Short Bio

Esther Heid is an Assistant Professor for Machine Learning for Sustainable Chemistry in the Faculty of Technical Chemistry, TU Wien, Austria, and head of the TU-wide dataTUdiscovery AI/ML service center. She received her Ph.D. in Theoretical Chemistry from the University of Vienna in 2019. She subsequently held postdoctoral positions at MIT (2020–2022) and TU Wien (2022–2024), where she advanced her work at the interface of chemistry and machine learning. In 2024, she was awarded a prestigious ERC Starting Grant, which supported her promotion to tenure-track Assistant Professor at TU Wien. Her research group focuses on deep learning approaches for chemical reactions, with an emphasis on predicting reaction properties and pathways across gas-phase, organocatalytic, and biocatalytic systems, as well as developing new generative approaches for chemical reactions.

Prizes, Awards, Memberships

Esther Heid was awarded the Karl Schlögl Award of the Austrian Academy of Sciences, the Loschmidt Award of the Chemical-Physical Society of Vienna, and the Award of Excellence of the Federal Ministry of the Republic of Austria for her PhD thesis. She was furthermore named a Rising Star in Chemical Engineering at MIT, won the Best Lecture Award from TU Wien, and received several prestigious fundings and fellowships, amongst others a ÖAW DOC Fellowship (2017-2019), FWF Schrödinger Fellowship (2020-2023), FWF START grant (2024-2027), ERC Starting Grant (2024-2029), and is Co-PI on an FWF SFB and FFG BRIDGE project.

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