Bio:

Yiliu Wang joined the Allen Institute in 2023 as a Shanahan Foundation Fellow. At the Allen Institute, she addresses fundamental questions in neuroscience by developing advanced mathematical models that bridge AI and brain research. Her current work focuses on studying neuronal populations as interconnected cell types, investigating their spatial organization, firing patterns, and interactions across different brain states—including loss of consciousness, behavioral tasks, and disease onset.

Yiliu holds a Master’s degree in Mathematics and Statistics from the University of Oxford and a PhD in Statistics from the London School of Economics (LSE), where she was supervised by Prof. Milan Vojnovic. During her doctoral research, she worked on inference, optimization, approximation, and set selection problems in relational learning, a subfield of high-dimensional statistics. She finds neuronal datasets an ideal testing ground for relational learning methods and a source of inspiration for advancing them.