I am a final year PhD student in Statistics
at Boston University, advised by Professor
Uri Eden and Professor
Emily Stephen.
My research focuses on developing statistical modeling tools to understand the
dynamics of coordinated neural activity across multiple brain areas, track
spatial-temporal changes in functional connectivity, and capture any sources of
linkages and types of phase offsets.
Previously, I earned a BSc in Applied Mathematics in Taiwan and a MS in
Statistics
from
Indiana University - Bloomington, where I was
supervised by Professor
Stanley Wasserman. In the summer of 2023, I worked as a data scientist intern at
Roche Diagnostics.
Contact Info:
Email: whsin [at] bu [dot] edu
Office: CCDS 428
665 Commonwealth Ave
Boston, MA 02215 USA
Research:
I am particularly interested in statistical approaches to network analysis. Previously,
I worked with Professor Stanley Wasserman at Indiana University and focused on statistical
methodologies for social network analysis. After moving to Boston University, I began working
with Professor Uri Eden on statistical methods for analyzing neural activities. I'm supported
by
Simons Foundation -- Simons Collaboration on the Global Brain.
Publications:
W. -C. Hsin, U. T. Eden and E. P. Stephen, "Switching Models of Oscillatory
Networks Greatly Improve Inference of Dynamic Functional Connectivity,"
arXiv:2404.18854, April 2024.
The code for all of the methods described and the simulation studies performed in the paper is
available in a GitHub repo
code repository.
W. -C. Hsin, U. T. Eden and E. P. Stephen, "Switching Functional Network
Models of Oscillatory Brain Dynamics," 2022 56th Asilomar Conference on Signals, Systems,
and Computers, IEEE, Pacific Grove, CA, USA, 2022, pp. 607-612,
doi: 10.1109/IEEECONF56349.2022.10052077.
The code for all of the methods described and the analysis performed in the paper is
publicly available through a
code repository via GitHub.
Talks:
W. -C. Hsin, U. T. Eden and E. P. Stephen, "Switching Functional Network
Models of Oscillatory Brain Dynamics," 2023 Society for Neuroscience @ Washington DC.
Nanosymposium session: Network Analysis and Modeling.
W. -C. Hsin, "Switching Functional Network
Models of Oscillatory Brain Dynamics," The 16th International Conference on Brain
Informatics (BI 2023) @ Hoboken & New York. Invited workshop: Time Domain Analysis of
Neural Oscillations.
W. -C. Hsin, U. T. Eden and E. P. Stephen, "Switching Functional Network
Models of Multiple Rhythms During Anesthesia," 2022 Society for Neuroscience @ San Diego.
Nanosymposium session: Networks - Functional Connectivity and Computation.
W. -C. Hsin, "State-Space Models of Switching Between Functional Networks,"
Simons Collaboration on the Global Brain Remapping, Simons Foundation @ Stanford University, 2022.
W. -C. Hsin, Mathematical Neuroscience Group, Dean's Advisory Board, Center
for Computing and Data Sciences Building Tour with Computer Science and Mathematics & Statistics,
Boston University, March 30, 2023.
Description: Mathematical Neuroscience group applies ideas from mathematics and statistics to characterize
and model brain activity. We undertake interdisciplinary projects with experimental and clinical
collaborators to assess - and perturb - brain function (e.g., how the brain encodes memories) and
brain dysfunction (e.g., how disease impacts brain dynamics).
Teaching:
"Those that know, do. Those that understand, teach." - Aristotle.