Speakers

Name	Presentation(s)
Abhilash Babu	Using scikit-learn models in a C/C++ application, Lightning Talks
Achilleas Koutsou	gin@home: run your own research data management platform, Lightning Talks
Adam Chang	Highly-Scalable NLP to Answer Questions on South Africa’s COVID-19 WhatsApp Hotline
Adam Webber	Building a Data-Driven Product from Scratch, How Hard Can It Be?
Adam Zadrożny	Law, Graphs & Python
Adrien Treuille	Python Dashboarding Shootout and Showdown
Adway Dhillon	Serving BERT Models in Production with TorchServe
Aishwarya Agrawal	Interpretable ML models at scale
Alankrita Tewari	Anyone GAN do this: Solving the Minority Class Imbalance problem once and for all
Alejandro Saucedo	Accelerating ML Inference at Scale with ONNX, Triton and Seldon
Aleksander Molak	Modeling aleatoric and epistemic uncertainty using Tensorflow and Tensorflow Probability
Alex Wu	Unifying Large Scale Data Preprocessing and Machine Learning Pipelines with Ray Datasets
Allen Downey	Computational Survival Analysis
Alon Nir	Sliding into Causal Inference, with Python!, Snack-size Awesome Lists, Lightning Talks
Amy Wooding	Love your (data scientist) neighbour: Reproducible data science the Easydata way
Anders Berkeman	Computations as Assets - a New Approach to Reproducibility and Transparency
Andrew Garrow	A Platform to Enable Data Science At Scale in Tesco
Andrew Shao	Introduction to Unsupervised and Semi-Supervised Learning in TensorFlow
Andrey Cheptsov	From Jupyter Notebooks To JetBrains DataSpell
Ankit Rathi	Best Practices in Machine Learning Observability
Antoni Baum	Cutting edge hyperparameter tuning made simple with Ray Tune
April Rathe	Dask: From POC to Production
Ardo Illaste	It's not just about survival: using survival analysis to study customer behaviour, Lightning Talks
Aseel Addawood	Reasoning with Natural Language Processing: advancement in the interpretation of Arabic speech
Ashraf Ibrahim	Redefining Insurance with Predictive and Preventive Artificial Intelligence.
Austin Walters	What's in your data: Data Profiler - An Open Source Solution to Explain Your Data, What's in your data: Data Profiler - An Open Source Solution to Explain Your Data
Avi Aminov	Classifying Documents on a Graph using GNNs
Banjo Obayomi	Lightning Talks, Building an Open Source Topic Modeling Library
Barry Fitzgerald	Risk at Scale - Running a large investment risk system and how risk analysis techniques can help you
Benjamin Ajayi-Obe	An analysis of Societal Bias in SOTA NLP Transfer Learning
Benjamin Lehne	A Platform to Enable Data Science At Scale in Tesco
Benjamin Zaitlen	Data Processing at Scale
Ben Marwick	Building Responsible Data Science Workflows: Transparency, Reproducibility, and Ethics by Design
Brad Boehmke	Foundational Infrastructure to Create a Successful Data Science Team
Braden Riggs	Unlocking more from your Audio Data, Unlocking More From Your Audio Data, Lightning Talks
Brendan Collins	Spatial Analytics using Dask & Numba, Lightning Talks
Brian Cechmanek	Pointer Generator Summarisation and Explainability for Legal Documents, Lightning Talks
Bruno Gonçalves	Graphs for Data Science with NetworkX (pre-recorded)
Carl Drougge	Computations as Assets - a New Approach to Reproducibility and Transparency
Chase Ginther	Enterprise Machine Learning Pipelines with Unstructured Image Data
Chengxuan Wang	FugueSQL - The Enhanced SQL Interface for Pandas, Spark, and Dask DataFrames
Cheuk Ting Ho	Knowledge graph data modelling with TerminusDB, Turning Pandas DataFrames to Semantic Knowledge Graph
Chin Hwee Ong	Designing Functional Data Pipelines for Reproducibility and Maintainability
Chris Ostrouchov	Serving and Managing Reproducible Conda Environments via Conda-Store
Christian Juncker Brædstrup	Stau - lightweight job orchestration for data science workloads, Lightning Talks
Christopher Ariza	Why Datetimes Need Units: Avoiding a Y2262 Problem & Harnessing the Power of NumPy's datetime64
Christopher Lozinski	An Introduction to the Current Information War
Clair J. Sullivan	Working with Data in a Connected World: the Power of Graph Data Science
Clark Zinzow	Unifying Large Scale Data Preprocessing and Machine Learning Pipelines with Ray Datasets
Clark Zinzow	Unifying Large Scale Data Preprocessing and Machine Learning Pipelines with Ray Datasets
Cor Zuurmond	Wisdom of the Crowd: amplifying human intelligence with AI
Dana Averbuch	Take a Deep Berth and Let’s Dive Into the Matching Algorithm for Marina’s, Lightning Talks
Daniel Townsend	Managing your data using FastAPI and Piccolo Admin
Danny Chiao	Feature Stores: An operational bridge between machine learning models and data
David Hopes	An analysis of Societal Bias in SOTA NLP Transfer Learning
Dean Pleban	🦉DVC Showcase – Who Moved My Data? 🗂
Diego Arenas	Automating the Exploration of Databases for Data Science with AEDA, Lightning Talks
Dingqian (Sara) Liu	What do C-Suite Executives Pay Attention To?
