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Say Hello to the 2023 CANSSI Distinguished Postdoctoral Fellows

By , In , In News

Every year, CANSSI selects a number of individuals to become part of its CANSSI Distinguished Postdoctoral Fellowships (CDPF) program.

The program provides a paid, comprehensive two-year training experience that includes a major research project under the joint supervision of professors from two universities, interdisciplinary collaboration, and opportunities for teaching and professional development.

The applicants for 2023 were invited to rank their preferred choices from among 10 research projects submitted by statistical sciences faculty members at Canadian universities.

We are pleased to announce that the following individuals have been selected as CDPF recipients for 2023:

  • William Ruth (Simon Fraser University). William will work on “High-dimensional Hierarchical Models for Infectious Disease Data” under the supervision of Bruno Rémillard (HEC Montréal) and Bouchra Nasri (Université de Montréal).
  • Alex Sharp (University of Waterloo). Alex will work on “Statistical Foundations of Invariant Representation Learning, With Applications to Data-driven Compression and Algorithm Design” under the supervision of Benjamin Bloem-Reddy (University of British Columbia) and Chris J. Maddison (University of Toronto).
  • Chi-Kuang Yeh (University of Waterloo). Chi-Kuang will work on “Semi-supervised Learning for High-dimensional Functional Data Integration with Measurement Error” under Archer Yi Yang and Qihuang Zhang (McGill University) and Peijun Sang (University of Waterloo).

We will be publishing profiles of all recipients and their research projects in the coming months.

CANSSI Ontario Postdoctoral Fellowship in Statistics

For 2023, CANSSI has also partnered with CANSSI Ontario to award a special CANSSI Ontario Postdoctoral Fellowship in Statistics with its own set of candidate research projects.

The recipient of this year’s fellowship is Mai Ghannam (University of Windsor). Mai will work on “Discovery of Extremal Structure for Heavy-tailed Multivariate Time Series” under the supervision of Rafal Kulik (University of Ottawa) and Stanislav Volgushev (University of Toronto).