Daniel S. Katz (@danielskatz)

Works on computer, computational, and data research at NCSA, CS, ECE, and the iSchool at the University of Illinois at Urbana-Champaign, and has a strong interest in studying common elements of how research is done by people using software and data.

Kevin M. Moerman (@Kevin-Mattheus-Moerman)

Lecturer Biomedical Engineering, College of Engineering & Informatics NUI Galway, Research Affiliate MIT Media lab, Senior Member IEEE, Developer for the GIBBON computational biomechanics project.

Kyle Niemeyer (@kyleniemeyer)

Mechanical engineer in the School of Mechanical, Industrial, and Manufacturing Engineering at Oregon State University. Computational researcher in combustion, fluid dynamics, and chemical kinetics, with an interest in numerical methods and GPU computing strategies.

Arfon Smith (@arfon)

Product for Data @github. Previously Head of Data Science @stsci. Zooniverse co-founder. Editor-in-chief of the Journal of Open Source Software

Kristen Thyng (@kthyng)

Physical oceanographer at Texas A&M University. Researches coastal ocean dynamics, transport of material in the ocean, and tidal turbines as a renewable energy source.

Gabriela Alessio Robles (@galessiorob)

Gabriela is a data Scientist focused on building open, fair, and diverse Ecosystems on software platforms including GitHub and most recently Atlassian. Throughout Gabriela’s career, she has helped product teams empower users by advocating for the inclusion of multicultural perspectives in technology. A member of Codeando Mexico Gabriela’s has aided in disaster relief and develops open data from the public sector. It is her passion to use education as a way to bring minorities into the tech industry.

Tania Allard (@trallard)

Research Software Engineer and data engineer, contributor and maintainer of a number of open source projects, mentor and community builder. She is particularly interested in reproducibility, sustainability, openness and FAIR principles in research software and data as well as bias an ethics in data science.

Katy Barnhart (@kbarnhart)

Research scientist at the U.S. Geological Survey Landslide Hazards Program. Her research focuses on integrating observations, model development, and model analysis to understand the evolution of the Earth's surface. She is a core developer of the Landlab toolkit.

Juanjo Bazán (@xuanxu)

Astrophysics researcher at CIEMAT, mathematician and software engineer currently developing chemical evolution models for galaxies. Juanjo has worked as advisor on open source policies and contributed code to many popular libraries like Rails or Astropy. He is member of the founder team of Consul, the more widely used open sourced citizen participation software.

Sebastian Benthall (@sbenthall)

Sebastian Benthall is an interdisciplinary researcher working on the economics of privacy and security at NYU School of Law. He received his PhD in Information Management and Systems from the University of California, Berkeley. His research has focused on how privacy and security depends on data flow and digital supply chain networks. More recently, he has become a contributing Research Engineer on Econ-ARK, an open source toolkit for structural modeling of heterogeneous agents.

Eloisa Bentivegna (@eloisabentivegna)

Computational physicist at IBM Research Europe, with interests in gravitational physics, high-energy physics, and fluid dynamics, as well as large-scale Scientific Computing in general.

Monica Bobra (@mbobra)

Research scientist at Stanford University in the W. W. Hansen Experimental Physics Laboratory who studies the Sun and space weather as a member of the NASA Solar Dynamics Observatory science team and contributes to Heliopython and SunPy.

Frederick Boehm (@fboehm)

Fred is a biostatistician with research interests in statistical genetics and quantitative trait locus mapping in model organisms. He maintains the qtl2pleio R package. As a postdoctoral researcher at the University of Massachusetts Medical School, he collaborates with microbiologists to study the genetics of tuberculosis susceptibility.

Jed Brown (@jedbrown)

Assistant Professor of Computer Science at the University of Colorado Boulder leading a research group developing scalable algorithms and sustainable software for prediction, inference, and design via high-fidelity and multiscale physically-based models. He is a core developer of PETSc.

Kakia Chatsiou (@kakiac)

My research focuses on automated, quantitative methods of processing large amounts of textual and other forms of unstructured data – mainly political texts and social media – and the methodology of text mining. I have published on applications of measurement and the analysis of text as data on machine learning methods and deep learning. I am also applying machine learning and natural language processing techniques to the analysis of public policy. My substantive research interests centre on resilience and the role of public policies and institutions at different levels of governance in shaping it. I have worked as an evaluation and digital transformation scientific advisor with local authorities and voluntary sector organisations in the UK and have delivered training to policy makers on evaluation practices, text analytics and data enabling transformation.

