2019 Speakers

Meet the speakers who make SciPy 2019 fascinating. 

To all our speakers - thank you. 

Meet our
Keynote Speakers
Meet our
Tutorial Presenters
Meet our
Speakers & Authors
Meet our
Poster Presenters
 
Keynote Speakers

Stuart Geiger is a staff ethnographer and a principal investigator at the UC-Berkeley Institute for Data Science. He studies the people, platforms, infrastructures, and institutions that support the production of knowledge, particularly in decentralized and open organizations, including free/open-source software development and scientific research. His work has examined topics including newcomer socialization, community governance, distributed collaboration, invisible work, burnout, career paths, and fairness, accountability, and transparency in machine learning. His Ph.D work at the UC-Berkeley School of Information studied the governance and moderation of Wikipedia, focusing on the social roles of software developers and data scientists. He is a methodological and disciplinary pluralist, integrating approaches from across the humanities, the qualitative and quantitative social sciences, and computer, information, and data science. His work has been published in venues including Computer-Supported Cooperative Work, American Behavioral Scientist, Information, Communication & Society, and Big Data & Society. Stuart is also an instructor with Software Carpentry and the core maintainer of AcademicPages, a GitHub Pages template for personal academic websites.

https://bids.berkeley.edu/people/r-stuart-geiger

Geiger

UC-Berkeley Institute for Data Science

Stuart

Rachel Thomas was selected by Forbes as one of “20 Incredible Women in AI”, earned her math PhD at Duke, and was an early engineer at Uber. She is co-founder of fast.ai, which created the “Practical Deep Learning for Coders” course that over 200,000 students have taken. Rachel is a popular writer and keynote speaker. Her writing has been read by over half a million people; has been translated into Chinese, Spanish, Korean, & Portuguese; and has made the front page of Hacker News 9x. She is on twitter @math_rachel and her website is http://www.fast.ai/about/#rachel

Thomas

University of San Francisco Data Institute

Rachel

Carol serves on Project Jupyter’s Steering Council and works as a Core Developer on JupyterHub and mybinder.org. She serves as a co-editor of The Journal of Open Source Education (JOSE) and co-authored an open source book, Teaching and Learning with Jupyter.

She is a member of Python’s inaugural Steering Council and a core developer of CPython. She’s a Python Software Foundation Fellow and former Director. With a strong commitment to community outreach, Carol co-organizes PyLadies San Diego and San Diego Python User Group.

Carol has an MS in Management from MIT and a BSE in Electrical Engineering from Duke University.

Willing

Willing Consulting

Carol

 
Tutorial Presenters

Hannah Aizenman is a member of the Matplotlib development and studies visualization as graduate student in Computer Science at The Graduate Center (CUNY). She is an adjunct at the City College of New York, where she is teaching Psychology undergraduates tech skills, including using Python in their research. She has also taught data analysis using Python to high school students in a summer REU, to graduate students and faculty primarily from the social sciences and humanities in a bootcamp, and to engineers in a freshman seminar.

Aizenman

City College of New York/bThe Graduate Center (CUNY)

Hannah

Lorena Barba has developed Python- and Jupyter-based courses and open learning modules for more than 5 years. She taught a two-day intense tutorial using the "CFD Python" learning module in Argentina, July 2013. She has also taught an on-campus engineering course in aerodynamics using the AeroPython learning module, now under review for the Journal of Open Source Education. http://lorenabarba.com

Barba

The George Washington University

Lorena

Becker

NVIDIA

Nick

Dr. James A. Bednar is a Senior Technical Consultant at Anaconda, Inc. He received multiple nominations for teaching awards over his 10-year career of lecturing at the University of Edinburgh (UK), and has published more than 50 scientific papers. He manages the open-source packages in the PyViz project, including Datashader, Param, ImaGen, and Colorcet.

http://homepages.inf.ed.ac.uk/jbednar/

Bednar

Anaconda, Inc.

James

Maarten is a freelance developer / consultant / data scientist working working mostly with Python, C++ and Javascript in the Jupyter ecosystem. His expertise ranges from fast numerical computation, API design, to 3d visualization. He has a Bachelor in ICT, a Master and PhD in Astronomy and likes to code and solve problems. His PhD research was on the field of galactic dynamics. He worked on the Gaia mission, combing astronomy and IT, to enable visualization and exploration of the large dataset this satellite will yield. Through the work on ipyvolume he has become one of the ipywidgets developers.

http://www.maartenbreddels.com

Breddels

Maarten Breddels

Maarten

Browne-Anderson

DataCamp

Hugo

Matthias Bussonier, at UC Merced, has been heavily involved in Project Jupyter from its early IPython days. He has given numerous talks on Jupyter. He has also been a strong welcoming presence in the community for new and experienced members.

https://github.com/Carreau/

Bussonnier

UC Merced

Matthias

Colin is a Data Scientist at Freebird. Colin is also a core contributor to PyMC3 and ArviZ and holds a PhD in Mathematics from Rice University.