Dipam Paul	Anyone GAN do this: Solving the Minority Class Imbalance problem once and for all, Anyone GAN do this: Solving the Minority Class Imbalance problem once and for all
Doris Jung-Lin Lee	Lux: Automatic Visualizations for Exploratory Data Science
Dor Kedem	Introduction to Distance Metric Learning
Dr. Brandeis Marshall (she/her)	Building Responsible Data Science Workflows: Transparency, Reproducibility, and Ethics by Design
Dr. Shrirang Ambaji Kulkarni	Impact of Noisy Data on Support Vector Machine and Deep Learning Algorithms on Edge Computing Device
Eduardo Blancas	Effective Testing for Machine Learning Projects
Ehsan Totoni	Bodo: Supercomputing-Like Performance and Scale for Python/Pandas
Eli Sander	Think Like Git
Emeli Dral	Is my data drifting? Early monitoring for machine learning models in production.
Eric Dill	conda-forge in 2021
Eric Ma	An attempt at demystifying graph deep learning
Ethan Swan	Foundational Infrastructure to Create a Successful Data Science Team
Evgeny Karev	Livemark: markdown for data journalism and documentation writing, Lightning Talks
Eyal Kazin	Start Asking Your Data “Why?” - A Gentle Introduction To Causal Inference
Farooq Shaikh	Building a Meta Forecasting Model with Prophet and LSTM for Time series Forecasting, Lightning Talks
Filip Jankovic	From Jupyter to Production: Deploying an Influenza Monitoring System at Scale with Wearable Sensors
Francesc Alted	Introducing Blosc2, the next generation of the Blosc compressor
Francesco Lässig	Darts for Time Series Forecasting
Francesco Tisiot	Get to know Apache Kafka with Jupyter Notebooks, Kickstart your Apache Kafka with Faker Data, Lightning Talks
Frits Hermans	DedupliPy: a new deduplication package
Gaby Lio	Data Science in the Enterprise: A Holistic Approach
Gatha	Visualizations for Privacy Preservation: The Balancing Act between Utility and Uncertainty
Gus Cavanaugh	High Performance Python With Numba, Dask, and Rapids For the Absolute Beginner
Gus Powers	Foundational Infrastructure to Create a Successful Data Science Team
Guzal Bulatova	Sktime - a Unified Toolbox for Machine Learning with Time Series Data, Lightning Talks
Han Wang	Large Scale Data Validation with Fugue
hassaku	Improving accessibility for data science with graph sonification library, Lightning Talks
Haw-minn Lu	Map Visualizations with Dash Leaflet
Hoda Rezaei	Innovating in the Oil & Gas Industry with AI/ML
Hugo Bowne-Anderson	Dask for Everyone
Hussain Sultan	Packaging PyData for Enterprise Software Supply Chain (pre-recording)
Huy Ngo	Towards Collaborative Reproducibility: Pinning Repository of Binary Distributions
Ilana Tuil	Productizing Wav2Vec 2.0: challenges and considerations, Lightning Talks
Iman Mossavat	Compressive Sensing
Imen Ayari	Software inspired workflow for Data Analysis
Irina Vidal Migallón	The prototype hole and tools to help you out of it
Ivana Feldfeber	Analyzing gender based violence data with Python
Jacob Schreiber	Submodular optimization for minimizing redundancy in massive data sets
Jacob Tomlinson	GPU development with Python 101
Jacob Zelko	A Visual Odyssey: Animations and Visualizations Made with Julia, Lightning Talks
Jacqueline Nolis	Enterprise Machine Learning Pipelines with Unstructured Image Data, Enterprise Machine Learning Pipelines with Unstructured Image Data
