Philippe Schwaller

Philippe Schwaller joined EPFL as a tenure-track assistant professor in the Institute of Chemical Sciences and Engineering in February 2022. He leads the Laboratory of Artificial Chemical Intelligence, which works on AI-accelerated discovery and synthesis of molecules. Philippe is also a core PI of the NCCR Catalysis, a Swiss centre for sustainable chemistry research, education, and innovation. He belongs to a new generation of scientists with a broad set of skills – in his case, a combination of chemistry, materials science, computer science, and experimental research.

Teaching & PhD

Teaching

Chemistry and Chemical Engineering

PhD Students

Agostini Sandro, Armstrong Daniel Paul, Chen Junwu, Guilbert Salomé Marie Alizé, Guo Jeff, Kopf Sarina Nicole, Mansouri Tehrani Sayed Mohammadamin, Marulanda Bran Andres Camilo, Neeser Rebecca Manuela, Neukomm Théo Alain, Rankovic Bojana, Sabanza Gil Víctor, Schilter Oliver Tobias, Sin Wing Pong, Valverde Das Neves Paulo Filipe,

Courses

Practical programming in Chemistry

This course offers a comprehensive, practical introduction to computer programming tailored for chemists and chemical engineers. Python is the main language used throughout the course.

Project of Computational chemistry

This course exploits modern computational tools in a research project aiming at resolving a chemistry problem by group of two students.

AI for chemistry

The AI for Chemistry course will focus on teaching students how to use machine learning algorithms and techniques to analyze and make predictions about chemical data. The course will cover topics such as the basics of machine learning, common algorithms and their applications in chemistry.

AI in chemistry and beyond:Highlights in the field

Should have expertise in chemistry, physics or lite and material sciences. Although a very good knowledge in Al-based algorithms is required to fully understand the technical details, a basic knowledge is sufficient to understand the potential of these methods and their applications

AI in chemistry and beyond: Trends in the field

AI in chemistry and beyond: Success stories

Lecture series on scientific machine learning

This lecture presents ongoing work on how scientific questions can be tackled using machine learning. Machine learning enables extracting knowledge from data computationally and in an automatized way. We will learn on examples how this is influencing the very scientific method.