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2022 Speakers
Keynotes
Keynote Speakers
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Ben Blaiszik

University of Chicago

Ben Blaiszik is a research scientist at the University of Chicago and the Data Science and Learning Division at Argonne National Laboratory where he leads a number of projects that leverage Python to accelerate scientific research and to make large scale data and best in class machine learning models easily discoverable and usable. These include the NIST/CHiMaD Materials Data Facility, the DOE supported Data and Learning Hub for Science, and the NSF CSSI project Foundry. He is also a member of the founding council of the Materials Research Data Alliance, a group working to develop open, accessible, and interoperable materials data to fuel the Materials Genome Initiative.

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Enzo Ferrante

CONICET

Dr. Ferrante received his Systems Engineering degree from UNICEN University (Argentina), completed his PhD in Computer Sciences at Université Paris-Saclay and INRIA in Paris, France, and worked as a postdoctoral researcher at Imperial College London in the UK. He returned to Argentina in 2017, where he holds a permanent researcher position from the Argentina's National Research Council (CONICET). He leads the Machine Learning for Biomedical Image Computing group at the Research Institute for Signals, Systems and Computational Intelligence, sinc(i). In 2020 Dr. Ferrante received the Young Researcher Award from the National Academy of Sciences of Argentina, and the Mercosur Science & Technology Award for his scientific contributions in the area of AI for medical image computing. His research interests span both artificial intelligence and biomedical image analysis, with focus on deep learning methods.

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Peter Kalmus

NASA JPL / Caltech

Dr. Peter Kalmus is a Data Scientist at NASA's Jet Propulsion Laboratory. He is the recipient of NASA’s Early Career Achievement Medal and has over 100 peer-reviewed scientific publications. Peter started his career in astrophysics. He obtained a B.Sc. in physics from Harvard College and a Ph.D. in physics from Columbia University, and led searches for gravitational waves from magnetars and supernovae on behalf of the LIGO Scientific Collaboration as a Caltech postdoc. He switched fields into climate science in 2012 due to his mounting climate concern, joining JPL as a postdoc in the now-discontinued Climate Physics group, where he studied cloud and atmospheric processes and supported the AIRS team. Since being hired permanently at JPL in 2016, Peter has increasingly moved his research focus into biodiversity and ecological forecasting. He is currently the PI or Science PI on 3 ROSES projects in these areas, and he leads JPL’s Biodiversity Club. In addition, Peter continues his atmospheric science work as the PI on a new ROSES project to study changes in the severe convective thermodynamic environment in the “tornado alley” region of the US. Outside of JPL, Peter is also a well-known climate activist, the author of an award-winning book, “Being the Change: Live Well and Spark a Climate Revolution,” and a regular opinion contributor to The Guardian, the LA Times, and other publications.

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Megan Sosey

Space Telescope Science Institute

Megan Sosey is an engineer and scientist, working at the Space Telescope Science Institute for the last 24 years. She is currently leading the design, development, and delivery of the Data Management System that will process, archive, and serve to the astronomical community observations taken using the Nancy Grace Roman Space Telescope. She received her bachelor degrees in Physics and Astronomy from the University of Arizona. After starting at STScI she worked to earn a Masters in Computer Science from Loyola University of Maryland. During her career she has had the opportunity to collaborate with astronomers, archeologists, hardware engineers, software engineers, systems engineers, students, and Nobel Laureates. She has contributed code to multiple open source projects used throughout the astronomical community, and has had the privilege of being part of the Astropy Collaboration, Hubble Space Telescope, and James Webb Space Telescope missions, in a variety of capacities over the years.

Tutorial Presenters
Tutorial Presenters
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Anderson Banihirwe

CarbonPlan

Anderson works as a software/data engineer at CarbonPlan, a non-profit working on data science and policy issues surrounding carbon removal and climate solutions. He is an open-source software advocate and contributor. He helps maintain the Xarray, dask-jobqueue, and a few other packages/libraries within the scientific Python data ecosystem.

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James Bednar

Anaconda, Inc.

Jim Bednar is the Director of Custom Services at Anaconda, Inc. Dr. Bednar holds a Ph.D. in Computer Science from the University of Texas, along with degrees in Electrical Engineering and Philosophy. He has published more than 50 papers and books about the visual system, software development, and reproducible science. Dr. Bednar manages the HoloViz project, a collection of open-source Python tools that includes Panel, hvPlot, Datashader, HoloViews, GeoViews, Param, Lumen, and Colorcet. Dr. Bednar was a Lecturer and Reader in Computational Neuroscience at the University of Edinburgh from 2004-2015, and previously worked in hardware engineering and data acquisition at National Instruments.

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Youness Bennani

Bloomberg

Youness Bennani is a full stack software developer at Bloomberg. He works on developing a financial data analysis tool that relies on Jupyter and leverages the Bloomberg Terminal and its data. Youness was previously working as a data analyst for the Berkeley National Lab, developing statistical models for energy efficiency policy decisions. Youness holds a Master's degree in energy and environmental engineering.

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Eduardo Blancas

Ploomber

Eduardo Blancas is the Co-Founder and CEO of Ploomber, a Y Combinator-backed company developing tools to bridge the gap between interactive data work and production. Before that, he was a Data Scientist at Fidelity Investments, where he deployed the first customer-facing Machine Learning model for asset management. Eduardo holds an M.S. in Data Science from Columbia University and a B.S. in Mechatronics Engineering from Tecnológico de Monterrey.

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Hugo Bowne-Anderson

Outerbounds

Hugo Bowne-Anderson is Head of Developer Relations at Outerbounds, a company committed to building infrastructure that provides a solid foundation for machine learning applications of all shapes and sizes. He is also host of the industry podcast Vanishing Gradients. Hugo is a data scientist, educator, evangelist, content marketer, and data strategy consultant, with extensive experience at Coiled, a company that makes it simple for organizations to scale their data science seamlessly, and DataCamp, the online education platform for all things data. He also has experience teaching basic to advanced data science topics at institutions such as Yale University and Cold Spring Harbor Laboratory, conferences such as SciPy, PyCon, and ODSC and with organizations such as Data Carpentry. He has developed over 30 courses on the DataCamp platform, impacting over 500,000 learners worldwide through his own courses. He also created the weekly data industry podcast DataFramed, which he hosted and produced for 2 years. He is committed to spreading data skills, access to data science tooling, and open source software, both for individuals and the enterprise.

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Alex Bozarth

IBM

Alex is a Software Engineer and Jupyter Architect at the IBM Center for Open Source Data and AI Technologies (CODAIT), contributing to the Jupyter ecosystem. He serves on the JupyterLab Council and is a core committer on the Elyra project. He is also a PPMC for Apache Livy (Incubating).

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Jason Chambless

KBI Biopharma, Inc

Jason Chambless is a software developer at KBI Biopharma, Inc, a global biopharmaceutical manufacturing organization. He received his PhD in chemical and biological engineering in 2008 from Montana State University in Bozeman, MT. Jason has worked as a software developer since 2006, using languages from Fortran to C# to Python, to do everything from modeling industrial chemical reactors to building websites that track supply chain procurement.