Pierre de Buyl (@pdebuyl)

Postdoc at the KU Leuven's Institute for Theoretical Physics. Pierre de Buyl studies active particles and soft matter using statistical physics and numerical simulations. He is one of the editors of the SciPy Lecture Notes.

Patrick Diehl (@diehlpk)

Patrick is an applied mathematician at the Center of Computation and Technology at Louisiana State University. His research interests arenon-local models, e.g. peridynamics; asynchronous many-task systems; and high performance computing. He is the co-host of the FLOSS for science podcast. Patrick received his PhD from the University of Bonn in Germany.

Dan Foreman-Mackey (@dfm)

Dan Foreman-Mackey is an Associate Research Scientist at the Flatiron Institute in the Center for Computational Astrophysics. His research program focuses on the development and application of probabilistic data analysis techniques to make novel discoveries and solve fundamental problems in astrophysics.

Jeff Gostick (@jgostick)

Associate Professor in Chemical Engineering at the University of Waterloo, runs the Porous Materials Engineering & Analysis Lab with a research focus on the transport phenomena in porous materials, especially electrodes. Lead developer of OpenPNM a pore network modeling package, PoreSpy a quantitative image analysis toolkit for tomograms.

Richard Gowers (@richardjgowers)

Senior software engineer at NextMove Software, lead developer of MDAnalysis and occasional contributor to various things. Interested in most things chemistry and software related, from Python to x86 assembly.

Olivia Guest (@oliviaguest)

Olivia Guest is a computational modeler in cognitive science and neuroscience. She creates and evaluates computational accounts for categorization and conceptual representation in healthy adults, patient groups, infants, and animals. She is also interested in using computational modeling and data science broadly in theoretical as well as applied contexts.

David Hagan (@dhhagan)

Experimental atmospheric chemist and software engineer at QuantAQ. He has spent much of his academic career building and maintaining a number of open source projects related to air quality and air quality sensors.

Alice Harpole (@harpolea)

Alice Harpole is a postdoc in the Department of Physics & Astronomy at Stony Brook University. Her research focuses on using hydrodynamics simulations to better understand the interiors of stars and flows on neutron stars. She is a fellow of the Software Sustainability Institute and core developer of the AMReX-Astro codes.

Kathryn Huff (@katyhuff)

Kathryn Huff is an Assistant Professor in Nuclear, Plasma, and Radiological Engineering at the University of Illinois at Urbana-Champaign. Her research focuses on modeling and simulation of advanced nuclear reactors and fuel cycles. She also advocates for best practices in open, reproducible scientific computing.

Luiz Irber (@luizirber)

Postdoc at the Lab for Data Intensive Biology at University of California Davis studying the formation and maintenance of online communities, and also working on indexing, searching and scaling data analysis in large public sequencing databases using data sketches, Python, Rust and decentralizing technologies.

Mark A. Jensen (@majensen)

Director of Data Management and Interoperability at the Frederick National Laboratory for Cancer Research, he leads efforts to design, build and maintain scientist-friendly research data systems that integrate clinical and multiomic data across thousands of cancer patient-donors. He is active in open source software development and a supporter of the FAIR (Findable, Accessible, Interoperable, Reusable) movement in scientific data management. A molecular evolutionary biologist by training, he served as an Associate Editor for the Journal of Molecular Evolution from 2008-2013.

Vincent Knight (@drvinceknight)

Vince is a mathematician at Cardiff University. He is a maintainer and contributor to a number of open source software packages and a contributor to the UK python community. His research interests are in the field of game theory and stochastic processes and also has a keen interest in pedagogy. Vince is a fellow of the Software Sustainability Institute and is interested in reproducibility and sustainability of scientific/mathematical research.

Hugo Ledoux (@hugoledoux)

Associate-professor at the Delft University of Technology in the Netherlands. Particularly interested in combining the fields of geographical information systems (GIS) and computational geometry, with an emphasis on 3D modelling.

Christopher R. Madan (@cMadan)

Assistant Professor in the School of Psychology at the University of Nottingham. Studying human memory and decision making using cognitive psychology and neuroimaging approaches, and developing novel computational methods along the way.

