Modern Experimental Design and Active Learning in the Real World

This website aims to be a resource for researchers from academia and industry to understand major challenges, outline recent advances, and highlight promising future directions in the areas of real-world experimental design and active learning. We organize a workshop series and an online reading group.

Overview

Whether in robotics, protein design, or physical sciences, one often faces decisions regarding which data to collect or which experiments to perform. There is thus a pressing need for algorithms that make intelligent decisions about data collection processes that allow for data-efficient learning. Experimental design and active learning have been major research topics within both machine learning and statistics communities.

This website aims to highlight new and emerging research opportunities that arise from the need make experimental design and active learning procedures that are effective in realistic applications. Progress in this area has the potential to provide immense benefits in emerging high impact applications, such as materials design, drug discovery, algorithm configuration, crowdsourcing, citizen science, computational biology, AutoML, robotics, reinforcement learning, and more.

Workshop Series

NeurIPS 2023: Adaptive Experimental Design and Active Learning in the Real World.
ICML 2022: Adaptive Experimental Design and Active Learning in the Real World.
ICML 2020: Workshop on Real World Experiment Design and Active Learning.

Online Reading Group

We are holding an online reading group focusing on modern adaptive experimental design and active learning in the real world. All interested participants are welcome to join!

The reading group will be held on Thursdays at 11am PDT/California, 6pm GMT/UK, 7pm CET/Zurich time. To add this to your calendar, click here. To receive information via email, subscribe to our mailing list.

To join, please use the following Zoom link: https://ethz.zoom.us/j/67585775251