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Deepak Cherian

National Center for Atmospheric Research

I am a physical oceanographer and open-source scientific software developer. I help maintain Xarray, and other projects in the Xarray ecosystem (cf-xarray, flox, xgcm).

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Naty Clementi

Coiled

Naty Clementi is an Open Source Software Engineer at Coiled and is a contributor of Dask. Naty has presented versions of the Dask Tutorial in a local Women Who Code meetup (https://www.youtube.com/watch?v=ZKw7PdoS7YA&t=318s) and youtube streamings (https://www.youtube.com/watch?v=nHMcqEYZ5qY&t=488s).

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Matthew Craig

Minnesota State University Moorhead

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 several 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.

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Simon Cross

RIKEN

Things about myself that you can talk to me about if you feel like:

* I work full-time as a core developer of QuTiP for RIKEN.
* I help out with HPy, the new C API for Python.
* I founded PyConZA in 2012 and am still heavily involved.
* I've worked in data science, bioinformatics and radio astronomy.
* I've written some not terrible games for PyWeek.

I like hearing what others are excited enough about to devote a lot of their attention to.

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Martha Cryan

IBM

Martha is a software engineer at the IBM Center for Open Source Data and AI Technologies. She is a distinguished contributor on [JupyterLab](https://github.com/jupyterlab/jupyterlab) and a committer on [Elyra](https://github.com/elyra-ai/elyra).

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Itay Dafna

Bloomberg LP

Itay Dafna is a Software Engineer in Bloomberg’s San Francisco Engineering office. He is developing open source and proprietary data visualization libraries and tooling to help users explore, understand, and communicate complex relationships within their data. Itay joined Bloomberg in 2013, where he has previously held the roles of Quantitative Analytics Team Leader and Financial Engineer. Itay earned his MSc in Management from the London School of Economics, and has been awarded the Certificate in Quantitative Finance from the CQF Institute.

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Steven Diamond

Gridmatic

Steven Diamond is a research scientist at Gridmatic, an energy startup. He holds a Ph.D. in computer science from Stanford, where his research focused on domain-specific languages (DSLs) for optimization. He is the original developer of CVXPY, a widely used Python-embedded DSL for convex optimization. He has served as the primary instructor of Stanford's convex optimization course, and has run tutorials on convex optimization across the world. He has given many talks on CVXPY, including at SciPy18.

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Draga Doncila Pop

Monash University

I am currently a PhD student working on an open source interactive interface for cell segmentation and tracking optimisation. I work part time as a software engineer making contributions to open source software, and am a napari core developer.

I am passionate about scientific software, open source development and open research. I love sharing my knowledge with others and making software development accessible for all.

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Janos Gabler

University of Bonn

I am an Economist turned programmer and about to finish my PhD at University of Bonn. I love building complex models of human behavior to analyze policy relevant questions.

I have authored several open source Python packages. The most popular is estimagic, a library for numerical optimization and calibration of scientific models.

In my free time I build pizza ovens, bandsaws or furniture and enjoy long bike rides.

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Jennifer Glick

IBM Quantum

Jennifer Glick is a quantum applications researcher and technical lead of quantum prototypes at IBM Quantum where she researches, develops, and implements quantum algorithms and software that can address industry-relevant problems challenging to solve with today’s classical techniques. Jen is a contributor to the first demonstrations of Qiskit Runtime, a platform that enables execution of more complex quantum workloads. She is regularly involved in teaching quantum computing at community and industry events, including programming sessions at IBM THINK conferences, the Qiskit Global Summer School on Quantum Machine learning, and a tutorial on Qiskit Runtime at IEEE Quantum Week 2021. In 2020, she was selected for MIT Technology Review’s global 35 under 35 Innovators for her work on developing applications of quantum computing. Jen received her Ph.D. in physics from Michigan State University in 2017 and her B.S. in engineering physics from Colorado School of Mines in 2011.

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Perry Greenfield

STScI

Perry Greenfield got his Ph.D. in Physics from M.I.T. in Radio Astronomy studying the first discovered gravitational lens with the Very Large Array. He has been at the Space Telescope Science Institute for 36 years and is currently a Consulting Science Software Engineer. He and his group started using Python in 1998 and pioneered the use of Python in astronomy, being involved in key developments such as PyRAF, pyfits, numarray, matplotlib, and Astropy. Python plays a central role in the science software for the Hubble and James Webb Space Telescopes, and the future Nancy Grace Roman Space Telescope.

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Zac Hatfield-Dodds

Anthropic

Zac is the lead maintainer of the Hypothesis project, a PSF Fellow, and generally enjoys contributing to open-source communities. Earlier this year he moved from Australia to SF, where he works as a research engineer at https://anthropic.com, helping to build reliable, interpretable, and steerable AI systems.

When away from a computer - it happens! - Zac can often be found in the great outdoors, or relaxing with a good book and a block of dark chocolate.

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Scott Henderson

University of Washington eScience Institute

Scott is a research scientist at the University of Washington eScience Institute and Department of Earth and Space Sciences. He works on a number of NASA-funded projects to support open source software such as Xarray. Scott is excited about open science initiatives, scalable computing with large public satellite data archives, and living in Seattle, WA.

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Alexander Kaszynski

Ansys

Alex Kaszynski

Co-Creator of PyVista, incessant coder, and leader within Ansys to embrace open-source development and the Python ecosystem.

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Elijah Knaap

Center for Geospatial Sciences @ UC-Riverside

Eli Knaap is a research scientist and Associate Director of the Center for Geospatial Sciences at the University of California-Riverside, with interests in spatial data science, urban dynamics, and neighborhood effects. He is a core developer for the Python Spatial Analysis Library (PySAL) and QuantEcon

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Roni Kobrosly

DrFirst

I am a former epidemiology researcher who has spent about a decade employing causal modeling and inference. The bulk of my academic career was spent conducting data analyses to estimate the population-level effects of harmful environment exposures.

Since leaving the academic world, I've been loving my second life in the tech industry as a ML engineer, and more recently as the Head of Data Science at a medium-sized health tech company based in Washington DC. I love mentoring junior data folks and explaining the magic of data and modeling to a non-technical audience.

I'm also a contributor in the open-source community, being the author and maintainer of the causal-curve python package.

