91AV

Yuya Oaki is an Associate Professor of Department of Applied 91AV, Keio University, Japan. His research interest is layered materials, 2D materials, and conjugated polymers for their energy and sensing applications. He has studied data-driven approach for small data, such as experimental and literature data, since he worked as a project member of materials informatics (JST PRESTO, 2016–2020). He was awarded The Chemical Society of Japan Award For Young Chemists and The Young Scientists’ Prize of The Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology.

Associate Professor Emma Schymanski is head of the Environmental Cheminformatics (ECI) group at the Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg. In 2018 she received a Luxembourg National Research Fund (FNR) ATTRACT Fellowship to establish her group in Luxembourg, following a 6 year postdoc at Eawag, the Swiss Federal Institute of Aquatic Science and Technology and a PhD at the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany. Before undertaking her PhD, she worked as a consulting environmental engineer in Perth, Australia. She is involved in many collaborative efforts, with over 100 publications and a book. Her research combines cheminformatics and computational (high resolution) mass spectrometry approaches to elucidate the unknowns in complex samples, primarily with non-target screening, and relate these to environmental causes of disease. An advocate for open science, she is involved in and organizes several European and worldwide activities to improve the exchange of data, information and ideas between scientists to push progress in this field, including NORMAN Network activities (e.g. NORMAN-SLE, MassBank, MetFrag and PubChemLite for Exposomics.

Sukriti Singh received her M.Sc. and PhD degrees from the Indian Institute of Technology Bombay in 2022 under the supervision of Prof. Raghavan B. Sunoj. The work carried out in her graduate studies involves mechanistic insights into some of the important regio- and stereo-selective catalytic reactions using density functional theory (DFT) computations. It also includes the potential applications of machine learning (ML) in chemistry for the reaction outcome prediction. She is presently working as a postdoctoral research associate with Prof. J. M. Hernandez-Lobato at the University of Cambridge. Her research interests include developing ML methods to tackle low-data situations and to accelerate the exploration of chemical reaction space of high contemporary interest.

Prof. Zhu Xi obtained his bachelor's degree in physics from the University of Science and Technology of China (USTC) in 2006, and Ph.D. at Nanyang Technological University (NTU), Singapore, in 2011. He joined The Chinese University of Hong Kong, Shenzhen in 2017, and holds a position as deputy director at the Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS). His research interests focus on the application of condensed matter physics theory in interdisciplinary research. His current research focuses on the AI application in materials science and pharmacy, he leads the development of the on-demand and in-cloud materials synthesis platform scheme “MAOSIC” based on intelligent robots and cloud computing;  and developed the blockchain technology endorsed automatic experimental platform (BiaeP) for unforgettable experimental data.  Promoting the digitalization of materials science in AI era.