streamlining. She has a Ph.D. in Molecular Biophysics & Biochemistry from Yale University and completed a postdoctoral fellowship at Columbia University focused on elucidating mechanisms of the cancer pathway. Outside of work, Michelle enjoys running, watching college basketball, wine, and tweeting (@modernscientist).
 
George Githinji
 
Nathan Goldbaum
University of Illinois
Postdoctoral researcher, National Center for Supercomputing Applications * Core contributor to yt, a python toolkit for analyzing and visualizing astrophysics simulation data * Controbutor to Enzo, an open source cosmological hydrodynamics code * Research focuses on galaxy evolution, with a focus on the state of the global ISM and star formation Ph.D. 2015, University of California Santa Cruz in Astronomy & Astrophysics
 
Gerard Gorman
Imperial College London, UK
 
Anton Gorshkov
Intel Corporation
Anton Gorshkov works at Intel for 3 years as software development engineer in Path-finding team. His main activity is performing of applied research projects in the area of technical computing, analyzers and runtimes. Anton has a PhD degree in the field of Computer Science. LinkedIn: https://www.linkedin.com/in/antongorshkov/
 
Alexandre Gramfort
INRIA
Alexandre Gramfort is researcher at INRIA and formerly Assistant Professor at Telecom ParisTech, Université Paris-Saclay, in the image and signal processing department from 2012 to 2017. His field of expertise is signal and image processing, statistical machine learning and scientific computing applied primarily to functional brain imaging data (EEG, MEG, fMRI). His work is strongly interdisciplinary at the interface with physics, computer science, software engineering and neuroscience. He is a core developer of the Scikit-Learn machine learning software (http://scikit-learn.org) since 2010 and at the origin of the MNE-Python software (http://martinos.org/mne/) now used and developed across many labs worldwide. He started also the PySurfer package and contributed to various neuroscience Python packages (nilearn, nibabel).
 
Brian Granger
Cal Poly State University, Project Jupyter
Brian is an Associate Professor of Physics and Data Science at Cal Poly State University in San Luis Obispo, CA. He is a leader of the IPython project, co-founder of Project Jupyter and is an active contributor to a number of other open source projects focused on data science in Python. He is a board member of the NumFOCUS Foundation and a faculty fellow of the Cal Poly Center for Innovation and Entrepreneurship.
 
Klaus Greff
IDSIA, USI, SUPSI
 
Shane Grigsby
Cooperative Institute for Research in Environmental Sciences (CIRES)
Shane is a Ph.D candidate in Geography at the University of Colorado, Boulder, where he is a research analyst at the Cooperative Institute for Research in Environmental Sciences (CIRES). His research includes developing algorithms to process remote sensing data, as well as using LiDAR and optical imagery to investigate meltwater processes and pathways on the Greenland ice sheet and their contribution to sea level rise. Previously, he worked for three years as an instructor to the NASA Student Airborne Research Program, and received his Masters from UCSB where he used thermal and hyperspectral data to estimate crop temperatures during the California drought.
 
Sean Gulick
University of Texas
Sean Gulick is interested in tectonic-climate interactions, the role of catastrophism in the geologic record and marine geophysical imaging at nested resolutions. His current projects include tectonic and climate interactions in the St. Elias Mountains and Surveyor submarine fan, geohazards and margin evolution of subduction and transform faulting in Alaska, Sumatra, and Japan, and the geologic processes and environmental effects of the Cretaceous-Paleogene Chicxulub meteor impact.
 
Melissa Gymrek
 
Matti Hamalainen
Massachusetts General Hospital, Harvard University
 
Jessica Hamrick
University of California, Berkeley
Jessica Hamrick is a Ph.D. candidate in the Psychology department at the University of California, Berkeley working with Tom Griffiths. Previously, she received her M.Eng. in Computer Science from MIT working with Josh Tenenbaum, and did research for a summer at Google DeepMind. Jessica's research lies at the intersection of cognitive science and machine learning and focuses on how people use imagination (or "mental simulation") to solve problems and reason about the world. In addition to research, Jessica is a core contributor to the IPython/Jupyter notebook, is the lead developer of the nbgrader project, and is a member of the Project Jupyter Steering Council.
 