I make a very good scrambled eggs and hash brown breakfast. I mean really, really good. Really. 🍳

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Tetsuo Koyama

PyVista developers team

Interested in scientific computing and visualization with computer graphics.
Developer team member of PyVista.
Past experience as a speaker:
- [PyConJP 2019 speaker "Introduction to FEM Analysis with Python"](https://youtu.be/6JuB1GiDLQQ)
- [PyConJP 2020 speaker "How to plot unstructured mesh file on Jupyter Notebook"](https://youtu.be/X3Z54Kw4I6Y)
- [SciPy Japan 2020 speaker "Translation Project of Mayavi2 documents"](https://youtu.be/epxm9SjLMS0)
- [PyConJP 2021 speaker "Visualize 3D scientific data in a Pythonic way like matplotlib"](https://youtu.be/ru-nENLgleo)

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Kevin Lacaille

Planet Labs

Kevin is a Canadian astronomer, tiny satellite enthusiast, and software engineer at Planet, where he develops tools to empower fellow scientists and developers to explore the Earth. Having worked in both academia and tech, Kevin has over 7 years of public speaking experience at conferences around the world and has published 25 peer-reviewed papers. He has a wide variety of teaching experience as a university teaching assistant, college mathematics educator, and planetarium presenter. His most recent experiences include speaking at the Canadian Astronomical Society Conference 2019, and teaching a hands-on Python workshop at L3Harris Engineers Week 2021. Portfolio website: https://www.lacaille.dev/

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Haw-minn Lu

West Health Institute

Dr. Haw-minn Lu is currently a Principal Data Scientist for Data Science/Machine Learning at West Health Institute in La Jolla, a nonprofit medical research organization. Dr. Lu earned his PhD in 1998 from the Electrical and Computer Engineering Department at the University of California, San Diego after receiving SM and SB degrees from the Massachusetts Institute of Technology.

Dr. Lu has been doing machine learning for over 25 years. His interests include machine learning, interactive visualization, data imputation/anonymization, and computing infrastructure.

Prior to joining West Health, Dr. Lu was involved in several startups using Python as the core infrastructure for applications such as ecommerce, network communications, and digital animation.

Dr. Lu is an instructor of machine learning at the University of San Diego

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Mariana Meireles

NumFOCUS

I'm a software engineer at Anaconda, a Jupyter distinguished contributor, a member of the Jupyter Widgets steering council and the NumFOCUS DISC committee.

I'm a person driven by meaning and I find a lot of significance and love in libre software and the internet and I love to work with it. The concept of liberating knowledge and nurturing cultural and scientific development deeply resonates with many of my personal goals and working towards making the digital world more accessible and comfortable for all is a very fulfilling mission to me.

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Tim Mensinger

University of Bonn

I'm a PhD candidate in economics at the University of Bonn, currently working on topics related to computational econometrics. My projects range from contributing to optimization libraries to implementing statistical methods or models of human behavior. In all cases, I try to develop software that is easy to use and extend. Besides that, I'm a big advocate for reproducibility and the open-source philosophy, which I try to support by being an active member of the Open Source Economics initiative.

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Ido Michael

Ploomber

Ido Michael co-founded Ploomber to help data scientists build faster. He'd been working at AWS leading data engineering/science teams. Single handedly he built 100’s of data pipelines during those customer engagements together with his team. He's a MS graduate from Columbia University in NY. He focused on building Ploomber after he constantly found that projects dedicated about 30% of their time just to refactor the dev work (prototype) into a production pipeline.

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Riley Murray

CVXPY

Riley holds a PhD in Computing and Mathematical Sciences from Caltech. His thesis work on convex relaxation methods for nonconvex optimization received Caltech's 2021 Amori Doctoral Prize. He is currently a postdoc at UC Berkeley, where he leads the development of BLAS- and LAPACK-like libraries for randomized numerical linear algebra. He started contributing to CVXPY in 2018 and now serves as one of CVXPY's four project maintainers.

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Tom Nicholas

Columbia University

Tom is a Research Software Engineer working in Ryan Abernathey's Ocean Transport Group at Lamont Doherty Earth Observatory, Columbia University.

He first started using the open-source scientific python stack during his PhD, when he was studying plasma turbulence in nuclear fusion reactors.

He is a member of the xarray core development team, and also works on xGCM, pint-xarray, and xarray-datatree.

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Jim Pivarski

Princeton University

Jim Pivarski was trained as a particle physicist with a Ph.D. from Cornell and helped commission the CMS experiment at the Large Hadron Collider (LHC). He then worked as a data scientist at Open Data Group for 5 years. In 2016, he joined Princeton as a computational physicist, where he develops software tools for data analysis, including Awkward Array, which manipulates arrays of data structures.

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Prabhu Ramachandran

Indian Institute of Technology Bombay

Prabhu Ramachandran is a faculty member at the department of aerospace
engineering, IIT Bombay. His research interests include particle methods for
computational fluid dynamics, scientific computing, parallel and
high-performance computing, and applied scientific data visualization.

He has been actively involved with the FOSS and Python communities for the
past two decades. He is an active member of the SciPy community and develops
many Python-based open source packages that are useful in the context of
scientific computing. He is the creator of the Mayavi Python package for 3D
visualization (https://github.com/enthought/mayavi). He is a PI of the FOSSEE
project (https://fossee.in) through which he has led the development of tools
and material to spread the adoption of Python. He has been a nominated fellow
of the Python Software Foundation since 2010. He was awarded the Kenneth
Gonsalves award by the Python Software Society of India and PSF in 2014. For
more information see https://www.aero.iitb.ac.in/~prabhu

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Jonathan Rocher

KBI Biopharma

Jonathan Rocher is principal software architect at KBI Biopharma Inc. He earned a PhD in Theoretical Physics from the university of Paris, and currently leads, designs and/or builds scientific applications and data science tools to streamline and improve the drug manufacturing processes at KBI. In all, he has been building mid to large size scientific applications using the Enthought Tool Suite for more than 10 years at KBI and before that at Enthought Inc for mid to large size companies in biotech, oil and gas, and other industries. He is also a passionate supporter, teacher and contributor to open-source scientific Python, including a regular SciPy conference contributor.

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Jessica Scheick

University of New Hampshire

Dr. Jessica Scheick is a glaciologist, open-source software developer, remote sensor, and lifelong lover of snow, winter, and the outdoors. She is currently a Research Assistant Professor at the University of New Hampshire, where she works on glaciological research, research-enabling open-source software projects, and climate justice and diversity, equity, and inclusion initiatives. She is the lead developer and maintainer for the icepyx library, an Xarray user and contributor, and regularly runs Hackweeks with the University of Washington's eScience Institute. When she's not working, you can usually find Jessica outside.

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Philipp Schiele

Ludwig Maximilian University of Munich

My educational background is in finance and economics and I'm currently pursuing a Ph.D. in financial econometrics at the Ludwig Maximilian University of Munich. My research mostly focuses on portfolio optimization, time series analysis, and deep learning. As part of my Ph.D., I am currently a visiting student researcher at Stanford University. I am also working as a Financial Engineer at Scalable Capital, a German robo-advisor. Generally, I am enthusiastic about finance, optimization, and technology.

