Jose Storopoli

Associate Professor and Researcher of the Department of Computer Science at Universidade Nove de Julho - UNINOVE located in São Paulo - Brazil. Lead on Education and Training at Pumas-AI.

Teaches undergraduate and graduate courses in Data Science, Statistics, Bayesian Statistics, Machine Learning and Deep Learning using Julia, R, Python, and Stan. Contributor to Julia, R and Stan ecosystems. Proficient in C/C++ and Rust. Has published Julia, Rust, R, and Python packages in official repositories/registries.

Researches, publishes and advises PhD candidates on topics about Bayesian Statistical Modeling and Machine Learning applied to Decision Making. Principal Investigator of LabCidades - Smart City Research Lab at UNINOVE.

Coauthor of Julia Data Science book. Leads the development of education and training materials for Pumas users in Julia. Member of the Stan Governing Body - SGB. Member of the Turing.jl Developer Team. Certified RStudio Tidyverse Instructor.

Talks:

13:20 UTC

TuringGLM.jl: Bayesian Generalized Linear models using @formula

07/28/2022, 1:20 PM — 1:30 PM UTC
Red

TuringGLM makes easy to specify Bayesian Generalized Linear Models using the formula syntax and returns an instantiated Turing model.

Example:

@formula(y ~ x1 + x2 + x3)

Heavily inspired by brms (uses RStan or CmdStanR) and bambi (uses PyMC3).

Platinum sponsors

Julia ComputingRelational AIJulius Technology

Gold sponsors

IntelAWS

Silver sponsors

Invenia LabsBeacon BiosignalsMetalenzASMLG-ResearchConningPumas AIQuEra Computing Inc.Jeffrey Sarnoff

Media partners

Packt PublicationGather TownVercel

Community partners

Data UmbrellaWiMLDS

Fiscal Sponsor

NumFOCUS