Virtual, 12-14 November 2021 (Beijing time), hosted in Xiamen, China.

Deadline for registration and abstract submission extended to 10 November 2021, 23:00 (Beijing time).

The International Symposium on Machine Learning in Quantum Chemistry (SMLQC, mlatom.com/smlqc-2021) will gather the theoretical and computational chemists, who use machine learning to accelerate and improve quantum chemical simulations. The topics of the conference include, but not be limited to, the development of new quantum chemical techniques improved by machine learning, development of new machine learning methods for describing potential energy surfaces and running molecular dynamics, and application of machine learning for description of various physicochemical processes.

SMLQC is a virtual symposium. It has been planned to be held at Xiamen University in person in 2020 and preparation to it started in 2019, but due to the severe pandemic situation, we had to first postpone it and finally make it fully online. We will provide participants with environment facilitating the interaction with each other as in a "real" in-person symposium. We will organize poster sessions and networking activities such as virtual meeting lobby for spontaneous chats, breakout rooms for lively discussions with speakers, chats over coffee breaks, private rooms, etc. (check out the schedule). The symposium is now open for registration (deadline: November 5 November 10).

The symposium is organized and supported by the State Key Laboratory of Physical Chemistry of Solid Surfaces (PCOSS), Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry (FTCC), and College of Chemistry and Chemical Engineering at Xiamen University, China

SMLQC organizers in Xiamen University:

Yi Zhao

Wei Wu

Pavlo O. Dral

Ze-Xing Cao

Peifeng Su