Brian McFee (@bmcfee)

Brian McFee is Assistant Professor of Music Technology and Data Science New York University. His work lies at the intersection of machine learning and audio analysis. He is an active open source software developer, and the principal maintainer of the librosa package for audio analysis.

Melissa Weber Mendonça (@melissawm)

Applied mathematician, working with numerical optimization and numerical linear algebra at the Federal University of Santa Catarina, in Brazil. Interested in open science, open research, and teaching practices in mathematics and computer science.

Lorena Mesa (@lorenanicole)

Political scientist turned data engineer and data scientist, Lorena Mesa is a GitHub data engineer and a Director and Vice-Chair, Elect on the Python Software Foundation. Lorena's passion for ethical and accountable open source and reproducible science has led her to be a supporter of the FAIR movement and champion of FATE - fair, accountable, and transparent - algorithms. One part activist, one part space enthusiast, and another part Trekkie, Lorena abides by the motto to "live long and prosper".

Mikkel Meyer Andersen (@mikldk)

Associate Professor at Department of Mathematical Sciences, Aalborg University, Denmark. Research interests include statistics for forensic genetics (mainly lineage markers like Y chromosomal DNA profiles) and open source research software. Teaches statistics and data science at BSc, MSc and PhD level. Involved in multiple software projects (e.g. for infrastructure and computer algebra).

Juan Nunez-Iglesias (@jni)

Juan is a Senior Research Fellow at Monash Micro Imaging, Monash University, Australia. He spent his PhD in computational biology working on methods to study gene expression data, before moving on to develop image analysis tools to elucidate neuronal circuits. He now spends all his time developing open source software for imaging in biological research, and is a core developer for scikit-image and napari.

Lorena Pantano (@lpantano)

Research scientist at Harvard T.H. Chan School of Public Health. She is focused on genomic regulation and data integration, and has 12 years of experience in biological data analysis and contributing to novel algorithms to improve the quantification and visualization of genomic data.

Stefan Pfenninger (@sjpfenninger)

Interdisciplinary researcher in renewable energy and environmental science. My group's research is on the global transition to a 100% clean and renewable energy system, and the technical, economic and policy barriers on the way to that goal. We develop software like Calliope to help us do so.

Viviane Pons (@VivianePons)

Associate professor at Université Paris-Sud. Mathematician, computer scientist and strong defender of open-source and open science in general. Contributor and user of the SageMath software. Member of the OpenDreamKit European project for open-source development in Mathematics.

Jack Poulson (@poulson)

Independent computational scientist running Tech Inquiry and Hodge Star Scientific Computing. Previously, research scientist at Google and assistant professor of mathematics at Stanford. His research interests: software engineering of high-performance mathematical libraries (e.g., conic optimization, lattice reduction, determinantal point processes, numerical PDEs), their connections to pure mathematics (e.g., differential geometry, conic analysis, representation theory).

Karthik Ram (@karthik)

A quantitative ecologist and data scientist at UC Berkeley' Institute for Data Science, his research focuses on food web dynamics, open science, open data, and reproducible research.

Kristina Riemer (@KristinaRiemer)

Scientific programmer in the DIgital Agriculture Group at the University of Arizona, Kristina maintains and promotes open software and datasets, provides computational training, and runs ecosystem models. She is interested in building open, inclusive, interdisciplinary scientific communities.

Amy Roberts (@pibion)

Amy Roberts is an Assistant Professor of Physics at the University of Colorado Denver, where she leads a research group focused on dark matter detection. She is particularly interested in building accessible analysis tools for the dark matter community and reproducible analysis infrastructure for large data sets.

Marie E. Rognes (@meg-simula)

Marie E. Rognes is Chief Research Scientist at Simula Research Laboratory, Oslo, Norway. Her research focuses on numerical methods for partial differential equations, software for scientific computing, with applications in biomechanics and neuroscience. She is a core member of the FEniCS and Dolfin-adjoint Projects.

Ariel Rokem (@arokem)

Trained in cognitive neuroscience (PhD: UC Berkeley, 2010) and computational neuroimaging (Postdoc, Stanford, 2011-2015), Ariel Rokem is now a data scientist at the University of Washington eScience Institute, where he continues to develop software for the analysis of human neuroimaging data, develops tools for reproducible and open research practices, and collaborates with researchers from a variety of fields to advance data-intensive research.