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Mridul Seth

-

I am currently working on the NetworkX open source project (work funded through a grant from Chan Zuckerberg Initiative!) Also collaborating with folks from the Scientific Python project (Berkeley Institute of Data Science), Anaconda Inc and GESIS, Germany. Before this I used to work on the GESIS notebooks and gesis.mybinder.org.
I am also interested in the development and maintenance of the open source data & science software ecosystem. I try to help around with the Scientific Open Source ecosystem wherever possible. To share my love of Python and Network Science, I have presented workshops at multiple conferences like PyCon US, SciPy US, PyData London and many more!

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Mansi Shah

Planet

Mansi Shah is a data scientist, flutist, and environmentalist whose work explores the spaces where artistic rigor and technical curiosity collide. She believes data (like art!) imitates life, and is interested in the profoundly human stories behind the numbers and notes. Mansi has over 10 years of experience as an artist and performer, connecting to diverse audiences through words and music. In addition to her work as a flutist, Mansi has performed in plays, directed ensembles, hosted concerts, and given lectures on topics ranging from creative applications of cloud native geospatial technologies to celebrating diversity in the arts. Her recent project Counterpoints premiered in early 2022 at the Data Through Design exhibition in NYC, and brings together her geospatial and musical perspectives. Mansi works for Planet Labs as a software engineer, helping make the power of daily global satellite imagery more accessible to all.
Website: https://www.iammansi.com/

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Julia Signell

Saturn Cloud

Julia is the Head of Open Source at Saturn Cloud, a data science platform that enables simple and customizable access to Jupyter and Dask on AWS. Julia has worked in the scientific Python ecosystem as an environmental researcher, an open source contributor, and on both the frontend and backend data science platform product teams. In her current role at Saturn Cloud, Julia works on the engineering team and contributes to the maintenance of Dask. Before joining Saturn, Julia worked on the HoloViz team at Anaconda and as a hydrometeorology researcher at Princeton University.

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Adam Symington

Geollect

Dr. Adam Symington is a geospatial data scientist, leading the data science team at Geollect Ltd in the United Kingdom. Over the last two years he has developed exceptional geospatial data science skills and worked on projects with a variety of data sources across multiple sectors. Adam regularly publishes geospatial data science tutorials on towards data science and runs the PythonMaps project, a project designed to spread the love of geospatial data through eye-catching visualisation. Prior to his career in data science Adam was a computational materials scientist at the University of Bath in England where he used machine learning and other statistical techniques to predict the properties of materials. Adam has published 17 peer reviewed research papers, including 3 open-source software papers. During Adams time in academia, he taught Python programming to undergraduates and postgraduate students and wrote his own Python programming course which he delivered to show students how to apply Python to their data analysis.

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Logan Thomas

Enthought

Logan is a Senior Digital Transformation (DTX) Services Consultant and Instructor at Enthought. In the past, he has worked as a data scientist and machine learning engineer in both the digital media and protective engineering industries. His experience includes discovering relationships in large datasets, synthesizing data to influence decision making, and creating/deploying machine learning models. Logan enjoys learning new things and sharing his knowledge with others. Outside of work, he enjoys staying active, spending time with his family, and brewing a good cup of coffee.

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Jacob Tomlinson

NVIDIA

Jacob Tomlinson is a senior Python software engineer at NVIDIA with a focus on deployment tooling for distributed systems. His work involves maintaining open source projects including RAPIDS and Dask. RAPIDS is a suite of GPU accelerated open source Python tools which mimic APIs from the PyData stack including those of Numpy, Pandas and SciKit-Learn. Dask provides advanced parallelism for analytics with out-of-core computation, lazy evaluation and distributed execution of the PyData stack. He also tinkers with the open source chatbot automation framework Opsdroid in his spare time. Jacob volunteers with the local tech community group Tech Exeter and lives in Exeter, UK.

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Jacob Tomlinson

NVIDIA

Jacob Tomlinson is a senior Python software engineer at NVIDIA with a focus on deployment tooling for distributed systems. His work involves maintaining open source projects including RAPIDS and Dask. RAPIDS is a suite of GPU accelerated open source Python tools which mimic APIs from the PyData stack including those of Numpy, Pandas and SciKit-Learn. Dask provides advanced parallelism for analytics with out-of-core computation, lazy evaluation and distributed execution of the PyData stack. He also tinkers with the open source chatbot automation framework Opsdroid in his spare time. Jacob volunteers with the local tech community group Tech Exeter and lives in Exeter, UK.

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Siddhant Wahal

Enthought, Inc.

Siddhant is a Scientific Software Developer at Enthought where he writes software that empowers scientists. He holds a Ph.D. in Computational Science from the University of Texas at Austin, and a B.Tech. in Mechanical Engineering from Indian Institute of Technology, Kharagpur.

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Kevin Yamauchi

ETH Zürich

Currently, I am a postdoctoral researcher, advised by Dagmar Iber in the Department of Biosystems Science and Engineering at the ETH Zürich. I am writing software for microscopy analysis in support of the lab’s goal of understanding the molecular mechanisms that underpin morphogenesis. Additionally, I am a core developer of napari.

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Jesssie Yu

IBM

Jessie Yu is a senior software enginner and prolific inventor at IBM. Prior to working on quantum computing, Jessie’s career was mainly in the area of IBM mainframe kernel development and analytics software. Her experience in IBM Quantum began in 2018 where she first worked on systems and infrastructure support and later took over as maintainer for qiskit-ibmq-provider, a framework that provides access to IBM Quantum devices and services. She is now the product owner of the quantum backend software. Throughout her career she has presented at various conferences, workshops, and customer engagements.

Conference Speakers
Conference Speakers & Authors
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Tanya Akumu

IBM Research Africa

Tanya Akumu is an engineer with experience in IoT, data analysis, machine learning and deep learning. She has a master's degree in Electrical and Computer Engineering with a specialization in applied machine learning from Carnegie Mellon University. She has Developed several projects that involved building data collection platforms, performing data analysis for remote monitoring and predictive maintenance and implementing machine learning architectures for energy systems and battery systems. Currently, she is an AI Science developer at IBM Research Africa working on explainable AI and robustness of machine learning systems using multidimensional subset scanning.

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Niels Bantilan

Union.ai

Niels is a machine learning engineer and core maintainer of Flyte, an open source ML orchestration tool and creator of Pandera, a statistical typing and data testing tool for scientific data containers. His mission is to help data science and machine learning practitioners be more productive.

He has a Masters in Public Health with a specialization in sociomedical science and public health informatics, and prior to that a background in developmental biology and immunology. His research interests include reinforcement learning, AutoML, creative machine learning, and fairness, accountability, and transparency in automated systems.

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Sebastian Bichelmaier

TU Vienna

Final-year PhD student working together with Infineon towards an efficient approach for modelling material properties using machine learning. My research is focused on overcoming computational limits imposed by costly DFT calculations by using neural-network force fields, and on extracting thermodynamical results from those accelerated models of the potential energy hypersurface. I am very interested in differentiable code and its use cases in physics.

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Alex Bozarth

IBM

Alex is a Software Engineer and Jupyter Architect at the IBM Center for Open Source Data and AI Technologies (CODAIT), contributing to the Jupyter ecosystem. He serves on the JupyterLab Council and is a core committer on the Elyra project. He is also a PPMC for Apache Livy (Incubating).