Carroll

Freebird

Colin

Thomas Caswell is a staff scientist at NSLS-II at Brookhaven National Laboratory building software for experimental data acquisition, management, and analysis for synchrotrons. In this role he applies his training in physics (PhD '14, U. Chicago; BA '07, Cornell) to build software to empower scientists. He has been active in the SciPy ecosystem from 2012 and is currently the lead developer of Matplotlib and the release
manager for h5py

Caswell

Brookhaven National Laboratory

Thomas

Alexandre is passionate about transforming people and the work they do. He has taught the scientific Python stack and machine learning to hundreds of scientists, engineers, and analysts at the world’s largest corporations and national laboratories. His graduate research was in the field of hearing research, where he developed models of human speech perception. He holds a Ph.D. in electrical engineering and a M.Sc. in acoustics engineering from the Technical University of Denmark and a B.Eng. in electrical engineering from the Université de Sherbrooke.

Chabot-leclerc

Enthought

Alex

Chen

University of Virginia

Daniel

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 a 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.

http://quantstack.net

Corlay

QuantStack

Sylvain

Matt Craig is a Professor of Physics and Astronomy at Minnesota State University Moorhead, in western Minnesota. He started using python about six years ago to do data analysis on data from a small telescope the university owns. Jupyter notebooks seemed like a natural fit for new users; widgets make it even easier for them to get started. Since learning about widgets a few years ago he has used them to connect programming novices with high-quality scientific packages. He has taught a Computational Physics course that has evolved into a scientific python course, with roughly equal emphasis on pythonic programming, computational methods, and a survey of existing packages. In addition, he leads a group of 5-10 undergraduates in doing astronomical research and coding in python.

http://mwcraig.github.io

Craig

Minnesota State University Moorhead

Matt

Matt Davis is a software engineer on the Data Infrastructure team at Clover Health. The team is responsible for making data accessible to those who need it and keeping data flowing smoothly between sources and sites of use.

Matt been using Python to work with data in science and at startups since 2008, after getting degrees in Astronomy and Aerospace Engineering. He maintains some moderately popular open-source Python libraries, including SnakeViz and Palettable.


https://penandpants.com

Davis

Clover Health

Matt

Allen Downey is a professor of computer science at Olin College, and author of *Think Python*, *Think Stats*, *Think Bayes*, *Think DSP* and several other books published by O’Reilly Media and available under free licenses. He has taught tutorials at PyCon, SciPy, and other conferences.

Downey

Olin College

Allen


Xu Fei runs the [data literacy Meetup](http://meetu.ps/c/2vZns/6l57W/d) in Toronto and is a [Software and Data Carpentry certified instructor](https://software-carpentry.org/scf/members/).

Fei

Code Ocean

Xu

Gilbert Forsyth is a data scientist at Capital One and a contributor to and maintainer of xonsh. He has served as the SciPy Program Chair for the last 3 years and offered a popular tutorial on Numba at SciPy in 2016 and 2017.

Forsyth

Capital One

Gilbert

Gama Dessavre

NVIDIA

Dante

Josh Gordon works on the TensorFlow team at Google, and teaches Applied Deep Learning at Columbia University. He has over a decade of machine learning experience to share. You can find him on Twitter at https://twitter.com/random_forests.

Gordon

Google

Josh

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. 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.

https://jasongrout.org

Grout

Bloomberg

Jason

Deborah has done machine learning research at MIT, Harvard, and Google Brain. Her work in machine learning has spanned developing models of human perception to exploring medical data. She has been a teaching assistant for undergraduate classes at MIT, graduate classes at Harvard, and the Boston Python Workshop. Before working in machine learning, she did education research and taught in Cambodia as a Fulbright Scholar. She has spoken at PyTennessee, SciPy Conference, AI With the Best, QConNY, and PyCon US. She is excited about helping people to improve their data science projects by understanding their data better.

http://deborahhanus.com

Hanus

Sparrow

Deborah

As a student of Electrical Engineering & Computer Science at UC Berkeley, Patricia has contributed to Zulip, an open source chat client, and nbconvert, a Jupyter notebook utility that converts a Jupyter notebook to other file formats. While doing research at MIT, her data wrangling and analysis resulted in a peer-review publication. She regularly teaches programming and design to the robotics team that she mentors, ballroom dance to high school students, and basic computer skills to senior citizens. She has also spoken about her research at several regional conferences. She is excited to combine her skills in Jupyter with her love of movies to teach people data analysis!