Marcus Hanwell
Kitware
 
Joseph Hardin
Pacific Northwest National Laboratory
 
Lindsey Heagy
University of British Columbia
 
Joseph Hellerstein
University of Washington
Joe is a Senior Data Science Fellow at the eScience Institute and an Affiliate Professor of Computer Science, both at the University of Washington (Seattle), where his work focuses on bringing software and data skills to biological research. Previously, he managed the Computational Discovery Department at Google, was a Principal Architect at Microsoft, and founded/led the Adaptive Systems Department at the IBM Research.
 
Jonathan Helmus
 
Aaron Hill
Texas Tech University
 
Paul Hobson
Geosyntec Consultants
Water Resources Engineer with a bend towards statistics, spatial analysis, and numerical modeling
 
John Hoffman
Princeton University
PhD candidate in Astrophysics at Princeton University
 
Chris Holdgraf
University of California, Berkeley
 
Julie Hollek
Twitter
 
Patrick Huck
 
Kathryn Huff
University of Illinois at Urbana-Champaign
Dr. Kathryn D. Huff is currently an Assistant Professor in the Department of Nuclear, Plasma, and Radiological Engineering at the University of Illinois at Urbana-Champaign where she leads the Advanced Reactors and Fuel Cycles Research Group (arfc.npre.illinois.edu). She holds an affiliate faculty position with the National Center for Supercomputing Applications and is one of the University of Illinois' most recent Blue Waters Professors. She was previously a Postdoctoral Fellow with both the Nuclear Science and Security Consortium and the Berkeley Institute for Data Science at the University of California - Berkeley. She received her PhD in Nuclear Engineering from the University of Wisconsin-Madison in August 2013 and her undergraduate degree in Physics from the University of Chicago. Her current research focuses on modeling and simulation of advanced nuclear reactors and fuel cycles. She is currently the elected chair of the Fuel Cycle and Waste Management Division of the American Nuclear Society. Through leadership within the Hacker Within, Software Carpentry, SciPy, the Journal of Open Source Software, and other initiatives she strives to advocate for best practices in open, reproducible scientific computing.
 
Daniela Huppenkothen
NYU, USA
 
Horea-Ioan Ioanas
Institute for Biomedical Engineering, ETH and University of Zurich
Molecular Biologist and Neuroscientist using Python for data acquisition, processing, and analysis. Interested in neuroimaging, behavioural analysis, and database models.
 
Alexander Ivanov
 
Mainak Jas
Telecom ParisTech, Université Paris-Saclay
 
Amit Kapadia
Planet
 
Daniel Katz
 
Abby Kenyon
Texas Tech University
I am a Ph.D. student at Texas Tech University in Lubbock, TX under the advisement of Dr. Christopher Weiss. I completed my undergraduate degree at Valparaiso University in Valparaiso, IN with majors in Meteorology and Mathematics. I just recently received my masters degree last spring in Atmospheric Science at Texas Tech University. My thesis investigated how the visual characteristics of thunderstorm outflow varied with different thermodynamic deficits using a joint observational-modeling approach.
 
Roy Keyes
Arundo Analytics
Roy Keyes is a senior data scientist at Arundo in Houston, TX. By training, he is a radiation physicist, with a PhD focusing on medical applications of radiation and computational methods. Since 2012 he has worked as a data scientist at tech startups in San Francisco and Houston. He is a longtime user and promoter of Python.
 
Usman Khan
NUST, Pakistan
 
Jean-Rémi King
New York University
 
Joe Kington
 
David Koop
 
Manuel Krebber
RWTH Aachen University
Manuel Krebber is a computer science student at RWTH Aachen University on the verge of completing his Master degree. For his master thesis, he created the pattern matching library MatchPy for Python. He currently works as a research assistant at the RWTH HPAC group.
 