James A. Bednar	Python Dashboarding Shootout and Showdown
James Bourbeau	Data Processing at Scale, Snowflake & Dask: How to scale workloads using distributed fetch capabilities
James Laidler	Iguanas - A new rule generation and optimisation package, Lightning Talks
James Powell	So you wanna be a Pandas expert? \| (Pre-recorded Tutorial), So you wanna be a Pandas expert? \| (Live Q&A)
Jason Lee	Improving Topic Model Interpretability Through Aggregation, Lightning Talks
Jeremy Goodsitt	What's in your data: Data Profiler - An Open Source Solution to Explain Your Data
Jeremy John Selva	Tips and advice when creating a python software for lab members to use in academia, Lightning Talks
Jeremy Tuloup	JupyterLite: Jupyter ❤️ WebAssembly ❤️ Python
Jesper Dramsch	How to Guarantee No One Understands What You Did in Your Machine Learning Project
Jiri Navratil	Uncertainty Quantification 360: A Hands-on Tutorial
John Cox	Using Generative Adversarial Networks (GANs) to Produce Elliptic Curves of Specified Rank, Lightning Talks
John McCambridge	Lightweight and Automated Exploratory Data Analysis, Lightning Talks
John Sandall	Agile Data Science: How To Implement Agile Workflows For Analytics & Machine Learning
Jonathan Bechtel	Behind the Black Box: How to Understand Any ML Model Using SHAP
Juan Luis Cano Rodríguez	Document your scientific project with Markdown, Sphinx, and Read the Docs
Juan Orduz	Exploring Tools for Interpretable Machine Learning
Jules S. Damji	Feature Stores: An operational bridge between machine learning models and data
Julia Kodysh	Data infrastructure at the COVID Tracking Project
Julien Herzen	Darts for Time Series Forecasting
Jun Liu	Fugue Tune: A Simple Interface for Distributed Hyperparmeter Optimization
Kalyan Munjuluri	Machine Learning Lifecycle Made Easy with MLflow
Kalyan Prasad	Neural Prophet – A powerful AI framework for Time Series Models
Karishma Babbar	Machine Learning Lifecycle Made Easy with MLflow
Kevin Anderson, Mark Mikofski, Abhishek Parikh, Silvana Ovaitt	Data and tools to model PV Systems
Kevin Duisters	Wisdom of the Crowd: amplifying human intelligence with AI
Kevin Jahns	Collaborative editing in Jupyter Notebook
Kevin Kho	An Intro to Workflow Management with Prefect, Simplifying Testing of Spark Applications
Kevin Stumpf	Snowflake and Tecton: How to build production-ready machine learning pipelines
Kirstie Whitaker	Building Responsible Data Science Workflows: Transparency, Reproducibility, and Ethics by Design
Kjell Wooding	Makefiles: One great trick for making your conda environments more managable.
Laura Jehl	Analyzing Company Filings for Stock Selection – a Practical Report
Layne Sadler	AIQC; deep learning experiment tracking with multi-dimensional pre/post-processing.
Liron Faybish (Ben-Kimon)	Keeping sensitive data safe using recommendation systems
Logan Kilpatrick	The importance of non-code open source contributions, Lightning Talks
Lucy Jiménez	Analyzing gender based violence data with Python
Madhur Tandon	JupyterLite: Jupyter ❤️ WebAssembly ❤️ Python
Magdalena Wiercioch	Deep learning-aided drug discovery
Malte Tichy	What could possibly go wrong when evaluating forecasts?
