27-28 March 2024, sponsored by the Acceleration Consortium and Merck KGaA

Event timeline

27 March 2024
Applications close
27-28 March 2024
Hackathon date

With the completion of a 2-day virtual hackathon hosted by scientists from the Acceleration Consortium and Merck KGaA on 27-28 March 2024, we thank participants for exploring, collaborating, innovating, and contributing to the advancement of Bayesian optimization for the physical sciences.

During the hackathon, researchers had the opportunity to select or develop Bayesian optimization algorithms and apply them to benchmarking tasks, design new benchmark tasks, create instructional tutorials, describe real-world applications, and more. The results of this collaborative effort will be collated and presented in a scholarly article(?).

Although the event has concluded, the outputs from the hackathon, including applied and developed algorithms, benchmarks, and tutorials, will continue to serve as valuable resources for the research community. Outputs from teams that have opted to release their projects are available at https://github.com/AC-BO-Hackathon or through their own accounts (see individual project pages for links). We believe that through this event, new connections have been formed, new skills have been acquired, and new ideas have been inspired.

We want to express our gratitude to all the participants for their contributions, and we look forward to future collaborations in advancing Bayesian optimization in chemistry and materials science.


We’d like to congratulate the following teams for their outstanding contributions to the hackathon! The top-ranked(?) projects from the showcase and judging session are as follows:

Rank Project # Team Name Project Name
1st Project 23 Noisy Nerds Reliable Surrogate Models of Noisy Data
2nd Project 34 BOMS Prob Streamlining Material Discovery - Bayesian Optimization in Thermal Fluid Mixtures
3rd Project 7 Surface Science Syndicate BayBE One More Time - Exploring Corrosion Inhibitors for Materials Design
4th Project 5 KLM Comparing Bayesian Optimization Methods Across Multiple Hyperparameters Against Simulated “Human” Decision-making
5th Project 8 Molecular Representation BO for Drug Discovery-What is the role of molecular representation?
6th Project 9 PME No Hikari Optimizing The CO2 Adsorption Capacity of Metal-Organic Frameworks Using Thompson Sampling
7th Project 11 BlenDS BlendDS - An intuitive specification of the design space for blends of components
8th Project 30 SERO Opt Active learning for voltammetry waveform design
9th Project 45 General Optimizers Bayesian Optimization for Generality
10th Project 3 Sparks Group Take Your Time - Measuring Optimization Performance as a Function of ACQF Optimizer Runtime

For a full list of hackathon projects, we encourage you to check out the projects page.


The Acceleration Consortium @ University of Toronto Merck KGaA

Prize Sponsor

Matterhorn Studio