Raquel, Afnan, and Lisa participate in the 8th Artificial Intelligence in Chemistry Symposium

As part of the 8th Artificial Intelligence in Chemistry Symposium
(AiChem 8 conference website), Raquel, Afnan, and Lisa participated in both the pre-conference workshop and the main conference, contributing to discussions at the intersection of chemistry, data science, and machine learning.

Raquel, Afnan, Lisa, Andrea and Pat organized the pre-conference workshop, which focused on introducing practical machine learning workflows for chemistry. Lisa introduced the basics of Python and Jupyter notebooks, Raquel presented a hands-on notebook on data curation and cleaning, and Afnan explored molecular representations and machine learning models commonly used in cheminformatics. The workshop lectures and notebooks are publicly available
(GitHub repository).

In the main conference, both Raquel and Afnan presented their research as oral contributions. Raquel presented her ongoing work titled “No Pose Left Behind: Integrating Activity and Structural Data with Uncertainty-Aware Multiobjective Learning for Kinase Inhibitor Prediction”, highlighting methods for combining structural and bioactivity data in predictive modeling. Afnan presented her work on molecular transformers, discussing their applications and evaluation for molecular property prediction tasks (as talk and poster).

Lisa presented a poster on her work on benchmarking of different machine learning models, compound representations and dimension reduction methods on the ToxCast dataset.

We especially enjoyed engaging with the AiChem community and exchanging ideas with researchers working across machine learning, cheminformatics, and data-driven drug discovery.