Hanus

University of California, Berkeley

Patricia

Sebastian loves data analysis, programming, and teaching. As a student research assistant at MIT, he used Python, NumPy, Pandas, and Keras to wrangle gigabytes of voice data (stored as text) into a neural network to detect vocal trauma. As a research assistant at the University of Nebraska, he used Python, NumPy, and sklearn on text data for computer security. In his spare time, he collects and analyzes data to improve his minecraft civilization. He regularly teaches programming and design to the robotics team that he founded and basic computer skills to senior citizens. He is excited to help the tutorial attendees discover their own data-related passion projects.

Hanus

Massachusetts Institute of Technology

Sebastian

Before becoming a programmer, Veronica was a researcher with an eye for process improvement (she helped pick the Mars Curiosity Rover’s landing site!). She loves exploring the web and teaching, and speaks on building the tooling & docs you need and has co-taught a PyCon tutorial on using web-scraping and machine learning to predict Oscar winners. When she isn’t thinking about how the web can be better for developers, she enjoys blogging and snuggling as many cats as possible.

Hanus

@veronica_hanus

Veronica

Zac is a researcher at the Australian National University’s 3A Institute, building a new applied science to 'manage the machines' - AI, cyber-physical systems, and other new technologies.

He started using Python to analyse huge environmental datasets, and contributing to libraries like Xarray to make such analysis easier for all scientists. Now, as a maintainer of Hypothesis, Pytest, and Trio, Zac is still passionate about making it easy to write software you can understand and rely on - especially for models or ML tools where we can't know the correct answer in advance!

When not at a computer he can usually be found surrounded by books of all kinds, the Australian bush, or both.

Hatfield-Dodds

Australian National University

Zac

Dave Hoese graduated with a Bachelor’s degree in computer engineering in 2011 from the University of Wisconsin - Madison. After graduating he continued his work as a software engineer at the Space Science and Engineering Center (SSEC) at UW - Madison. His work involves writing software for researchers, forecasters, and the rest of the scientific community to make meteorological instrument data easier to find, use, and understand. At the SSEC Dave is part of teams, include the Community Satellite Processing Package (CSPP) team, that release open source applications like Polar2Grid, Geo2Grid, and SIFT. This work has lead to Dave being a core developer on various open source python packages like SatPy, VisPy, PyResample, and aggdraw among others.

Dave is a certified software carpentry instructor. He has helped teach scientific programming skills at multiple software carpentry workshops. In addition to these workshops, Dave has conducted tutorials on git at the SSEC to introduce his coworkers to git, gitlab, and github. Dave has started programmer brown bag meetings at the SSEC to have programmers update each other on their projects as well as introduce them to new programming libraries and concepts.

Hoese

University of Wisconsin - Madison, Space Science and Engineering Center

David

Kraus

NVIDIA

Keith

Ravin Kumar is a data consultant at Carbon IT Services. In the past Ravin has worked at companies such as SpaceX analyzing data to improve internal operations. Ravin has also taught data courses through University of Southern California extension school. Ravin is a core contributor to ArviZ and a contributor to PyMC.

https://arviz-devs.github.io/arviz/

Kumar

ArviZ

Ravin

John Leeman received bachelors degrees in meteorology and geophysics from the University of Oklahoma and a PhD in geoscience from Penn State. He now works as a software engineer at Unidata, a community service organization serving university partners with meteorological data and software tools. John has been using Python since 2008 and now works full time on Unidata’s open source tools MetPy and Siphon - not only as a software developer, but as a trainer and educational content developer. John has been a teaching assistant for three undergraduate courses, developed a graduate course from scratch and co-taught it (content and video available http://tge.geoscience.tech/en/latest/), and has helped with the development of Unidata’s Python training materials (https://unidata.github.io/unidata-python-workshop/). John and Ryan have taught ten Python workshops in the last two years. John is a software carpentry instructor and also develops a weekly “MetPy Monday” training post or video on the Unidata developer’s blog (https://www.unidata.ucar.edu/blogs/developer/).

http://www.leemangeophysical.com

Leeman

Leeman Geophysical LLC

John

Eric is a data scientist at the Novartis Institutes for Biomedical Research. There, he conducts biomedical data science research, with a focus on using Bayesian statistical methods in the service of making medicines for patients. Prior to Novartis, he was an Insight Health Data Fellow in the summer of 2017, and defended his doctoral thesis in the spring of 2017.

Eric is also an open source software developer, and has led the development of nxviz, a visualization package for NetworkX, and pyjanitor, a clean API for cleaning data in Python. In addition, he has made contributions to a range of open source tools, including PyMC3, matplotlib, bokeh, and CuPy.

His personal life motto is found in the Luke 12:48.