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Julius Busecke

Columbia University

I am a oceanographer who is interested in the role of the ocean for earth's climate and marine ecosystems. I use a variety of datasets from observations, over satellite data, to fully coupled numerical models of the earth system. Given the urgency given by the human-made climate crisis, I believe it is imperative to transform the way we do science to be fully open and more efficient. I try to contribute to this goal by using and contributing to the growing scientific python stack and try to empower more people to get involved with climate data.

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Allan Campopiano

Deepnote

As a data scientist at Deepnote, I have the privilege of partnering with developers all over the world in order to help them promote their tools to the broader scientific community. By demonstrating the leading data science tools in Deepnote, scientists and developers can easily onboard to new concepts and techniques.

My degree in cognitive and behavioural neuroscience helped me realize my dual passion for (1) developing scientific software and (2) communicating technical concepts in a straightforward manner. My main goal is to find creative ways to lower the barrier-to-entry for scientists who are learning new tools.

To this end, I've published two peer-reviewed statistical software libraries. The most notable is Hypothesize—a Python library for robust statistics based on Rand Wilcox's R package. I continue to deliver workshops on robust statistics, data visualization, and data science tooling in general.

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Juan Luis Cano Rodríguez

poliastro

Juan Luis Cano is an Aerospace Engineer based in Madrid, Spain working as a Data Scientist Advocate at Orchest. He has worked for the satellite industry in the past, developing Python tools for geospatial data processing, automating satellite operations, and completing several freelance R&D projects. Juan Luis is the author and lead developer of poliastro, a Python library for interactive Astrodynamics, and was one of the founders of the Python community in Spain. In his spare time he enjoys listening to music, eating exotic street food, roasting strangers on LinkedIn, and chasing impossible dreams.

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Luigi Cruz

SETI Institute

Luigi Cruz is a Digital Signal Processing intern at the SETI Institute currently working on the GPU accelerated beamformer for the Allen Telescope Array. He is pursuing his bachelor's degree in Computer Engineering at the Federal University of Technology in Brazil. He also maintains multiple open-source projects like the PiSDR, an SDR specialized Raspberry Pi image, CyberEther, a CUDA accelerated signal visualization library, and Radio Core, a Python library for demodulating SDR signals using the GPU with the help of cuSignal and CuPy.

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Orhan Eroglu

National Center for Atmospheric Research

Orhan Eroglu works at the National Center for Atmospheric Research (NCAR) in Boulder, CO as a Software Engineer III, leading the Geoscience Community Analysis Toolkit (GeoCAT) group. He manages the GeoCAT team's several research and development projects in the scientific Python ecosystem, ensuring the implementations are scalable and compatible with the Pangeo ecosystem as well as the community is involved throughout the project lifecycle with the help of an open development approach. UXarray (Project Raijin), GeoCAT-comp, GeoCAT-examples, and GeoCAT-viz are some the GeoCAT efforts. Orhan received his B.Sc. and M.Sc. degrees in computer engineering from Bogazici University in 2009 and Turkish Air Force Academy in 2013, respectively, in Istanbul, Turkey. He worked as a senior researcher and software engineer in The Scientific and Technological Research Council of Turkey (TUBITAK), Informatics And Information Security Research Center (BILGEM) between 2009 and 2016. He received a Ph.D. degree in electrical and computer engineering from Mississippi State University, USA in 2019, with his dissertation of machine learning-aided information retrieval from satellite observatory.

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Thomas Fan

Quansight Labs

Thomas J. Fan is a Senior Software Engineer at Quansight Labs and is a maintainer for scikit-learn, an open-source machine learning library for Python. Previously, Thomas worked at Columbia University to improve interoperability between scikit-learn and AutoML systems. He is a maintainer for skorch, a neural network library that wraps PyTorch. Thomas has a Masters in Mathematics from NYU and a Masters in Physics from Stony Brook University. During his academic career, he has conducted research in quantum computation.

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Juanita Gomez

Scientific Python

Juanita Gomez is passionate programmer, mathematician, and open source advocate. She has a BS in Pure Mathematics from Pontificia Universidad Javeriana in Colombia and is currently pursuing a PhD in Computer Science at UC Santa Cruz. She is a community manager for the Scientific Python project, a community effort to better coordinate and support scientific Python libraries.

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Savin Goyal

Outerbounds

Savin is the co-founder and CTO of Outerbounds where he focuses on building generalizable infrastructure to accelerate the adoption and impact of ML in enterprises. Previously, he was at Netflix where he built Metaflow, a popular OSS ML platform. In his previous life, he obtained a bachelors degree in CS from IIT Delhi.

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Perry Greenfield

STScI

Perry Greenfield got his Ph.D. in Physics from M.I.T. in Radio Astronomy studying the first discovered gravitational lens with the Very Large Array. He has been at the Space Telescope Science Institute for 36 years and is currently a Consulting Science Software Engineer. He and his group started using Python in 1998 and pioneered the use of Python in astronomy, being involved in key developments such as PyRAF, pyfits, numarray, matplotlib, and Astropy. Python plays a central role in the science software for the Hubble and James Webb Space Telescopes, and the future Nancy Grace Roman Space Telescope.

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Gabe Joseph

Coiled

Gabe is an open-source engineer at Coiled, where he primarily contributes to Dask. Previously, he's worked on other Python tools for analyzing scientific data at scale, including the geospatial data platform at Descartes Labs and bioacoustic analysis tools for the National Park Service. On the side, he works on stackstac and other geospatial tools mostly as an excuse to look at cool pictures from space.

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Cliff Kerr

Bill and Melinda Gates Foundation

Dr. Cliff Kerr is a Senior Research Scientist at the Institute for Disease Modeling, part of the Bill & Melinda Gates Foundation, where he works on COVID, polio, and family planning. Previously, he completed a B.Sc. in neuroscience and a Ph.D. in physics, was a lecturer in scientific computing at the University of Sydney, co-founded two startups (on data analytics and health economics), worked on a DARPA project teaching robots to pick up balls, and developed an algorithm that composes music in real time based on brain activity recordings. He is passionate about architecture, cooking, and promoting equity in global health. He lives in New York.

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Kevin Kho

Prefect

Kevin Kho is an Open Source Community Engineer at Prefect, an open-source workflow orchestration management system. Previously, he was a data scientist at Paylocity, where he worked on adding machine learning features to their Human Capital Management (HCM) Suite. Outside of work, he is a contributor for Fugue, an abstraction layer for Pandas, Spark, and Dask. He also organizes the Orlando Machine Learning and Data Science Meetup.

