Xin Dai

Xin Dai is a Research Staff Scientist at the Computational Science Initiative (CSI) within Brookhaven National Laboratory. His work bridges machine learning with scientific domains like computational biology and biomedical risk modeling. At CSI, he focuses on applying AI/ML to complex scientific challenges, particularly in structural biology and biomedical informatics.

Education:

• PhD in Physics, Tsinghua University (2013–2018)
• BS in Physics, Nanjing University (2009–2013)

Research Interests: Using cutting-edge AI/ML techniques to address interdisciplinary problems, with emphasis on:

• Computational biology for atomistic interpretation of cryo-EM maps
• Biomedical risk modeling for cancer survival analysis
• Theoretical condensed matter physics in topological insulators

Key Article Trends: His recent work (2022–2023) explores deep learning applications in structural biology and oncology, while earlier research (2017) focused on quantum materials and electronic transport phenomena.

Current Affiliation: Brookhaven National Laboratory, where he has worked since 2020 after a postdoctoral stint at Ohio State University.