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Mathias Lécuyer
Trustworthy AI
Privacy In AI
Robustness In Machine Learning
Explainability In AI
Causality In AI
About
I am an assistant professor at UBC in Vancouver, where I am part of the ML, system, and S&P groups, as well as CAIDA and TrustML. I am also Head or Research at Wiremind. Prior to this, I was a postdoctoral researcher at Microsoft Research NY, and completed my PhD at Columbia University. I work on trustworthy AI, on topics ranging from privacy, robustness, explainability, and causality, with a specific focus on applications that provide rigorous guarantees.
Research Performance Summary
2013-2026
Active Research Span
First Recorded Paper
Dispatch: Secure, resilient mobile reporting
Year:
2013
Citations:
2
Venue:
ACM SIGCOMM Computer Communication Review 43 (4)
Latest Recorded Paper
Natural Privacy Filters Are Not Always Free: A Characterization of Free Natural Filters
Year:
2026
Citations:
0
Venue:
arXiv preprint arXiv:2602.15815
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.
Publication Venues and Collaboration
Journal, Conference, and Book Publication Breakdown
Top Coauthors
Lécuyer
Geambasu
Research Impact by Period
Papers
8
Citations
12
Avg. Citations / Paper
1.5
H-Index
2
Papers
19
Citations
321
Avg. Citations / Paper
16.9
H-Index
10
Papers
12
Citations
1668
Avg. Citations / Paper
139
H-Index
8
Papers
3
Citations
171
Avg. Citations / Paper
57
H-Index
2
Contact and Professional Links
Detected Research Keywords
Privacy Budget Scheduling
Privacy Filters Odometers
Differentially Private Learning
Enhancing Selectivity Big
Selectivity Big Data
Adaptive Randomized Smoothing
Randomized Smoothing Certified