|
|
# 2025 ChemAutoML: Open Chemistry |
|
ChemAutoML is an open-source platform that automates the development of machine learning models for pharmaceutical chemistry. By removing the need for coding expertise, it empowers researchers to accelerate drug discovery, including for neglected diseases. The tool generates predictive models and explainability visualisations, making results more transparent and actionable. Recent tests show its performance matches or exceeds expert-built models. With new features and upcoming publication, ChemAutoML is poised to democratize AI use in drug development worldwide
João Lucas Rodrigues Constantino is a PhD candidate in Computer Science and Computational Mathematics at the University of São Paulo, where he also earned his BSc in Computer Science. Initially drawn to Natural Sciences, he chose this field of study in order to explore simulations of complex systems. His research soon centered on Artificial Intelligence, particularly AutoML and XAI. Since 2023, he has contributed to AutoAI-Pandemics, a project under AI4PEP, focused on AI solutions for Global Health. In 2025, he earned an honorable mention for his thesis and third place at AI4GHI for his project on drug repurposing against Dengue.more
Full Professor since 2006 and currently Director since 2022 of the Institute of Mathematical and Computer Sciences at the University of São Paulo (ICMC-USP), São Carlos Campus, Research Productivity Fellow 1A of CNPq. He coordinates the IARA network, Artificial Intelligence Recreating Environments. He leads the WG12.2 Working Group on Machine Learning and Data Mining of the International Federation for Information Processing (IFIP). He served as Vice-President of the Brazilian Computer Society (SBC) from 2019 to 2023, member of the CNPq Computer Science Advisory Committee (CA-CC) from 2018 to 2021 (coordinator from 2019 to 2020). From 2013 to 2017 he was a member of the council of the International Association for Statistical Computing (IASC), of the International Statistical Institute (ISI). His main research interests are Machine Learning, Data Mining, and Data Science, with applications in various fields. He has published several papers in these areas, some of which have been awarded at conferences organized by ACM, IEEE, and SBC. He has written several books, including "Artificial Intelligence: A Machine Learning Approach", published by GrupoGen in 2011 and winner of the Jabuti Award 2012, and "A General Introduction to Data Analytics", published by Wiley in 2018. more
Portfolio LinkedIn
University of Illinois at Urbana-Champaign
Low-cost neurosurgical navigation for life-saving brain procedures
Minimally invasive radiotherapy for liver and solid tumours
University of California, Los Angeles
Internal radiotherapy with stabilising bladder balloon
