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.

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

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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/

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

http://hugobowne.github.io/

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/

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.

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

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.

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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

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

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

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.

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/).

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.

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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.

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

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

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!

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.

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.

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.

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.

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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/

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

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.

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

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.

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".

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).

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.

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.

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

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)

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

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.

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.

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/

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.

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.

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.

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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.