Navjot Kukreja
Imperial College London, UK
 
Meagan Lang
University of Illinois
 
Michael Lange
Imperial College London, UK
Michael Lange is a Research Associate at Imperial College London. His key research interests lie in the development and optimisation of computational science and simulation codes for high performance computing (HPC) architectures through the use of domain-specific languages (DSL) and automated code generation. He has published a range of papers and co-authored several software packages across multiple scientific disciplines, including seismic imaging, ocean modelling, finite difference and finite element computation, mesh adaptation and management, Lagrangian particle tracking and ocean ecology. He particularly focuses on developing high-productivity software environments for scientific computing that provide bespoke performance optimisation through high degrees of automation. Michael has extensive experience in code optimisation and modernisation and has been a contributor to a range of high-profile scientific software packages, such as the linear algebra library PETSc and the finite element automation framework Firedrake.
 
Shraddha Lanka
University of San Francisco
 
Eric Larson
University of Washington
 
John Leeman
John obtained bachelor's degrees in meteorology and geophysics from the University of Oklahoma in 2012, and a PhD in geoscience from Penn State in 2017. He has worked in research fields ranging from gas hydrate thermodynamics to SODAR and boundary layer instrumentation, and did his doctoral work in earthquake physics. John's software development experience includes work on the seafloor process simulator at Oak Ridge National Laboratory and telemetry analysis tools for NASA's Morpheus lunar lander project. The common thread amongst all of these projects was “the development of new tools and software to attack previously intractable problems.” John is now a software engineer at Unidata in Boulder, Colorado.
 
Jaakko Leppäkangas
Telecom ParisTech, Université Paris-Saclay
 
Mathias Louboutin
The University of British Columbia, Canada
 
Fabio Luporini
Imperial College London, UK
 
Johan Mabille
QuantStack
Johan Mabille is a scientific software developer specializing in high-performance computing in C++. He holds master's degree in computer science from Centrale-Supelec. As an open source developer, Johan coauthored xtensor and xeus , and is the main author of xsimd. Prior to joining QuantStack, Johan was a quant developer at HSBC.
 
Christopher Madan
 
Dhruv Madeka
New York University
Dhruv Madeka is a Quantitative Researcher at Bloomberg LP. His current research interests focus on Machine Learning, Data Visualization and Applied Mathematics. Having graduated from the University of Michigan with a BS in Operations Research and from Boston University with an MS in Mathematical Finance, Dhruv is part of one of the leading research teams in Finance, developing models, software and tools for users to make their data analysis experience richer.
 
Anton Malakhov
Intel Corporation
Anton has served as software development engineer at Intel Corporation for 11 years. He is experienced in multi-core (shared memory) parallelism, dynamic task scheduling, and concurrent containers thanks to 9 years at the Intel Threading Building Blocks (TBB) project (http://www.threadingbuildingblocks.org/). Now, Anton works for the Intel Distribution for Python project, researching ways to implement better parallelism support for the Python environment. LinkedIn: http://linkedin.com/in/antonmalakhov/
 
Tyler Martin
 
Ryan May
Unidata
Meteorologist by training, software engineer by training. I write software to make the lives of academic meteorologists much easier.
 
Michael McKerns
UQ Foundation
Mike has been a research scientist at Caltech since 2002, and is co-founder of the UQ Foundation, a non-profit for the advancement of predictive science. Mike is the author several python packages, including mystic (highly-constrained non-convex optimization and uncertainty quantification), pathos (parallel graph management and execution in heterogeneous computing), and dill (serialize all of python). His software is the backbone of several research projects on risk analysis and predictive science, and is leveraged by several third-party packages in machine learning and parallel computing.
 
Himanshu Mishra
IIT KGP, India
I am a third year undergraduate student at IIT Kharagpur pursuing Mathematics and Computing. I have participated in Google Summer of Code 2015 and 2016.
 
