Pedro O. Pinheiro

I am a research scientist at Genentech, Prescient Design team.

Previously, I was a research scientist at Deep Genomics and Element AI (where I work closely with people from Mila). I received a Ph.D. from École Polytechnique Fédérale de Lausanne (EPFL) and Idiap Research Institute (Switzerland), under supervision of Ronan Collobert. During my phd, I also spent time at Facebook AI Research (FAIR). Previously, I graduated with a MSc. in Image and Signal Processing from Institut National des Sciences Appliquées de Lyon (INSA), in France. I am originally form sunny Fortaleza, Brazil.

Email | LinkedIn

Research

I am interested in machine learning and its applications, specifically deep learning methods for representation learning and generative modeling. Currently, I am interested in developing AI methods that can tackle complex scientific problems, such as molecular sciences and drug discovery.

Below is a list of some recent highlighted work. For a full list of publications, please see my Google Scholar page.

	Implicit generative property enhancer Pedro O. Pinheiro, Pan Kessel, Aya A. Ismail, Sai P. Mahajan, Kyunghyun Cho, Saeed Saremi, Nataša Tagasovska NeurIPS, 2025 paper \| code (coming soon)
	Unified all-atom molecule generation with neural fields Matthieu Kirchmeyer^, Pedro O. Pinheiro^, Karolis Martinkus, Emma Willett, ..., Richard Bonneau, Saeed Saremi NeurIPS, 2025 (^*equal contribution) paper \| code (coming soon)
	Score-based 3D molecule generation with neural fields Matthieu Kirchmeyer^, Pedro O. Pinheiro^, Saeed Saremi NeurIPS, 2024 (^*equal contribution) paper \| code
	Structure-based drug design by denoising voxel grids Pedro O. Pinheiro, Arian Jamasb, Omar Mahmood, Vishnu Sresht, Saeed Saremi ICML, 2024 paper \| code
	3D Molecule generation by denoising voxel grids Pedro O. Pinheiro, Joshua Rackers, Joseph Kleinhenz, Michael Maser, Omar Mahmood, Andrew Martin Watkins, Stephen Ra, Vishnu Sresht, Saeed Saremi NeurIPS, 2023 paper \| code
	DyAb: sequence-based antibody design and property prediction in a low-data regime Joshua Yao-Yu Lin, Jennifer L. Hofmann, Andrew Leaver-Fay,..., Pedro O. Pinheiro,..., Andrew Watkins, Kyunghyun Cho, and Nathan C. Frey bioRxiv, 2025 paper
	An RNA foundation model enables discovery of disease mechanisms and candidate therapeutics Albi Celaj, Alice Jiexin Gao, Tammy T.Y. Lau, Erle M. Holgersen, ..., Pedro O. Pinheiro, ..., Brendan J. Frey bioRxiv, 2023 paper