Program

For information about the maintainers track see the maintainers page.

This program may be subject to changes.

Monday, 2 September
Tuesday, 3 September
Wednesday, 4 September
Thursday, 5 September
Friday, 6 September

Poster session

The panels for the posters will be installed in the morning of the poster session day (look the schedule) in the hall and will be removed on the same day at the end of the conference, so authors can hang up their posters for entire day.

The size of the panel is: 100x250 cm.

Tutorials

With the tutorial tickets you can attend any tutorial of any track.

Monday, 2 September

Time	Baroja	Oteiza	Chillida
09:00	Getting Started with JupyterLab Mike Müller	Hands-on TensorFlow 2.0 Josh Gordon	3D image processing with scikit-image Alexandre de Siqueira
10:30	Coffee break
11:00	Numpy Tutorial Valerio Maggio	Deep Diving into GANs: From Theory to Production with TensorFlow 2.0 Paolo Galeone, Michele "Ubik" De Simoni	Reproducible Data Science in Python Rok Roškar, Chandrasekhar Ramakrishnan
12:30	Lunch
14:00	Introduction to pandas I Marc Garcia	Create CUDA kernels from Python using Numba and CuPy. Valentin Haenel	Building data pipelines in Python: Airflow vs scripts soup Dr. Tania Allard
15:30	Coffee break
16:00	Introduction to pandas II Marc Garcia	Speed up your python code Jérémie du Boisberranger	Performing Quantum Measurements in QuTiP Simon Cross
17:30	End

Tuesday, 3 September

Time	Baroja	Oteiza	Chillida
09:00	Never gets in a battle of bits without ammunitions Valerio Maggio	Sufficiently Advanced Testing with Hypothesis Zac Hatfield-Dodds	Introduction to geospatial data analysis with GeoPandas and the PyData stack Joris Van den Bossche
10:30	Coffee break
11:00	Introduction to SciPy Gert-Ludwig Ingold	Effectively using matplotlib Tim Hoffmann	Astronomical Image Processing Samuel Farrens
12:30	Lunch
14:00	Introduction to scikit-learn: from model fitting to model interpretation I Olivier Grisel, Guillaume Lemaitre	CFFI, Ctypes, Cython, Cppyy: how to run C code from Python Matti Picus	Parallelizing Python applications with PyCOMPSs Javier Conejero
15:30	Coffee break
16:00	Introduction to scikit-learn: from model fitting to model interpretation II Olivier Grisel, Guillaume Lemaitre	kCSD - a Python package for reconstruction of brain activity Jakub M. Dzik, Marta Kowalska	Data Science Lab Open session with mentors
17:30	End
20:00	Tutorials social event

Main conference

Wednesday, 4 September

Time	Mitxelena	Baroja	Oteiza
10:00	Opening notes
10:15	Keynote: Samuel Farrens From Galaxies to Brains! - Image processing with Python
11:00	Coffee break
11:30	Distributed GPU Computing with Dask Peter Andreas Entschev	How a voice assistant works Miren Urteaga	Sufficiently Advanced Testing with Hypothesis Zac Hatfield-Dodds
12:00	Modern Data Science: A new approach to DataFrames and pipelines Maarten Breddels, Jovan Veljanoski	QuTiP: the quantum toolbox in Python as an ecosystem for quantum physics exploration and quantum information science Alexander Pitchford, Nathan Shammah	What about tests in Machine Learning projects? Sarah Diot-Girard
12:30	Lunch
14:00	Open source project updates
14:45	Apache Arrow: a cross-language development platform for in-memory data Joris Van den Bossche	Constrained Data Synthesis Nick Radcliffe	Scientific DevOps: Designing Reproducible Data Analysis Pipelines with Containerized Workflow Managers Nicholas Del Grosso
15:15	Caterva: A Compressed And Multidimensional Container For Big Data Francesc Alted	ToFu - an open-source python/cython library for synthetic tomography diagnostics on Tokamaks Didier VEZINET, Laura Mendoza	Dashboarding with Jupyter notebooks, voila and widgets Maarten Breddels, Martin Renou
15:45	Modin: Scaling the Capabilities of the Data Scientist, not the machine Devin Petersohn	JupyterLab debugger Jeremy Tuloup	Make your Python code fly at transonic speeds! Pierre Augier
16:00	Coffee break
16:30	Best Coding Practices in Jupyterlab Alexander CS Hendorf	Controlling a confounding effect in predictive analysis. Darya Chyzhyk	PyFETI - An easy and massively Dual Domain Decomposition Solver for Python Guilherme Jenovencio
16:45	Lessons learned from comparing Numba-CUDA and C-CUDA Lena Oden	The Rapid Analytics and Model Prototyping (RAMP) framework: tools for collaborative data science challenges Joris Van den Bossche, Guillaume Lemaitre	High Voltage Lab Common Code Basis library: a uniform user-friendly object-oriented API for a high voltage engineering research. Mikołaj Rybiński
17:00	Poster introduction (Maintainers plenary session - maintainers track)
17:15	Poster session
18:30	End