Kevin Moerman
 
Daniel Moyer
 
Michael S. Murillo
Michigan State University
I am a Professor in the Computational Mathematics, Science and Engineering department at Michigan State University. My research interests are computational plasma physics and agent based modeling. More information on me can be found here: https://murillogroupmsu.com/dr-michael-murillo/
 
David Nicholson
Emory University
I am a neuroscientist at Emory University in Atlanta, Georgia. I work in Sam Sober's lab in the Biology department. We study songbirds as a model system to understand how the brain learns and produces vocalizations. My thesis project focuses on figuring out what parts of the brain connect with each other, using standard techniques and newer viral methods. I also use machine learning to automate processes in the lab. For that I write code in Python, Matlab, occasionally Java/C/Javascript
 
Kyle Niemeyer
Oregon State University
Kyle Niemeyer is an Assistant Professor in the School of Mechanical, Industrial, and Manufacturing Engineering at Oregon State University. He received a PhD in Mechanical Engineering from Case Western Reserve University. His research interests include computational modeling of combustion and fluid flows, high-performance computing, and methods to improve openness and reproducibility in those fields. Kyle is on the editorial boards of the Journal of Open Source Software (JOSS), Journal of Open Research Software (JORS), and The Journal of Open Engineering (TJOE), and serves on the steering committee of engrXiv. More information and musings by Kyle can be found at https://niemeyer-research-group.github.io and @kyleniemeyer.
 
Logan Page
 
Daniil Pakhomov
Johns Hopkins University
 
Chris Parmer
Chris Parmer is a co-founder of Plotly and Plotly's Chief Product Officer.
 
Sam Penrose
Sam Penrose loves how working with data at scale for Mozilla brings out the power and beauty of mathematics. Previously he helped Industrial Light and Magic bring the power and beauty of giant robots out to movie screens everywhere.
 
Thomas Perret
 
Dmitry Petrov
 
Pjotr Prins
 
Min Ragan-Kelley
IPython/Jupyter
Min has been a core contributor to Jupyter and IPython since 2006. He also maintains the PyZMQ messaging library.
 
Karthik Ram
 
Rémi Rampin
New York University
Rémi Rampin is a Research Engineer at NYU Tandon School of Engineering, where he has been maintaining VisTrails, a scientific workflow and provenance management system, and developing ReproZip, a software for creating reproducible packages of experiments and environments.
 
John Readey
 
Andrew Reid
NIST
Computational materials scientist and HPC operations guy, with a background in physics.
 
Matthew Rocklin
Continuum Analytics
Matthew is a computational scientist at Continuum Analytics and full time open source developer within the scientific python ecosystem. He holds a PhD in Computer Science from the University of Chicago and undergraduate degrees in Mathematics and Physics from the University of California at Berkeley. His research crosses numerical linear algebra, computer algebra, and distributed systems. He builds libraries for out-of-core and distributed computing that target non-expert users.
 
Ariel Rokem
eScience Institute, University of Washington
 
Philipp Rudiger
Continuum Analytics Inc.
Philipp works on developing open source and client specific software solutions for data management, visualization and analysis at Continuum Analytics and is the co-creator of Holoviews. Additionally, Philipp is interested in computational modeling of the brain and is currently still working on completing his PhD in the field. Philipp's main research area is in understanding the mammalian visual system through computational modeling. In particular, his research explores how cortical circuits self-organize through activity dependent processes, encode the visual statistics of the environment and give rise to the functional properties of the cortex.
 
Jacob Schreiber
University of Washington
Jacob Schreiber is a graduate student and NSF IGERT Big Data fellow at the University of Washington, where he studies how to crunch massive data sets to solve problems arising in genome science. In his spare time he is a core developer for scikit-learn and the author of pomegranate.
 
Scott Sievert
University of Wisconsin–Madison
A grad student at UW–Madison studying optimization and machine learning. In my free time I enjoy skiing and sailing.
 
Sam Skillman
Descartes Labs
 
Peter Skipper
Civis Analytics
I'm a statistician who loves all things Python, working with Bayesian hierarchical models, convolutional neural nets, and propensity matching.
 