Ma

Novartis Institutes for Biomedical Research

Eric

Ryan May received his bachelors, masters, and doctorate in meteorology from the University of Oklahoma. He now works as a software engineer and Python team lead at Unidata, a community service organization providing university partners with meteorological data and software tools. Ryan has been using Python since 2006, starting out as a way to avoid studying for a Ph.D. qualifying exam; since then he has become part of the matplotlib core development team as well as a member of the CartoPy steering committee. While at Unidata, Ryan has taught 19 Python workshops and short courses, including 5 in the last year; he is also a software carpentry instructor. Ryan also works full time on Unidata’s MetPy and Siphon libraries. For recordings of the workshop, see: https://www.youtube.com/watch?v=7zmvJPB-_Zo&list=PL3W8LGk2BcKleDCL-Mmv9ueNtVoPVQI0y

May

Dopplershift LLC

Ryan

Aileen is a software engineer and data analyst with a data background that runs the gamut from experimental physics to healthcare startups to finance. She speaks frequently at industry conferences, and she has given talks and tutorials around the world on the many challenges of time series analysis. She is the author of the forthcoming O'Reilly title, "Practical Time Series Analysis". Aileen has a range of teaching experience, including conducting tutorials at several international Python and machine learning conferences. She has lectured in a variety of undergraduate and graduate level courses while a graduate student at Columbia and Yale universities. She is comfortable presenting machine learning and programming topics to audiences of both small and large sizes.

Nielsen

Skillman Consulting

Aileen

Juan Nunez-Iglesias is a Research Fellow and CZI Imaging Software Fellow at Monash University in Melbourne, Australia. He is a core developer of scikit-image and has taught scientific Python at SciPy, EuroSciPy, the G-Node Summer School, and at other workshops. He is the co-author of the O'Reilly title "Elegant SciPy".

Nunez-Iglesias

Monash University

Juan

Chandrasekhar Ramakrishnan is a programmer and data scientist with over 20 years of experience developing software solutions. He studied mathematics at the University of California, Berkeley (B.A. 1997) and Media Arts and Technology at the University of California, Santa Barbara (M.A. 2003).

Ramakrishnan

ETH Zurich

Chandrasekhar

Martin Renou is a Scientific Software Developer at QuantStack. Prior to joining QuantStack, Martin also worked as a Software developer at Enthought. He has a Master’s degree from the French Aerospace Engineering School ISAE-Supaero, with major in autonomous systems and programming. As an open source developer, Martin has worked on a variety of projects, from numerical analysis libraries in C++ such as xtensor and xframe, to visualization libraries in Python and JavaScript such as ipyleaflet and ipywebrtc.

Renou

QuantStack

Martin

Sergio Rey is Professor in the School of Public Policy and Founding Director of the Center for Geospatial Sciences at UCR. Rey’s research interests focus on the development, implementation, and application of advanced methods of spatial and space-time data analysis. His substantive foci include regional inequality, convergence and growth dynamics as well as neighborhood change, segregation dynamics, spatial criminology and industrial networks. Recent and current research projects include geodemographic approaches to neighborhoods in space-time contexts (NSF), new methods for spatial distribution dynamics (NSF), an analysis of the relationships between spatial linkages and urban economic dynamics (EDA), flexible geospatial visual analytics and simulation technologies to enhance criminal justice decision support systems (NIJ), spatial analytical framework for examining community sex offender residency issues over space and time (NSF), and cyberGIS software integration for sustained geospatial innovation (NSF). Rey is the creator and lead developer of the open source package STARS: Space-Time Analysis of Regional Systems as well as co-founder and lead developer of PySAL: A Python Library for Spatial Analysis.

Rey

University of California, Riverside

Serge

Thomas Robitaille is the lead developer of the glue package for multi-dimensional linked data visualization, and is one of the coordinators and lead developers for the Astropy project. He obtained a PhD in Astrophysics from the University in St Andrews in 2008 and worked as a researcher at the Harvard-Smithsonian Center for Astrophysics and the Max Planck Institute for Astronomy. In 2016, he left research to work as a full-time scientific software developer, initially as a freelance consultant, and now as the co-founder of the scientific software development company Aperio Software. He taught a course entitled “Python for Scientists” at the University of Heidelberg for several years, and has given dozens of talks and tutorials about glue, the Astropy project, and open-source development in general.

http://www.thomasrobitaille.com

Robitaille

Aperio Software Ltd.

Thomas

Samapriya Roy (Sam Roy) is a Remote Sensing and Geospatial developer and analyst. During his PhD his work focused on coastal degradation and urban land use and land cover changes across global deltas. As a teaching assistant he has taught Introductory GIS and application courses for over 5 years to to over 400 students along with multiple open impact trainings and hackathons.(https://samapriya.github.io/projects/open-impact/). He is also a regular contributor to satellite data analysis pipelines and automations tools on PyPI (https://pypi.org/search/?q=%22Samapriya+Roy%22) and on GitHub (https://github.com/samapriya)

Roy

Planet

Samapriya

Philipp Rudiger is a Software Engineers at Anaconda, with PhDs in computational neuroscience, and is co-author of the Panel, hvPlot, HoloViews, GeoViews, and Param packages.

http://philippjfr.com

Rudiger

Anaconda, Inc.

