🧪🤖 New paper in Nature Computer Science! What if you could design, test, and refine automated chemistry workflows before touching the lab? We present “MATTERIX: toward a digital twin for robotics-assisted chemistry laboratory automation”. 🔗 www.nature.com/articles/s43... [1/6]

We are delighted to announce that our perspective article, “Steering towards safe self-driving laboratories (SDLs),” has been accepted for publication in Nature Reviews Chemistry. Link: www.nature.com/articles/s41...

Day 2 presenters: Shi Xuan Leong Yuchi (Allan) Zhao @allanzhao.bsky.social Ella Ashoori Ella Rajaonsen Ishrath Mohamed Irshadeen Day 3 presenters: Alán Aspuru-Guzik @aspuru.bsky.social Sean Park Marcel Müller Yunheng (Jackie) Zou Luis Mantilla Calderón @realmantilla.bsky.social [2/2]

🤖 We introduce AnyPlace, a two-stage method trained entirely on synthetic data to predict a wide range of feasible placement poses for real-world scenarios. [2/5]

Excited to share our latest work on leveraging quantum–classical generative models for small-molecule design, specifically targeting KRAS inhibitors for cancer therapy. [1/4]

Excited to have #selfdrivinglaboratories listed as one of the seven technologies to watch in 2025 by @nature.com Thanks to the #matterlab, the @accelerationc.bsky.social and of course all the global community on SDLs! @uoft.bsky.social @vectorinst.bsky.social l www.nature.com/articles/d41...

Excited to share our latest work on object placement for robot manipulation, AnyPlace! 🚀 A two-stage method that predicts diverse placement poses for objects in the real world - trained entirely on synthetic data. Big thanks to all my collaborators! Check out the full post for more details👇.