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James Lamb

SpotHero

James Lamb is a machine learning engineer at SpotHero, a Chicago-based digital marketplace for parking. He is a maintainer of LightGBM, a popular machine learning framework from Microsoft Research, and has made many contributions to other open source data science projects, including hamilton, prefect, and XGBoost. Prior to joining SpotHero, he worked on a managed Dask + Jupyter + Prefect service at Saturn Cloud and as an Industrial IoT Data Scientist at AWS and Uptake. He is also an adjunct instructor at Marquette University, where he teaches Introduction to R Programming.

Outside of work, he enjoys going to hip hop shows, rooting for the Boston Celtics / Red Sox, and watching reality TV (especially Bravo).

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Jun Liu

Lyft

Jun Liu is a Data Scientist at Lyft. She leads machine learning projects in the problem field of recommendation and purchasing. Before joining Lyft, Jun received her Ph.D. in July 2020 in Applied Mathematics from Michigan State University.

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Matteo Manica

IBM Research

Matteo is a Research Staff Member in Accelerated Discovery at IBM Research Europe - Zürich. He's currently working on AI-driven chemical synthesis automation and on the development of multimodal generative models for material science. He received his degree in Mathematical Engineering from Politecnico di Milano in 2013. After getting his MSc he worked in a startup, Moxoff spa, as a software engineer and analyst for scientific computing. In 2019 he obtained his doctoral degree at the end of a joint PhD program between IBM Research and the Institute of Molecular Systems Biology, ETH Zürich, with a thesis on multimodal learning approaches for precision medicine.

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Tom Nicholas

Columbia University

Tom is a Research Software Engineer working in Ryan Abernathey's Ocean Transport Group at Lamont Doherty Earth Observatory, Columbia University.

He first started using the open-source scientific python stack during his PhD, when he was studying plasma turbulence in nuclear fusion reactors.

He is a member of the xarray core development team, and also works on xGCM, pint-xarray, and xarray-datatree.

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Tirth Patel

Nirma University

Maintainer of SciPy and a final-year computer science student at Nirma University. Previously, GSoC 2020 student with PyMC and GSoC 2021 student with SciPy.

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Bradley Rees

NVIDIA

Brad Rees is a Senior Manager at NVIDIA and lead of the RAPIDS cuGraph team. Brad has been designing, implementing, and supporting a variety of advanced software and hardware systems for over 30 years. Brad specializes in complex analytic systems, primarily using graph analytic techniques for social and cyber network analysis. Brad has a Ph.D. in Computer Science from the Florida Institute of Technology.

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Pamphile Roy

Quansight

Pamphile Roy is a software Engineer working at Quansight. He is from Tahiti, French Polynesia and is currently living in Austria.

He has been working in a wide range of scientific fields with both academic and industrial partners such as Airbus, Safran, Stanford, the French electricity and the EU's Join Research Commission.

Recently he has been doing machine learning for the game Microsoft Flight Simulator 2020, built grammar error correction models and implemented backend services at iTranslate.

He thrives to share and participate in the open-source space. As such, he is a maintainer of SciPy, contributes to a few other Python packages, member of the Scientific Python Ecosystem, and is a referee for the Small Development Grants Committee of NumFOCUS.

He has a Ph.D. in Uncertainty Quantification applied to Computational Fluid Dynamics from the CERFACS/INPT and two Master's in Aerospace Engineering.

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Rianne Schouten

Eindhoven University of Technology

Rianne Schouten is a PhD Candidate at Eindhoven University of Technology in the Data Mining Group, the Netherlands. Her research focuses on Exceptional Model Mining for heterogeneous datasets with time-dependent variables (a pattern mining framework).

In addition, she develops statistical methods for incomplete datasets. In particular, Rianne developed a multivariate amputation procedure for creating a missing data mask for complete datasets. She implemented her work first in statistical software R (in function ampute in package mice).

Now, together with Davina Zamanzadeh, Rianne releases a brand-new amputation library for Python: PyAmpute (documentation at https://rianneschouten.github.io/pyampute/).

A full overview of Rianne's publications and activities can be found at her website: https://rianneschouten.github.io. She can be reached through e-mail: r.m.schouten@tue.nl

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Shaswat Shah

Lyft

Shaswat is a Staff Machine Learning Engineer at Lyft where he has worked on a diverse set of problems spanning from price elasticity, recommendations and pickup time estimation. Currently, he is a tech lead on the Product Offerings team, which owns Lyft variants such as Shared and Wait & Save.

Before Lyft, Shaswat finished his Masters in Computer Science at Georgia Institute of Technology where he focused on applying computer vision techniques for volume estimation and signal processing. Shaswat also holds a Masters in Business Administration from Indian Institute of Management, Bangalore.

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Scott Shambaugh

Capella Space

Scott Shambaugh has spent his career in the US space industry working on Guidance, Navigation, and Control R&D for launch vehicles, human spaceflight, and small satellites, as well as some time developing autonomous self-driving vehicles. Currently Scott is the Spacecraft ADCS & Prop Lead at Capella Space, helping bring any-time, any-weather Earth imagery to the commercial market. He holds a M.S. in Aeronautical and Astronautical Engineering from Purdue and a B.S. in Mechanical Engineering from USC. Guiding his open-source efforts presented here is an unwavering optimism that firm foundations for science, engineering, and policy-making will improve quality of life for all.

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Davina Zamanzadeh

UCLA

Davina is a PhD student in computer science in her 4th year at UCLA. Previously trained in computer science with a BSc from UCSB, currently her research area is machine learning with clinical applications and she primarily does work on imputation with deep learning. Davina has balanced her experience between academia and industry, and actively partakes in the broader informatics community (check out the ForYourInformatics podcast!). In her free time Davina enjoys video editing and in the winters can be found falling down a double black diamond at Mammoth Mountain.

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Marius van Niekerk

Voltron Data

Marius van Niekerk is a Principal Software Engineer at Voltron Data holding an M.Sc in Mathematical Statistics from the University of Stellenbosch, South Africa. He has been actively involved in the PyData space for around 10 years now. He's been a member of the conda-forge core team for about 5 years.


Poster Presenters
Poster Presenters & Authors

Carl Simon Adorf

EPFL

Dr. Adorf is a computational scientist and research software engineer in the THEOS group led by Nicola Marzari at EPFL in Lausanne, Switzerland. He works on advancing the scientific research software infrastructure as work package manager for the H2020 Materials Modeling MarketPlace project and project team lead for the AiiDAlab simulation-as-a-service web platform (www.aiidalab.net). Previously, he obtained his Ph.D. at the University of Michigan, Ann Arbor, where he employed machine learning methods for materials inverse design and the study of colloidal crystallization pathways.

As part of his responsibilities he is maintaining and contributing to various open-science and open-source projects, including the Materials Cloud (materialscloud.org) and the AiiDA informatics platform (aiida.net). He also helps maintain the signac data and workflow management framework (signac.io) — a project that he launched in 2015 and that since then has seen widespread adoption across various research groups in the U.S. and Europe and is affiliated with the NumFOCUS organization as of 2019.