Philipp

Sara Safavi is a software engineer helping bring daily earth imagery to the world at Planet. Based in Austin, TX, Sara frequently gives tech talks and teaches workshops centered around Python and/or geospatial data and tools. Her most recent experience speaking at the Women in Space Conference 2019 and teaching hands-on workshops at FOSS4G-NA 2018, SciPy 2018, and TX GIS Forum 2018.

Safavi

Planet

Sara

Anthony Scopatz was a tenure-track faculty member at the University of South Carolina. Additionally he has given talks and tutorials at previous SciPy & PyData conferences.

Scopatz

Quansight, LLC

Anthony

Julia Signell is a Software Engineer at Anaconda, and is the author of the intake-xarray package as well as numerous contributions to other PyViz and SciPy libraries.https://www.linkedin.com/in/julia-signell-8a948a88/

Signell

Anaconda, Inc.

Julia

Stephanie Stattel is a senior software developer at Bloomberg LP, where she is developing applications to improve financial professionals’ research and investment workflows. She is a San Francisco lead of the company’s global Bloomberg Women in Tech (BWIT) community.

Stephanie was a graduate teaching assistant at UCLA for introductory and advanced Physics courses (led lectures for up to 150 students, as well as more targeted weekly office hours) I was also a private tutor in Los Angeles employed by Launch Education, now incorporated into ArborBridge.

Stattel

Bloomberg

Stephanie

Jean-Luc Stevens is a Software Engineers at Anaconda, with PhDs in computational neuroscience, and co- author of the Panel, hvPlot, HoloViews, GeoViews, and Param packages.

Stevens

Anaconda, Inc.

Jean-Luc

Tingyu Wang is a senior doctoral student in the group of Prof. Barba, and he is a co-author of the "Land in Vector Spaces" tutorial.

Wang

The George Washington University

Tingyu

Warner

University of Arizona

Joshua

Wolf

University of Bristol

Levi

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 conference, user groups and summer programs.

van der Walt

University of California, Berkeley

Stéfan

 
Conference Speakers & Authors

Allard

Microsoft

Tania is a Microsoft developer advocate with vast experience in academic research and industrial environments. Her main areas of expertise are within data-intensive applications, scientific computing, and machine learning. She focuses on the improvement of processes, reproducibility, and transparency in research, data science, and artificial intelligence.
Over the last few years, she has trained hundreds of people on scientific computing, reproducible workflows, and ML models testing, monitoring and scaling and delivered,d talks on the topic worldwide.

She is passionate about mentoring, open source, and its community and is involved in a number of initiatives aimed to build more diverse and inclusive communities. She is also a contributor, maintainer, and developer of a number of open source projects and the Founder of Pyladies NorthWest UK.

Tania

Axelrod

Chan Zuckerberg Initiative

Shannon graduated with a degree in Computer Science from the University of California at Berkeley in 2011. She joined the Chan Zuckerberg Initiate after working as a full stack engineer at Pandora Media for several years. At CZI she is a member of the Science Tools and Platform team helping to develop open source tools for Biology research. In her spare time she’s been doing her best to catch up on all the Biology she’s missed since high school and learning about the intersection between engineering and science research.

Shannon

Bilbro

ICX Media, Inc.

Dr. Rebecca Bilbro is a data scientist, Python and Go programmer, teacher, speaker, and author in Washington, DC. She specializes in visual diagnostics for machine learning, from feature analysis to model selection and hyperparameter tuning, and has conducted research on natural language processing, semantic network extraction, entity resolution, and high dimensional information visualization. An active contributor to the open source software community, Rebecca enjoys collaborating with other developers on inclusive projects like Scikit-Yellowbrick - a pure Python visualization package for machine learning that extends scikit-learn and Matplotlib to support model selection and diagnostics. In her spare time, she can often be found either out-of-doors riding bicycles with her family or inside practicing the ukulele. Rebecca earned her doctorate from the University of Illinois, Urbana-Champaign, where her research centered on communication and visualization in engineering.

Rebecca

Breddels

Maarten Breddels

Maarten is a freelance developer / consultant / data scientist working working mostly with Python, C++ and Javascript in the Jupyter ecosystem. His expertise ranges from fast numerical computation, API design, to 3d visualization. He has a Bachelor in ICT, a Master and PhD in Astronomy and likes to code and solve problems. His PhD research was on the field of galactic dynamics. He worked on the Gaia mission, combing astronomy and IT, to enable visualization and exploration of the large dataset this satellite will yield. Through the work on ipyvolume he has become one of the ipywidgets developers.

http://www.maartenbreddels.com

Maarten

Cabunoc Mayes

Mozilla Foundation

Abigail Cabunoc Mayes, @abbycabs, is the Working Open Practice Lead at the Mozilla Foundation. Abby mobilizes and mentors leaders in the Internet Health movement by building and running programs like Mozilla Open Leaders. Before this, she was Lead Developer of the Mozilla Science Lab, transforming science on the web.