Arfon Smith
 
Vicky Steeves
New York University
Vicky Steeves is the Librarian for Research Data Management and Reproducibility, a dual appointment between New York University Division of Libraries and NYU Center for Data Science. In this role, she works supporting researchers in creating well-managed, high quality, and reproducible research through facilitating use of tools such as ReproZip.
 
Jean-Luc Stevens
Continuum Analytics
 
Hussain Sultan
AQN Strategies
 
Tracy Teal
Data Carpentry
 
Andrew Therriault
City of Boston
Andrew Therriault joined the City of Boston as its first Chief Data Officer in 2016, after serving as Director of Data Science for the Democratic National Committee. He received his PhD in political science from NYU in 2011 and completed a postdoctoral research fellowship at Vanderbilt, and more recently served as editor of "Data and Democracy: How Political Data Science is Shaping the 2016 Elections" (O'Reilly Media). Therriault leads Boston’s Citywide Analytics Team, a group that is a nationally-recognized leader in using data science to improve city operations and make progress in critical areas such as public safety, education, transportation, and health.
 
Chloe Tseng
Twitter
Chloe Tseng is a Senior Data Analyst at Twitter, where she turns complex statistics and data into a story to drive business decisions. Deeply passionate about limiting gender inequality, she is the co-founder of She Talks Data, a non-profit organization that creates an intimate environment to drive authentic dialogue and provides technical and leadership events to support women with skills needed for professional advancement. She loves visualizing data to increase awareness and understanding of important social causes, and founded Viz for Social Good, a community that promotes social good through data visualization.
 
Gaurika Tyagi
University of San Francisco
 
Michail Tzimas
West Virginia University
 
Leonardo Uieda
Department of Geology and Geophysics, University of Hawaii at Manoa, USA, Faculdade de Geologia, Uni
I'm a professor of geophysics at the Universidade do Estado do Rio de Janeiro (UERJ), Brazil. Currently, I'm on leave doing a postdoc at the University of Hawaii to build Python wrappers for the Generic Mapping Tools. I work with inverse problems in geophysics, particularly in potential field methods, and develop open-source software for science.
 
Marijn van Vliet
Aalto University
 
Jake VanderPlas
UW eScience Institute
 
Gaël Varoquaux
INRIA
Gaël Varoquaux is an INRIA faculty researcher working on data science for brain imaging in the Neurospin brain research institute (Paris, France). His research focuses on modeling and mining brain activity in relation to cognition. Years before the NSA, he was hoping to make bleeding-edge data processing available across new fields, and he has been working on a mastermind plan building easy-to-use open-source software in Python. He is a core developer of scikit-learn, joblib, Mayavi and nilearn, a nominated member of the PSF, and often teaches scientific computing with Python using the scipy lecture notes.
 
Jan Warnking
 
Wendy Wei
 
Paul Wessel
Department of Geology and Geophysics, University of Hawaii at Manoa, USA
 
Chris White
Capital One
 
Carol Willing
 
Terry Wilmarth
Terry Wilmarth is a software development engineer at Intel Corporation for 8 years. She has been the OpenMP runtime architect at Intel for the past year, and working on the OpenMP runtime team for 5 years. Before that she worked on TBB and Flow Graph Analyzer (FGA) projects at Intel. Her PhD work was in high performance computing with Charm++.
 
Weixiang Yu
 

Poster Presenters and Authors

Sameera Abeykoon
Brookhaven National Laboratory
Sameera Abeykoon works as a Research Associate at the BNL’s Computational Science Initiative and a member of Data Acquisition, Management and Analysis group member at BNL, National Synchrotron Light Source II (NSLS-II). Her current research is focused on developing a suite of data analysis tools and streaming data analysis pipelines (Scikitbeam project https://github.com/scikit-beam/scikit-beam) to extract scientifically relevant information from high-throughput multidimensional X-ray data collected at the beamlines of NSLS-II. Sameera completed her M.Sc. and Ph.D. degrees at the University of Houston.
 