Manojit Nandi	Assessing and Mitigating Unfairness in AI Systems
Marcin Mosiolek	Deep Neural Deduplication
Marco Edward Gorelli	Let's Implement Bayesian Ordered Logistic Regression!, Run any Python code quality tool on a Jupyter Notebook!, Lightning Talks
Marek Suppa	Adapters: A neat (and production-enabling) trick for multi-task and multi-lingual NLP, Lightning Talks
Mark Keller	Snowflake & Dask: How to scale workloads using distributed fetch capabilities
Markus Löning	sktime - A Unified Toolbox for Machine Learning with Time Series
Martin Durant	All you need is zarr.: Parallel access to remote HDF5, TIFF, grib2 and others., Data Processing at Scale
Martin Renou	JupyterLite: Jupyter ❤️ WebAssembly ❤️ Python
Martin Wanjiru	A first step from ad-hoc SQL to scalable ETL
Matthew Powers	5 Reasons Parquet files are better than CSV for data analyses, Data Processing at Scale
Max Ghenis	Fusing economic survey datasets with the synthimpute Python package
Meenal Jhajharia	Football Analytics Using Hierarchical Bayesian Models in PyMC
Megan Yow	Simplifying Testing of Spark Applications
Meirav Ben Izhak	Storytelling With Data – How To Turn a Basic Dataset Into a Compelling Story
Meredydd Luff	From Jupyter Notebook to Production Web App, with Anvil and (only) Python
Meshva Patel	Data Analytics in Healthcare, Lightning Talks
Michael Sonntag	gin@home: run your own research data management platform, Lightning Talks
Mika Pflüger	gin@home: run your own research data management platform, Lightning Talks
Mike McCarty	Legate Pandas: Scaling the Python ecosystem
Miki Tebeka	Lightning Talks, Using IPython as Presentation Tool, Lightning Talks
Milecia McGregor	Using Reproducible Experiments To Create Better Machine Learning Models
Miles Adkins	Snowflake and Tecton: How to build production-ready machine learning pipelines, Snowflake & Dask: How to scale workloads using distributed fetch capabilities
Mitali Sanwal	Getting started with Dask using Saturn Cloud, Getting started with Dask using Saturn Cloud
MUSASIZI FRANCIS KAMANZI	Image(face) Classification with Computer Vision and Python
Nabanita Roy	Getting Started with Text Classification: Predict if Tweets are about Real Disasters
Neel Surya	An online pedagogical tool for data science using Bokeh, Lightning Talks
Nguyễn Gia Phong	Towards Collaborative Reproducibility: Pinning Repository of Binary Distributions
Nicolas Kruchten	Why Interactive Data Visualization Matters for Data Science in Python, Python Dashboarding Shootout and Showdown
Nicolo Musmeci	Modelling and data visualisation for commodity trading, Lightning Talks, Lightning Talks
Nidhin Pattaniyil	Deploying a Mobile App on Tensorflow: Lessons Learned, Serving BERT Models in Production with TorchServe
Niels Bantilan	Robust, End-to-end Online Machine Learning Applications with Flyte, Pandera and Streamlit
Nik Agarwal	Best of Both Worlds: R & Python, Lightning Talks
Nimrita Koul	Data Analysis with Pandas and NumPy
Nir Barazida	📚 Notebook To Production 👷🏼
Olga Bane	Predictive modeling in a video advertising marketplace
Oliver Gindele	ML in Production – Serverless and Painless
Oliver Rieger	Machine learning in health: Predicting pregnancy complications
Omri Fima	Components, Workflows, and Cookbooks - Building Medical Grade AI pipelines with Argo Workflows
Oyidiya Oji	Tech for Posterity. Challenges for the Future of AI Ethics and DEI
Paco Nathan	Graph Thinking
Paul Klinger	Image classification in retail: Lessons from the real world
Philipp Rudiger	Build polished, data-driven applications directly from your Pandas or XArray pipelines, Python Dashboarding Shootout and Showdown
Pranav Kompally	Project Nirvana : A Podcast Summariser, Lightning Talks
Prasanna Sattigeri	Uncertainty Quantification 360: A Hands-on Tutorial
Quan Nguyen	Making the Perfect Cup of Joe: Active Preference Learning and Optimization Under Uncertainty
Rachel shalom	Deep Learning for Tabular Data
Raghuram Thiagarajan	An online pedagogical tool for data science using Bokeh, Lightning Talks
Ramiro Caro	What to do when you can't trust your labels? A practical approach
Reshama Shaikh	Deploying a Mobile App on Tensorflow: Lessons Learned
Richard Zamora	Data Processing at Scale
Ritchie Vink	Polars, the fastest DataFrame library you never heard of.