Prior to joining Mozilla, Abby worked as a bioinformatics software developer at the Ontario Institute for Cancer Research and at Michigan State University where she applied open source and machine learning to research problems. With a background in bioinformatics, open source and community organizing, she is fueling a culture of openness in research and innovation. Named in "100 awesome women in open source" by source{d}.

Photo CC-BY-NC-SA Faces of Open Source / Peter Adams

Abigail

Chen

Oracle

Gordon is a University of Michigan Wolverine, who has academic degrees in Applied Statistics, Software Engineering, and Economics. Using Data Science technologies to solve challenging business problems is Gordon's passion. His Data Science journey started in 2006 when he led a team of students to win the 1st prize, out of 10,000 competing teams, in the China Undergraduate Mathematical Contest in Modeling (CUMCM). In Gordon's career, he has worked on various business problems, including managing a team of data scientists to develop the core probabilistic classification model for Kinnser RiskPoint, a product that is earning millions of dollars in revenue per year. Gordon currently works as a Principal Data Scientist at Oracle.

Gordon

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 a 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.

http://quantstack.net

Sylvain

Downey

Olin College

Allen Downey is a professor of computer science at Olin College, and author of *Think Python*, *Think Stats*, *Think Bayes*, *Think DSP* and several other books published by O’Reilly Media and available under free licenses. He has taught tutorials at PyCon, SciPy, and other conferences.

Allen

Fan

Columbia University

Thomas J Fan is a scikit-learn core developer working at Columbia University’s Data Science Institute. He enjoys collaborating with the open source community to build tools for machine learning. On his free time, he watches superhero movies, reads research papers, and gives talks at meetups.

Thomas

Gommers

Quansight

Ralf has been deeply involved in the SciPy and PyData communities for over a decade. He is a core developer of NumPy, SciPy and PyWavelets, and has contributed widely throughout the SciPy ecosystem. Ralf has been the NumPy release manager for two years, and is currently the SciPy release manager and steering council chair. He served on the NumFOCUS Board of Directors from 2012-2018.

Currently, Ralf is Director of Quansight Labs, which aims to provide a home for a "PyData Core Team" which consists of developers, community managers, designers, and documentation writers who build open-source technology and grow open-source communities around all aspects of the AI and Data Science workflow projects. Previously Ralf has worked in industrial R&D, on topics as diverse as MRI, lithography and forestry.

Ralf

Hanus

Sparrow

Deborah has done machine learning research at MIT, Harvard, and Google Brain. Her work in machine learning has spanned developing models of human perception to exploring medical data. She has been a teaching assistant for undergraduate classes at MIT, graduate classes at Harvard, and the Boston Python Workshop. Before working in machine learning, she did education research and taught in Cambodia as a Fulbright Scholar. She has spoken at PyTennessee, SciPy Conference, AI With the Best, QConNY, and PyCon US. She is excited about helping people to improve their data science projects by understanding their data better.

http://deborahhanus.com

Deborah

Hanus

@veronica_hanus

Before becoming a programmer, Veronica was a researcher with an eye for process improvement (she helped pick the Mars Curiosity Rover’s landing site!). She loves exploring the web and teaching, and speaks on building the tooling & docs you need and has co-taught a PyCon tutorial on using web-scraping and machine learning to predict Oscar winners. When she isn’t thinking about how the web can be better for developers, she enjoys blogging and snuggling as many cats as possible.

Veronica

Hatfield-Dodds

Australian National University

Zac is a researcher at the Australian National University’s 3A Institute, building a new applied science to 'manage the machines' - AI, cyber-physical systems, and other new technologies.

He started using Python to analyse huge environmental datasets, and contributing to libraries like Xarray to make such analysis easier for all scientists. Now, as a maintainer of Hypothesis, Pytest, and Trio, Zac is still passionate about making it easy to write software you can understand and rely on - especially for models or ML tools where we can't know the correct answer in advance!

When not at a computer he can usually be found surrounded by books of all kinds, the Australian bush, or both.

Zac

Hossain

Plotly

Shammamah Hossain is a software engineer at Plotly, where she is part of the team that develops the Dash Bio library. Prior to her time at Plotly, she studied a joint major of physics and computer science at McGill University.