Arman Akilic
National Synchroton Light Source-II, BNL
 
Daniel Allan
Brookhaven National Lab
 
Dan Barsever
Department of Cognitive Sciences, UC Irvine
 
Kevin Beam
 
Oliver Beckstein
Arizona State University
 
Jean Bilheux
Oak Ridge National Laboratory
 
Christopher S. Bretherton
University of Washington
 
Mary J. Brodzik
 
Lori Burns
 
Staurt Campbell
National Synchrotron Light Source-II, BNL
 
Thomas Caswell
Brookhaven National Laboratory
 
Emily Chao
 
Robert Cohn
Intel Corporation
 
Roberto Colistete Jr
Physicist in theoretical Physics, Gravitation and Cosmology. Developer of mobile softwares for handheld computers and smartphones Python professor in university courses
 
Scott Collis
Argonne National Laboratory, The University of Chicago
 
Andrew Colson
 
Daniel da Silva
Daniel da Silva is a scientific software engineer contractor at NASA Goddard Spaceflight Center in Maryland, working in global warming remote sensing and in-situ space weather measurement. He performs data analysis and designs operational systems using Python on a daily basis. Daniel has contributed 11+ contributions to the NumPy and SciPy projects, including code for a new masked array function, additional tests, and bug fixes.
 
Georgios Detorakis
Department of Cognitive Sciences, UC Irvine
 
Amanda Ernlund
I am a Ph.D. graduate student at New York University Medical Center. I work on cancer genomics with a focus on bioinformatics and the use of computational tools to analyze large datasets.
 
David Fenyo
 
Ricardo Ferraz Leal
ORNL
I have an MsC in Computer Engineering and a PhD in Physics. I have worked in private companies and Research Institutes. I have built and designed software architectures, led technical implementations of large scale systems and developed scientific software. I joined the Oak Ridge National Institute a couple of years ago where I build algorithms to analyze Neutron Scattering Data and develop Responsive Web Design applications to view and interpret those data.
 
Elliot Hallmark
Asuragen Inc
Elliot received a Bachelors of Science in physics at Humboldt State University in 2007. Shortly after that he discovered Python while trying to automate boring tasks in an office job. He then went on to work on projects in non-imaging optics, game engines, and websites among other things he finds fascinating. He is currently a developer in computational biology at Asuragen Inc in Austin Tx.
 
Molly Hardman
BSc Physics and Mathematics, MS Aerospace Engineering, Senior Associate Scientist at the National Snow and Ice Data Center, CIRES, University of Colorado, Boulder
 
Ingo Heimbach
 
Brian Helba
 
Robert Jackson
Argonne National Laboratory
Bobby Jackson is a postdoctoral researcher at Argonne National Laboratory studying thunderstorms using Doppler radars. His research interests pertain to the vertical motions inside thunderstorms and how they relate to meteorological conditions in the Tropics. His expertise includes the dynamics and microphysics of thunderstorms and ice clouds, as well as over a decade of experience in programming and software development in several languages, including Python. Bobby Jackson obtained his Ph.D. at the University of Illinois at Urbana-Champaign in Atmospheric Sciences studying the microphysical properties of cirrus clouds and estimating uncertainties in ice measurements. https://www.linkedin.com/in/robert-jackson-bab4ba54/
 
Mahzad Khoshlessan
Arizona State University
 
John Leeman
Unidata
John obtained bachelor's degrees in meteorology and geophysics from the University of Oklahoma in 2012, and a PhD in geoscience from Penn State in 2017. He has worked in research fields ranging from gas hydrate thermodynamics to SODAR and boundary layer instrumentation, and did his doctoral work in earthquake physics. John's software development experience includes work on the seafloor process simulator at Oak Ridge National Laboratory and telemetry analysis tools for NASA's Morpheus lunar lander project. The common thread amongst all of these projects was “the development of new tools and software to attack previously intractable problems.” John is now a software engineer at Unidata in Boulder, Colorado.
 
