Three days of lectures, workshops and conversations at IME-USP, bringing together mathematicians, statisticians and AI researchers to examine the mathematical foundations beneath the recent successes of artificial intelligence — successes which are almost as impressive as they are poorly understood.
Speakers
The list below is provisional — the full programme will be announced soon.
Prof. Rafael Izbicki
UFSCAR – São Carlos
Title: “Uncertainty Quantification: The Mathematics Behind Reliable AI”
Prof. Paola Bermolen
Universidad de la República – Montevideo
Prof. Mauricio Velasco
Universidad de la República – Montevideo
Title: “To be announced”
Prof. Joaquin Fontbona
Universidad de Chile – Santiago
Title: “To be announced”
Prof. Paulo Oreinstein
IMPA – Rio de Janeiro
Title: “Robust and Efficient Mean Estimation via Soft Shrinkage”
Prof. Thiago Ramos
UFSCAR- São Carlos
Title: “Functional Newton Methods for Operator Learning”
Prof. Marcelo Finger
IME – USP
Title: “Formally Verifying Neural Networks Properties using Łukasiewicz Logic”
Prof. Hamed Yazdanpanah
IME – USP
Title: “Foundation Modelsfor Time Series Analysis: Foundations, Methods, and Open Challenges”
Prof. Nina S. T. Hirata
IME – USP
Title: “Inductive Bias in Deep Learning Models”
Prof. Tom Hanika
University of Kassel
Title: “Concentration of Measure Meets Machine Learning: Intrinsic Dimension from Gromov to Graph Neural Networks”
Scientific Comittee
- Florencia Leonardi / USP – São Paulo
- Hedibert Freitas Lopes / INSPER – São Paulo
- Roberto Imbuzeiro Oliveira / IMPA – Rio de Janeiro
Organizing Comittee
- Aline Duarte / USP – São Paulo
- Florencia Leonardi / USP – São Paulo
- Morgan André / USP – São Paulo
Support staff
- Lourdes Vaz da Silva / USP – São Paulo
- Renata Stella Khouri / USP – São Paulo
- Liena Valero Bello / USP – São Paulo
- Arthur Henrique Dias Rodrigues / USP – São Paulo
- Matheus Teixeira / USP – São Paulo
inct.events@ime.usp.br