Daniel Althviz

Quansight/Quansight Labs/Spyder

I have Bachelor's degrees in industrial engineering and in systems and computing engineering, with a minor in Biology and a Masters in software engineering, all from Universidad de los Andes in Bogotá, Colombia.

I started learning Python in 2016, when I got the opportunity to become involved with Spyder, and now I'm a core developer with the project. Currently, I'm employed by Quansight/Quansight Labs, working mainly on supporting the Spyder project: https://www.spyder-ide.org/

Alex Bozarth

IBM

Alex is a Software Engineer and Jupyter Architect at the IBM Center for Open Source Data and AI Technologies (CODAIT), contributing to the Jupyter ecosystem. He serves on the JupyterLab Council and is a core committer on the Elyra project. He is also a PPMC for Apache Livy (Incubating).

Simon Brugman

ING Bank

Simon works as a Senior Data Scientist at ING Bank, where he is part of his time developing popmon, a library for detecting dataset shift. In his past he has experience in core maintainer of the popular pandas-profiling package. His background is in computer science.

Juan Luis Cano

poliastro

Juan Luis (he/him/él) is an Aerospace Engineer with a passion for STEM, programming, outreach, and sustainability. He works as Data Scientist Advocate at Orchest, where he empowers data scientists by building an open-source, scalable, easy-to-use workflow orchestrator. He has worked as Developer Advocate at Read the Docs, previously as software engineer in the space, consulting, and banking industries, and as a Python trainer for several private and public entities.

Apart from being a long-time user and contributor to many projects in the scientific Python stack (NumPy, SciPy, Astropy) he has published several open-source packages, the most important one being poliastro, an open-source Python library for Orbital Mechanics used in academia and industry.

Finally, Juan Luis is the founder and former chair of the Python España association, the point of contact for the Spanish Python community, former organizer of PyCon Spain, which attracted more than 800 attendees in its last in-person edition in 2019, and current organizer of the PyData Madrid monthly meetups.

Luigi Cruz

SETI Institute

Luigi Cruz is a Digital Signal Processing intern at the SETI Institute currently working on the GPU accelerated beamformer for the Allen Telescope Array. He is pursuing his bachelor's degree in Computer Engineering at the Federal University of Technology in Brazil. He also maintains multiple open-source projects like the PiSDR, an SDR specialized Raspberry Pi image, CyberEther, a CUDA accelerated signal visualization library, and Radio Core, a Python library for demodulating SDR signals using the GPU with the help of cuSignal and CuPy.

Ondřej Cífka

LIRMM, Université de Montpellier; LTCI, Télécom Paris, Institut Polytechnique de Paris

Ondřej Cífka is a deep learning researcher with an interest in language, music, and sequence modelling in general. He got his Bachelor's and Master's degree from the Charles University in Prague where he worked on natural language processing and machine translation. His PhD at Télécom Paris, supported by a Marie Skłodowska-Curie fellowship, focused on music style transfer. He is now a postdoctoral researcher at Montpellier University working on animal movement modelling.

Itay Dafna

Bloomberg LP

Itay Dafna is a Software Engineer in Bloomberg’s San Francisco Engineering office. He is developing open source and proprietary data visualization libraries and tooling to help users explore, understand, and communicate complex relationships within their data. Itay joined Bloomberg in 2013, where he has previously held the roles of Quantitative Analytics Team Leader and Financial Engineer. Itay earned his MSc in Management from the London School of Economics, and has been awarded the Certificate in Quantitative Finance from the CQF Institute.

Chad Fulton

Federal Reserve Board of Governors

Chad Fulton is a Senior Economist at the Federal Reserve Board of Governors, and is a core contributor to Statsmodels with a particular interest in time series econometrics. He has written more than 20 tutorials on using state space models for time series analysis and forecasting in Python, from both a frequentist and Bayesian perspective.

Calvin Hendryx-Parker

Six Feet Up

Calvin Hendryx-Parker is the co-founder and CTO of Six Feet Up, a Python and Cloud expert consulting company that helps organizations build apps faster, innovate with AI/ML, simplify Big Data, and leverage Cloud technology. At Six Feet Up, Calvin establishes the company's technical vision and leads all aspects of the company's technology development. He provides the strategic vision for enhancing the offerings of the company and infrastructure, and he works with the team to set company priorities and implement processes that will help improve product and service development.

In 2019, Calvin was named an AWS Community Hero — one of only 24 Heroes in North America. He is the founder and host of the Python Web Conference, the largest worldwide event for web developers; the co-founder of IndyPy, the largest Python meetup in Indiana with 1,900+ members; and the founder of IndyAWS, the fastest growing cloud meetup in the state with 800+ members. Additionally, Calvin is the driving force behind LoudSwarm by Six Feet Up, a high impact virtual event platform that debuted in June 2020.

Calvin is regularly sought after to share his Python expertise — both at international conferences and in the media. Some of his recent contributions include:
- PyCon US (April 2022): Calvin presented, “Bootstrapping a Local Python Environment”
- Python Web Conference (March 2022): Calvin presented two talks including: “Predict Lightning Strikes using Django and AWS” and “Data Pipeline Modernization at Scale”
- Datanami (October 2021): Calvin was featured as an expert in the article, “What’s Driving Python’s Massive Popularity?”
- DjangoCon US (October 2021): Calvin presented on “Bootstrapping your Local Python Environment.”
- PyOhio (August 2021): Calvin presented on how to hack Django Channels to seamlessly integrate Slack into the virtual event platform via “Hacking Django Channels for Fun (and Profit).”
- DjangoCon Europe (June 2021): Calvin presented on how to use containers to implement a process that focuses on the developer experience and application delivery via “Deploying a Django Virtual Event Platform Using Containers and Terraform.”
- App Developer Magazine (May 2021): Calvin shares why Python — with its “batteries-included” standard library — is one of the best languages for both beginner and advanced developers in the article, “4 Reasons Python is Taking Over the World.”
- Cloud Field Day 10 (April 2021): Calvin was selected as a Field Day Delegate and invited to participate in Cloud Field Day 10 — a multi-day discussion with leaders and product managers from enterprise IT companies including NetApp, Dell Technologies, VMware, Oracle, Scality, Veeam, Intel, Komprise and StorageOS.

Nathan Jessurun

University of Florida

Nathan started his PhD in 2019 at the Florida Institute for Cybersecurity (FICS) Research Lab at the University of Florida. His accomplishments include the development of several novel optical PCB assurance algorithms and multiple publications on hardware security using optical & X-Ray image analysis. His current research involves interactive image segmentation, machine learning, and computer vision-based preprocessing techniques.

Steven Kolawole

ML Collective

Steven Kolawole has his technical skillset cuts across Machine Learning and Software Engineering, with a bias for ML Research these days. His research interests focus on resource-efficient machine learning in terms of computational resources and low-resource/limited labeled data.

He is and has been heavily involved in varieties of ML subfields including ML Engineering, Software Engineering, Data Engineering, Data Science/Analytics, and Cloud Computing.