Robert Meyer	Lessons learned from deploying Machine Learning in an old-fashioned heavy industry
Rongpeng Li (Ron)	Can the “Best” Language Model Detect Logical Fallacies?, Lightning Talks
Ross Hart	Building linear programs with ORTools
Ruben Mak	Some Attention for Attenuation Bias
Ryan Soklaski	hydra-zen: Configurable, Reproducible, and Scalable Computing with Hydra, MyGrad: Drop-in automatic differentiation for NumPy, Lightning Talks
Sandhya Prabhakaran	Sparcle: assigning transcripts to cells in multiplexed images
Sanket Verma	PyData Meetup Organisers Social
Sarah Krasnik	Dev, Staging, and Production in Data Engineering with Terraform
Sarah Schuhegger	Automatic body part recognition for medical images with python, Lightning Talks
Sara Stoudt	Building Responsible Data Science Workflows: Transparency, Reproducibility, and Ethics by Design
Sara Tähtinen	Computer vision and xAI: explaining a single prediction with visualisations and examples
Sebastian Lautz	Extracting complements and substitutes from sales data - a network perspective
Sebastian M. Ernst	Amazing things your (Unix) operating system can do for you: POSIX shared memory, Lightning Talks
Sergii Mikhtoniuk	Time: The most misunderstood dimension in data modelling
Seth Shelnutt	Extending Jupyter Data Visualizations Beyond the Notebook
Shagun Sodhani	Profiling and Tuning PyTorch Models
Shashank Shekhar	Counter Factual Analysis for Explainable AI
Shivay Lamba	Tensorflow For the Web : Converting Python Machine Learning Models to Javascript using TFJS Converte, Lightning Talks
Simona Maggio	Lightning Talks, Stress Test Center: moving the stress from the user to the model
Sin-seok SEO	Know Your Data First: An Introduction to Exploratory Data Analysis
Sivan Biham	Wounds Over Time - Tracking Wound Healing via 3D Models
Smriti Singh	NLP and Hate speech: Why does it matter and what can we do?
Sofia Hörberg	Computations as Assets - a New Approach to Reproducibility and Transparency
Soumya Ghosh	Uncertainty Quantification 360: A Hands-on Tutorial
Stavros Papadopoulos	TileDB and the New Data Economics
Steven Kolawole	Building a Sign-to-Speech prototype with TensorFlow and DeepStack: How it happened & What I learned
Suliman Sharif	Using a Pythonic Compass to Link the Physics Community to the Chemistry Community
Sune Debel	Functional, Composable, Asynchronous, Type-Safe Python
Svea Marie Meyer	Sktime - a Unified Toolbox for Machine Learning with Time Series Data, Lightning Talks, Lightning Talks
Sven Mika	Large-Scale Production Reinforcement Learning with RLlib
Sylvain Corlay	Python Dashboarding Shootout and Showdown
Sylvia Lee	Bridging Data and Business: Power Plant Output Optimization Based on Electricity Market Price, Digital Hub™ Platform : An Innovative Data Science Toolkit
Temiloluwa Adeniyi	So Much Data, Such Poor Quality
Thibault Lestang	Building Responsible Data Science Workflows: Transparency, Reproducibility, and Ethics by Design
Thorsten Beier	JupyterLite: Jupyter ❤️ WebAssembly ❤️ Python
Timo Metzger	What's new in Bokeh 2.4, Lightning Talks
Timothy Odom	An online pedagogical tool for data science using Bokeh, Lightning Talks
Tomás Capretto	Bambi: A new library for Bayesian modeling in Python., Lightning Talks
Tom Augspurger	Scalable Sustainability with the Planetary Computer
Tonya Sims	Faceoff Fun with Python Frameworks: FastAPI vs Flask 2.0
Usman Kamran	The Need for Modular Data Science Solutions, Lightning Talks
Utkarsh Mishra	Python and Flutter application for Colouring and Enhancing Old Photos
Valentina Bono	Image classification in retail: Lessons from the real world
Valentin Danchev	Building Responsible Data Science Workflows: Transparency, Reproducibility, and Ethics by Design
Vasu Sharma	Simplification as a Service
VELEZ RUEDA ANA JULIA	Analyzing gender based violence data with Python
Vicente Ruben Del Pino Ruiz	Introduction to Quantum Computing with Python and Qiskit
Vini Jaiswal	Data Engineering for successful Machine Learning
Violeta Misheva	Pragmatic Advice for Implementing Responsible Machine Learning: Technical and Organizational Best Pr, Lightning Talks
Wojtek Kuberski	How to detect silent model failures?
Xiuwen Tu	Best approximation of pi - an investigation with Python, Lightning Talks
Xu Chen	An online pedagogical tool for data science using Bokeh, Lightning Talks
Yacine Jernite	Building Responsible Data Science Workflows: Transparency, Reproducibility, and Ethics by Design
Yatin Bhatia	Best Practices in Machine Learning Observability
Yuan Tang	Towards Cloud-Native Distributed Machine Learning Pipelines at Scale (pre-recorded)
Zachary Blackwood	Automatic Pattern-Based Data Catalogs, Lightning Talks
Zayd Ma	Packaging PyData for Enterprise Software Supply Chain (pre-recording)