On February 29th and March 1st, a total of 23 students from various courses including mathematics, physics, chemistry, biology, and environmental science at Nara Women's University (2nd to 4th year undergraduates, 1st and 2nd year master's students) visited different laboratories at RIKEN: the Azuma Laboratory (CPR), the Takeishi Laboratory (CBS), iTHEMS, the RIBF facility, and the Sako Laboratory (CPR). At each laboratory, they had the opportunity to glimpse cutting-edge research, and during the evening exchange sessions with RIKEN researchers, they were able to ask deeper questions about the research topics and learn about the researchers' daily lives.

This diversity promotion activity is part of a joint initiative between the Faculty of Science at Nara Women's University and RIKEN iTHEMS, conducted in conjunction with a series of lectures at Nara Women's University, and is planned to continue in the coming years.

Hello everyone! My name is Lingxiao Wang (王 凌霄). My research ambitiously bridges the fields of machine learning and physics, with a particular focus on using deep learning techniques, such as deep neural networks (DNNs) and generative AI, to explore QCD matter with physics models and lattice calculations. Beyond traditional boundaries, my work extends to pioneering applications of AI for Science, such as the automating scientific discovery, medical AI, and the analysis of collective behavior.

My academic journey in physics commenced with a Ph.D. at Tsinghua University, China(2015-2020), where I investigated quark matter under extreme conditions. Concurrently, I was a visiting Ph.D. student at the University of Tokyo, Japan(2018-2019), focusing on chiral matter. During my postdoctoral position at the Frankfurt Institute for Advanced Studies(FIAS), Germany (2020-2023), I honed my expertise in applying machine learning to physical sciences, and simultaneously held a joint position as a Research Assistant at Insitute of Physics in Goethe University, where I applied machine learning to THz physics. Currently, I am also a Visiting Scholar at the Institute of Modern Physics, Fudan University, China, working on machine learning applications in particle and nuclear physics.

For many years, I have organized a series of "Machine Learning Physics" seminars and learning clubs, providing an inclusive space for scientists interested in AI. I am especially enthusiastic about knowledge sharing and discussions that pave the way for interdisciplinary topics. My door (Main Building 249) is always open for anyone who wants to drink a cup of coffee/tea with me!