Steven is also big on knowledge sharing via community mentorship and collective growth, open-source development, meetups facilitation, speakership, technical writing, research, and he gets kicks from helping tech muggles find their feet.

Blaine Mooers

University of Oklahoma Health Sciences Center

Blaine Mooers is an Associate Professor of Biochemistry and Molecular Biology at OUHSC in Oklahoma City, OK, USA. He is also a member of the Stephenson Cancer Center and directs the Laboratory of Biomolecular Structure and Function. His lab uses X-ray crystallography, small-angle X-ray scattering, structure-based drug design, and molecular dynamics simulations to study the role of RNA structure in RNA editing. He also collaborates with colleagues to develop better anti-cancer compounds. He has been using Python and Jupyter to aid his data analysis for the past eight years. His research interests include developing software to improve computational workflows in structural biology. A Warren L. DeLano Memorial PyMOL Open-Source Fellowship funded some of this work. The National Institutes of Health currently funds his research. Contact him at blaine-mooers at ouhsc.edu.

Artash Nath

Monitor My Ocean

I am a Grade 10 Student from Toronto, Canada. I am an explorer. I travel from the depth of oceans to the farthest exoplanets using science, open data, and algorithms.

For the past year, I have been measuring changes in the underwater ocean noise levels, and in particular the contribution of anthropogenic activities such as marine shipping.

Linkedin: https://www.linkedin.com/in/artash-nath/
Twitter: https://www.twitter.com/wonrobot/

RISE 100 Global Fellow, Schmidt Futures and Rhodes Trust
2022 ISEF Team Canada
2021 Gold Medalist, Canada Wide Science Fair
2020 Gold Medalist, IRIC North America Science Fair

Tyler Newton

University of Oregon

Tyler Newton is a PhD Candidate at the University of Oregon currently focusing on research in seismology and computer vision. He is passionate about generating robust and reusable scientific software to solve problems. His past work spans analyzing stress on faults, constraining sea level rise estimates, building time series event detection and association algorithms, and designing a hardware interface for nodal seismic sensors.

Gabriel Okasa

EPFL

I am a postdoctoral researcher in data science at the Chair for Technology and Innovation Strategy (TIS-EPFL). I obtained my PhD in economics and finance with specialization in econometrics at the University of St.Gallen, Switzerland. Prior to joining EPFL I was affiliated with the Swiss Institute for Empirical Economic Research (SEW-HSG). My research interests lie at the intersection of econometrics and machine learning, focusing on both predictive as well as causal machine learning. I am particularly interested in robust machine learning and estimators based on resampling methods. Besides the theory I enjoy the statistical programming of the related algorithms, mainly using R and Python.

Geoffrey Poore

Union University

Geoffrey Poore is the creator of Codebraid and PythonTeX. He uses Python and Jupyter notebooks extensively in teaching upper-level undergraduate physics.

Rick Ratzel

Nvidia

Rick Ratzel is the Tech Lead for the Python / UX team. Rick joined NVIDIA just over three years ago, bringing several years of experience as a technical lead for teams in industries that include test and measurement, electronic design automation, and scientific computing. Rick’s focus for cuGraph, and throughout his career, has been on software architecture and API usability.

Rick Ratzel

Nvidia

Rick Ratzel is the Tech Lead of the Python / UX team for the cuGraph graph analytics library at NVIDIA. Rick joined NVIDIA just over three years ago, bringing several years of experience as a technical lead for teams in industries that include test and measurement, electronic design automation, and scientific computing.

Mansi Shah

Planet

Mansi Shah is a data scientist, flutist, and environmentalist whose work explores the spaces where artistic rigor and technical curiosity collide. She believes data (like art!) imitates life, and is interested in the profoundly human stories behind the numbers and notes. Mansi has over 10 years of experience as an artist and performer, connecting to diverse audiences through words and music. In addition to her work as a flutist, Mansi has performed in plays, directed ensembles, hosted concerts, and given lectures on topics ranging from creative applications of cloud native geospatial technologies to celebrating diversity in the arts. Her recent project Counterpoints premiered in early 2022 at the Data Through Design exhibition in NYC, and brings together her geospatial and musical perspectives. Mansi works for Planet Labs as a software engineer, helping make the power of daily global satellite imagery more accessible to all.
Website: https://www.iammansi.com/

Jyotika Singh

Placemakr

Jyotika is the Director of Data Science at Placemakr where she leads data intelligence and algorithm development that governs and optimizes operations. Previously, Jyotika was heading the Data Science team at ICX Media where she developed novel solutions that led to the business foundation. Jyotika has invented multiple patents in data science, algorithms and marketing optimization techniques.

Jyotika is passionate about supporting women in STEM. She volunteers as a mentor at Data Science Network in Nigeria, where she participates in mentorship sessions with young Nigerian women aspiring a career in Data Technology. She also serves as a mentor at Women Impact Tech, US, for supporting women in technology, product and engineering.

Mohammad Amin Tahavori

Politecnico di Milano

Experienced energy-economic modeller, focusing on the integration of energy and economic models with the objective of providing open-source tools to model the future energy transition scenarios and their environmental and economic impacts.

Nadia Tahiri

University of Sherbrooke

Prof. Nadia Tahiri is a bioinformatician, molecular/evolutionary biologist, and computer scientist. She is currently an assistant professor in the Department of Computer Science and a member of the Centre de recherche en écologie de l'Université de Sherbrooke (CREUS). She is interested in the evolutionary history of species by integrating climate parameters (phylogeography). Postdoctoral researcher from 2019 to 2021, she worked on QSAR/PBPK model prediction in environmental health sciences at Université de Montréal, supported by several awards and grants. She is interested in the evolutionary history of species by integrating climate parameters. More specifically, she is working on establishing the mathematical and statistical basis for solving the difficult problem of classifying phylogenetic trees, as well as creating a new open-source platform for biologists to use these new methods. Nadia is also very involved in community initiatives to promote women in technology and to make committee programs more inclusive (the right moves for equity, diversity, and inclusion).

Jacob Tomlinson

NVIDIA

Jacob Tomlinson is a senior Python software engineer at NVIDIA with a focus on deployment tooling for distributed systems. His work involves maintaining open source projects including RAPIDS and Dask. RAPIDS is a suite of GPU accelerated open source Python tools which mimic APIs from the PyData stack including those of Numpy, Pandas and SciKit-Learn. Dask provides advanced parallelism for analytics with out-of-core computation, lazy evaluation and distributed execution of the PyData stack. He also tinkers with the open source chatbot automation framework Opsdroid in his spare time. Jacob volunteers with the local tech community group Tech Exeter and lives in Exeter, UK.

Min Khant Zaw

Georgia Institute of Technology

Min is a researcher in computational statistics, scientific computing and many heuristic fields of computational science. He’ve previously published on many areas related to High performance computing, algorithms, architecture related fields and some papers on climate change models. His interests currently include Quantum computing, discrete mathematics and theory of computation. He is currently based in Georgia Tech.

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