Li Li
National Synchrotron Light Source-II, BNL
 
Theodore Lindsay
 
Anton Malakhov
Intel Corporation
Anton has served as software development engineer at Intel Corporation for 11 years. He is experienced in multi-core (shared memory) parallelism, dynamic task scheduling, and concurrent containers thanks to 9 years at the Intel Threading Building Blocks (TBB) project (http://www.threadingbuildingblocks.org/). Now, Anton works for the Intel Distribution for Python project, researching ways to implement better parallelism support for the Python environment. LinkedIn: http://linkedin.com/in/antonmalakhov/
 
Blake Marsh
Federal Reserve Bank of Kansas City
Blake Marsh is an economist at the Federal Reserve Bank of Kansas City. He joined the Banking Research department in July 2016. His research areas are commercial bank regulation and financial intermediation. His current research examines commercial real estate lending, syndicated corporate lending, and financial innovation. Mr. Marsh holds a B.A. in economics from The George Washington University and M.A. and Ph.D. degrees from American University. He previously held positions at the Board of Governors of the Federal Reserve System and in the mortgage industry. https://www.kansascityfed.org/people/blakemarsh
 
David Mashburn
Pluralsight, LLC
 
Ryan May
Unidata
Meteorologist by training, software engineer by training. I write software to make the lives of academic meteorologists much easier.
 
Brian McFee
 
Jeremy McGibbon
University of Washington
 
Michael Milligan
Minnesota Supercomputing Institute, University of Minnesota
Michael is Head of Application Development and a member of the Scientific Computing group at the Minnesota Supercomputing Institute. His background is in astronomical instrumentation and data analysis, but loves that the MSI gives him constant opportunities to jump into new fields and technologies. Recently he has been leading the MSI's Interactive Supercomputing initiatives, where JupyterHub has become an important component.
 
Narendra Mukherjee
Brandeis University
I am currently pursuing my PhD in Neuroscience in Brandeis University - I am interested in the behaviorally-relevant multi-scale dynamics of large populations of neurons in the brain. I study taste processing in rats, record from neural populations, and build probabilistic graphical models of their activity during behavior and learning. I leverage Python at every point of this process, from building hardware to run experiments to the analysis of large datasets of neural recordings.
 
Denis Nagorny
Intel Corporation
 
David Najera
 
Emre Neftci
Department of Cognitive Sciences, UC Irvine
 
Dillon Niederhut
Enthought
Dillon Niederhut holds a Ph.D. in Anthropology from the University of California at Berkeley. His graduate research was in computational semantics and advanced neuroimaging applications, and he taught graduate-level classes in R and Python. Prior to joining Enthought, Dillon developed heterogeneous processing and analytics pipelines for Berkeley's Data Lab. Outside of the office, he contributes to several open-source initiatives, including Mozilla Science Lab, Bayes Impact, and Open Austin.
 
Jasmine Otto
University of Illinois at Chicago
Applied maths student. Interested in procedural generation, algebraic and statistical optimization, rich visualization; agent-based modelling of complex biological systems at multiple scales; recurring fractals, symmetries, and rhymes.
 
Oleksandr Pavlyk
Intel Corporation
 
Mark Picel
Argonne National Laboratory
 
Geoffrey Poore
Union University
Geoffrey Poore is the creator of PythonTeX and maintains the minted package for LaTeX.
 
Jacob Schreiber
University of Washington
Jacob Schreiber is a graduate student and NSF IGERT Big Data fellow at the University of Washington, where he studies how to crunch massive data sets to solve problems arising in genome science. In his spare time he is a core developer for scikit-learn and the author of pomegranate.
 
Diego Tomazella
 
Nadia Udler
 
Floris Van Breugel
 
Kirstein van Dam
Computational Science Initiative, BNL
 
Peter Weir
 
Brendt Wohlberg
 
Pamela Wu
New York University
 
Xiuwen Zheng
University of Washington
 
Wenduo Zhou
Oak Ridge National Laboratory