Date & time
3:30 p.m. – 5 p.m.
Tristan Glatard
This event is free
Department of Computer Science and Software Engineering
ER Building
2155 Guy St.
Room 1072
Yes
Computational reproducibility is achieved when a computational result can be recomputed using the same code and data as in the original computation. Computational reproducibility has become a central requirement in many scientific fields, due to the increasing reliance of experimental sciences toward digital data. This seminar will introduce computational reproducibility, present technical solutions currently available to achieve it, highlight remaining issues, and illustrate it with examples from the neuroimaging domain.
Tristan Glatard is Associate Professor in the Department of Computer Science and Software Engineering, Canada Research Chair (Tier II) in Big Data Infrastructures for Neuroinformatics, and co-director of the Concordia Applied AI Institute.
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