Shammamah

Ma

Novartis Institutes for Biomedical Research

Eric is a data scientist at the Novartis Institutes for Biomedical Research. There, he conducts biomedical data science research, with a focus on using Bayesian statistical methods in the service of making medicines for patients. Prior to Novartis, he was an Insight Health Data Fellow in the summer of 2017, and defended his doctoral thesis in the spring of 2017.

Eric is also an open source software developer, and has led the development of nxviz, a visualization package for NetworkX, and pyjanitor, a clean API for cleaning data in Python. In addition, he has made contributions to a range of open source tools, including PyMC3, matplotlib, bokeh, and CuPy.

His personal life motto is found in the Luke 12:48.

Eric

Nicholson

Emory University

David Nicholson (https://nicholdav.info/) is a neuroscientist at Emory University in Atlanta, Georgia. He works for the Prinz lab in the Biology department, developing brain-inspired continual machine learning algorithms as a member of a multi-university team on a DARPA project. He also works in applied machine learning in the area of animal vocalizations. In collaboration with Yarden Cohen, he developed a library to help researchers use neural networks for automated segmentation and annotation of vocalizations (https://github.com/NickleDave/vak). They have used this library to benchmark the first neural net architecture capable of accurately segmenting and labeling syllables in hundreds of hours of complex birdsong, such as that of the canary (https://github.com/yardencsGitHub/tweetynet). These projects began during his graduate studies in Sam Sober's lab at Emory, where his dissertation work showed that connections known to be important for learning motor skills in humans and other mammals are also found in regions of the songbird brain that are required to learn song. Lastly, David maintains several other Python packages and tools related to his research (more at https://github.com/NickleDave/MetaNickleDave).

David

Nunez-Iglesias

Monash University

Juan Nunez-Iglesias is a Research Fellow and CZI Imaging Software Fellow at Monash University in Melbourne, Australia. He is a core developer of scikit-image and has taught scientific Python at SciPy, EuroSciPy, the G-Node Summer School, and at other workshops. He is the co-author of the O'Reilly title "Elegant SciPy".

Juan

Preble

RTI International

Edward is a Research Data Scientist in RTI's Center for Data Science, where he applies machine learning, predictive modeling, text analytics, data visualization, and interactive reporting to solving problems in the social sciences, public health, and engineering sciences.

Edward

Robitaille

Aperio Software

Thomas Robitaille is the co-founder of Aperio Software, a company specializing on Scientific Software Development. He is the lead developer of the glue package for multi-dimensional linked data visualization, and is one of the coordinators and lead developers for the Astropy Project. Thomas obtained a PhD in Astrophysics from the University in St Andrews in 2008 and worked as a researcher at the Harvard-Smithsonian Center for Astrophysics and the Max Planck Institute for Astronomy. In 2016, he left research to work as a full-time scientific software developer, initially as a freelance consultant, before co-founding Aperio Software.

Thomas

Rosenthal

Rosenthal Data, LLC

Ethan Rosenthal is an independent data science consultant who specializes in building full stack machine learning products and advising startups on data strategy and vision. Prior to consulting, Ethan was the founding member of the Data team at Dia&Co where he led a team of data scientists, analysts, and engineers building data-driven applications involving recommender systems, logistics, computer vision, and more. Before Dia&Co, Ethan worked as a Data Scientist at Birchbox and earned a PhD in Physics from Columbia University building atomic-resolution microscopes to study superconductors. Outside of his day jobs, Ethan writes a technical data science blog, advises early career data scientists at Insight Data Science, and likes to get away from the computer and be active.

Ethan

Saul

Department of Mathematics and Statistics, Washington State University

Nathaniel Saul began the development of Scikit-TDA as a graduate researcher in Mathematics at Washington State University. Aided by his background in software development, his research focus has been on building tools to make Topological Data Analysis more approachable to the academic and industry communities.

Nathaniel

Schreiber

University of Washington

Jacob Schreiber is a fifth year Ph.D. student and IGERT big data fellow in the Computer Science and Engineering department at the University of Washington. His primary research focus is on the application of machine learning methods, specifically deep learning ones, to the massive amount of data being generated in the field of genome science. Additionally, he routinely contributes to the Python open source community as the core developer of pomegranate, a package for flexible probabilistic modeling, apricot, a package for data summarization for machine learning, and in the past as a core developer for the scikit-learn project. Future projects include graduating.

Jacob

Scopatz

Quansight, LLC

Anthony Scopatz was a tenure-track faculty member at the University of South Carolina. Additionally he has given talks and tutorials at previous SciPy & PyData conferences.

Anthony

Stephey

NERSC

Laurie Stephey is a postdoctoral fellow at NERSC (National Energy Research Supercomputing Center). She works with the Dark Energy Spectroscopic Instrument experiment to help optimize their Python-based data processing to run well on the NERSC supercomputers. Laurie learned Python in 2013 and has enjoyed using it ever since.