Thursday, 5 September

Time	Mitxelena	Baroja	Oteiza
9:00	Opening notes
9:15	Keynote: David Liu HPC and Python: Intel’s work in enabling the scientific computing community
10:00	Coffee break
10:30	Inside NumPy: preparing for the next decade Matti Picus	Visual Diagnostics at Scale Dr. Rebecca Bilbro	Kubeflow Kale: from Jupyter Notebook to Complex Pipelines Valerio Maggio
11:00	Deep Learning without a PhD Paige Bailey	Histogram-based Gradient Boosting in scikit-learn 0.21 Olivier Grisel	Exceeding Classical: Probabilistic Data Structures in Data Intensive Applications Andrii Gakhov
11:30	The Magic of Neural Embeddings with TensorFlow 2 Oliver Zeigermann	Recent advances in python parallel computing Pierre Glaser	Driving a 30m Radio Telescope with Python Francesco Pierfederici
12:00	High quality video experience using deep neural networks Tiberio Uricchio	Data sciences in a polyglot world with xtensor and xframe Sylvain Corlay, Wolf Vollprecht	Matrix calculus with SymPy Francesco Bonazzi
12:30	Lunch
14:00	Keynote: Sara Issaoun In the Shadow of the Black Hole
14:45	A practical guide towards algorithmic bias and explainability in machine learning Alejandro Saucedo	Understanding Numba Valentin Haenel	VeloxChem: Python meets quantum chemistry and HPC Olav Vahtras
15:15	Tracking migration flows with geolocated Twitter data Antònia Tugores	PyPy meets SciPy Ronan Lamy	emzed: a Python based framework for analysis of mass-spectrometry data Uwe Schmitt
15:45	Deep Learning for Understanding Human Multi-modal Behavior Ricardo Manhães Savii	High performance machine learning with dislib Javier Álvarez	vtext: fast text processing in Python using Rust Roman Yurchak
16:00	Coffee break
16:30	How to process hyperspectral data from a prototype imager using Python Matti Eskelinen	Can we make Python fast without sacrificing readability? numba for Astrodynamics Juan Luis Cano Rodríguez	pystencils: Speeding up stencil computations on CPUs and GPUs Martin Bauer
16:45	Enhancing & re-designing the QGIS user interface – a deep dive Sebastian Ernst	PSYDAC: a parallel finite element solver with automatic code generation Yaman Güçlü	TelApy a Python module to compute free surface flows and sediments transport in geosciences yoann audouin
17:00	Lightning talks
18:15	Closing notes
18:30	End
20:00	Talks social event

Sprints

Friday, 6 September

Open source sprints are session where maintainers and contributors (including first time contributors) meet, and work together in improving the open source projects. This can include bug fixes, new features, improvements to the documentation and others.

More sprints will be added when they are proposed.

If you want to propose a sprint, please send us a message to maintainers@euroscipy.org.

Time	Chillida	Oteiza	Axular
10:00	Sprint presentations
10:30	SciPy scikit-learn Dataframe summit (pandas et al) Testing with Hypothesis SciPy lecture notes	scikit-image Tensorflow PyPy Blosc2 & Caterva docs	Mentored sprint for beginners in open source from underrepresented minorities
12:30	Lunch
14:00	(continue)	(continue)	(continue)
18:30	End