Research visit(s):

• One-month stay at Isaac Newton Institute for Mathematical Sciences (University of Cambridge) for the RCL programme: Representing, calibrating & leveraging prediction uncertainty from statistics to machine learning

Talks:

• Kernel Trace Distance: Quantum Statistical Metric between Measures through RKHS Density Operators One World Seminar for Mathematics of Machine Learning, jointly hosted at Isaac Newton Institute
• Data depth as Learning Loss at CMSTATS 2024
• Fast kernel half-space depth for data with non-convex supports at ICORS 2024
• Kernel-based extension of the halfspace depth at CMSTATS 2023
• RKHS-based projection depths at COMPSTATS 2022

Posters:

• Hi! PARIS Meet Up! (on AI & Ethics) at Capgemini, Paris
• AQIS’19 Asian Quantum Information Science Conference at Korean Institute of Advanced Studies, Seoul
• QIT41 (Quantum Information Technology Symposium 2019) at Gakushuin University, Tokyo