Laurie

Tahiri

UQAM

Nadia Tahiri, Ph.D. is a Postdoctoral Researcher in Machine Learning at UQAM. Her research interests are in the field of Deep Learning, particularly in classification understanding, preprocessing healthcare and medical images. Nadia obtained her doctorate degree from the University of Quebec at Montreal in 2018 with her thesis titled "Bioinformatics algorithms for consensus tree reconstruction and multiple super-trees". She is the recipient of several awards and scholarships. She is also interested in consumer and general behavior prediction problems.

Nadia

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 conference, user groups and summer programs.

Stéfan

 
Poster Presenters & Authors

Gajendra

KLS Gogte Institute of Technology, India

Mr. Gajendra Deshpande holds a masters degree in Computer Science and Engineering and working as Assistant Professor at the Department of Computer Science and Engineering, KLS Gogte Institute of Technology, Belagavi, Karnataka, India. He is pursuing Ph.D. under the guidance of Dr. S.A.Kulkarni at The National Institute of Engineering, Mysuru, India. He has a teaching experience of 11 years and Linux and Network Administration experience of one year. Under his mentor-ship teams have won Smart India Hackathon 2018 and Smart India Hackathon 2019 . He is Technical Director for Sestoauto Networks Pvt. Ltd. and Founder of Thingsvalley. His areas of Interest include Programming, Web Designing, Cyber Security, Artificial Intelligence, Machine Learning, Brain Computer Interface, Internet of Things and Virtual Reality. He has presented papers at NIT Goa, Scipy India 2017 IIT Bombay, JuliaCon 2018 London and Scipy India 2018 IIT Bombay.

Deshpande

Matthew

Southern Methodist University

Matthew is a Ph.D. candidate in physics at Southern Methodist University with research expertise in experimental high energy physics. He works as a member of the ATLAS collaboration as part of the effort to use the Higgs boson as a tool to discover physics beyond the standard model with experiments preformed at CERN's Large Hadron Collider (LHC) in Geneva, Switzerland. He is also one of the core developers of the statistical fitting library pyhf and a researcher with the Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP).

Feickert

Laura

Accenture Federal Services

Laura loves to open happiness every day; a data analytics professional with an insatiable curiosity, Laura started her career in intellectual property, working for 14 years at the US Patent and Trademark Office in many digital, technical communications and program management roles. After completing her MS in Data Science from Indiana University in 2018, Laura pivoted to this new field and began working in the Analytics practice at Accenture Federal Services in January 2019. Her passions include using technology to impact lives, hosting friends and neighbors and music.

Kahn

Mehmet

Eastern Mediterranean University

Mehmet Kunt is director of Traffic Education and Research Center and faculty member at the Civil Engineering Department of Eastern Mediterranean University. Kunt obtained his PhD. in 1995 in Transportation Engineering from the University of Texas at Austin, and holds B.S. degree in Civil Engineering and M.S. degree in Transportation Engineering from Middle East Technical University in Turkey and the University of Texas at Austin, respectively. Since 2009 Kunt is exploring ways to use Python both in research and education. Since 2010 he made presentations on the use of Python and its modules both in SciPy and EuroSciPy conferences.

Kunt

Geoffrey

Union University

Geoffrey Poore is the creator of PythonTeX and maintains the minted package for LaTeX (github.com/gpoore/). He uses Python and Jupyter notebooks extensively in teaching upper-level undergraduate physics.

Poore

Nadia

UQAM

Nadia Tahiri, Ph.D. is a Postdoctoral Researcher in Machine Learning at UQAM. Her research interests are in the field of Deep Learning, particularly in classification understanding, preprocessing healthcare and medical images. Nadia obtained her doctorate degree from the University of Quebec at Montreal in 2018 with her thesis titled "Bioinformatics algorithms for consensus tree reconstruction and multiple super-trees". She is the recipient of several awards and scholarships. She is also interested in consumer and general behavior prediction problems.

Tahiri

Gavin

Oak Ridge National Laboratory

I am a research scientist at the Oak Ridge National Laboratory near Knoxville, Tennessee. My current work is developing computational models to simulate the fast pyrolysis of biomass in fluidized reactors. This research is part of the Consortium for Computational Physics and Chemistry for the U.S. DOE Bioenergy Technologies Office. I am also involved in various battery simulation activities as part of the Computer Aided Engineering for Batteries project. As an enthusiastic developer, I organize the Knoxville CocoaHeads and KnoxPy programming groups.

Wiggins

Min Khant

Webster Univeristy

I am a senior student from Computer Science major. I am really interested in Data Science and mathematical computation using Python and other science-friendly languages. I had presented in PyCon 2018 in Bangkok and are planning to present in the SciPy conference this year. I am currently working on a project related to climate change and data analysis using Python as my main research.

Zaw

Institutional Sponsor

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