William Rowe (@will-rowe)

Bioinformatician working at the University of Birmingham, UK. Research areas include data sketching for genomics, variation graphs and metagenome profiling. Currently working on long-read sequencing applications for real-time genomic epidemiology.

David P. Sanders (@dpsanders)

Works in computational applied mathematics at the Faculty of Sciences, Universidad Nacional Autónoma de México (National University of Mexico, UNAM). Research and teaching interests in the areas of scientific computing, nonlinear dynamics, and interval analysis. Currently a visiting professor at MIT. Co-author of the JuliaIntervals suite of packages for interval arithmetic and applications.

Charlotte Soneson (@csoneson)

Research Associate at the Friedrich Miescher Institute for Biomedical Research in Basel, Switzerland, with a research background mainly in development and evaluation of analysis methods for transcriptomics data. Developer and maintainer of several open-source R packages for analysis, quality assessment and interactive visualization of high-throughput biological data.

Matthew Sottile (@mjsottile)

Research scientist working on program synthesis tools for high performance computing at Noddle.io, and adjunct faculty at the Washington State University Department of Mathematics and Statistics. His PhD work in computer engineering focused on measurement and analysis methods for performance analysis of high performance systems. He believes that open and reproducible research software artifacts are critical to the advancement of computational science.

Ben Stabler (@bstabler)

Ben develops open source data science software that is used by transportation planning agencies to help prioritize infrastructure investments. He is active in several initiatives of the Transportation Research Board of the National Academies of Sciences, Engineering, and Medicine.

Yuan Tang (@terrytangyuan)

Senior software engineer at Ant Financial, building AI infrastructure and AutoML platform. He's a committer of TensorFlow, XGBoost, and Apache MXNet, maintainer of several Kubeflow projects, and author of numerous open source software projects. He's also the author of the best-selling book TensorFlow in Practice which is the first book teaching TensorFlow in Chinese and has been translated to several other languages such as traditional Chinese and Korean.

George K. Thiruvathukal (@gkthiruvathukal)

Professor of computer science at Loyola University, Chicago, and visiting faculty at the Argonne National Laboratory Leadership Computing Facility. Research interests: high-performance & distributed computing, cyber-physical systems, software engineering, programming languages and systems, history of computing, computational and data science, computing education, and ethical/legal/social issues in computing. Past editor-in-chief of IEEE Computing in Science and Engineering.

Tim Tröndle (@timtroendle)

Interdisciplinary scientist analysing future energy systems and the hurdles of a transition towards decarbonised energy supply. I am a system scientist by training and have been working as a software and research software engineer in the past.

Leonardo Uieda (@leouieda)

Geophysicist researching methods for determining the inner structure of the Earth from geophysical observations, mainly disturbances in the Earth's gravity and magnetic fields. Developer of open-source software for processing, modeling, and visualizing geophysical data. Currently Visiting Research Scholar at the University of Hawai'i at Mānoa working on the Generic Mapping Tools.

Marcos Vital (@marcosvital)

Biologist, quantitative ecologist and open science enthusiast at Universidade Federal de Alagoas, Brazil, where he coordinates the Quantitative Ecology Lab. He is interested in a wide range of topics related to evolutionary ecology and conservation biology, but also in other fields such as active learning methods and digital games in education.

Bruce E. Wilson (@usethedata)

Manager for the Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics (ORNL DAAC) and Adjunct Professor of Information Sciences at the University of Tennessee, Knoxville. Originally trained as a chemist and statistician. Spent a few years as an Enterprise Architect. Research interests in citations, linked data, reproducible science, identity, cybersecurity, data reuse, and long-term data preservation.

Lorena A Barba (@labarba)

Jason Clark (@jasonclark)

George Githinji (@george-githinji)

Roman Valls Guimera (@brainstorm)

Melissa Gymrek (@mgymrek)

Alex Hanna (@alexhanna)

Lindsey Heagy (@lheagy)

Anisha Keshavan (@akeshavan)

Thomas J. Leeper (@leeper)

Abigail Cabunoc Mayes (@acabunoc)

Pjotr Prins (@pjotrp)

Tracy Teal (@tracykteal)

Jake Vanderplas (@jakevdp)

Yo Yehudi (@yochannah)