HANAMI High-Level Symposium | 3rd Edition

Deborah Prezzi is a senior researcher at CNR-NANO in Modena, Italy. Her research focuses on the theoretical and computational modelling of materials, with particular emphasis on the connection between atomistic structure, electronic properties, spectroscopy, and functional behaviour. Over the years, she has worked on a broad range of low-dimensional and nanoscale systems, including carbon-based nanostructures, two-dimensional materials, and optoelectronic materials, often in close interplay with experimental spectroscopy. More recently, her interests have expanded to energy-storage materials, where automated atomistic simulations, data-generation workflows, and machine-learning approaches can provide new insights into complex electrochemical processes. In this direction, her work aims to combine physically grounded simulations with data-driven methods to interpret spectroscopic fingerprints and understand degradation, lithiation, and interfacial phenomena in battery materials.

Talk: Machine-learned spectroscopy for silicon batteries: from automated workflows to chemical insight

Katsuhisa Ozaki is a Professor in the Department of Mathematical Sciences at Shibaura Institute of Technology. He received his Ph.D. in Engineering from Waseda University in 2007. He was an Assistant Professor at Waseda University from April 2007 to March 2008, and a full-time Visiting Lecturer from April 2008 to March 2010. At Shibaura Institute of Technology, he served as an Assistant Professor from April 2010 to March 2013 and as an Associate Professor from April 2013 to March 2019, and has been a Professor since April 2019. His research interests include reliable computing, with a particular focus on rounding error analysis in finite-precision arithmetic. His main research area is numerical linear algebra, where he develops fast and accurate algorithms for reliable scientific computing.

Talk: Accuracy-Tunable Matrix Computation Using Low-Precision Arithmetic: Ozaki Schemes and Applications

Mariko Okada is a Professor at the Institute for Protein Research, The University of Osaka, Japan, where she has been conducting research in cancer systems biology since 2016. She also served as Provost’s Visiting Professor of Systems Biology at Imperial College London, UK (2024–2025). Prior to joining The University of Osaka, she was a scientist and team leader at the RIKEN Institute (2000–2016), where she worked at the Genomic Sciences Center (GSC), the Research Center for Allergy and Immunology (RCAI), and the Center for Integrative Medical Sciences (IMS). Her research focuses on understanding how cancer signaling networks regulate cell fate decisions by integrating mathematical modeling, multi-omics analysis, and experimental approaches. Her group also develops computational methods for systems biology and has recently been exploring the application of natural language processing (NLP) and deep learning (DL) to mathematical modeling, enabling the development of disease-specific virtual patient models.

Talk: Bridging AI and Systems Biology to Build Virtual Patients for Precision Medicine