Cristian Muñoz Villalobos has a diverse work experience spanning multiple years. Cristian currently holds the role of Senior Researcher and ML Engineer at Holistic AI since 2022. Prior to this, they worked as a Professor at CCE - PUC-Rio from 2016, where they taught Machine Learning methods, Big Data technology, and distributed systems. From 2012, Cristian worked at ICA PUC-Rio as an ML Researcher and Software Developer, focusing on a wide range of areas such as Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, and Big Data applications. Cristian also interned at Petrobras in 2019 as a Research Intern. Before that, they worked at FAMETAL from 2010 to 2012, where they were involved in automation and software development for the production line.
Cristian Muñoz Villalobos completed their education as follows:
- From 2015 to 2019, they attended Pontifícia Universidade Católica do Rio de Janeiro and obtained a Doctor of Philosophy (PhD) in Decision Support Methods in the field of Electrical Engineering.
- From 2012 to 2014, they also attended Pontifícia Universidade Católica do Rio de Janeiro and earned a Master of Engineering (M.Eng.) degree in Decision Support Methods.
- Between the years 2005 and 2010, Cristian attended the National University of Engineering and received a degree in Ing. Mecatrónico with a specialization in Artificial Intelligence.
In addition to their formal education, Cristian has also obtained various certifications. These include:
- Google Cloud Fundamentals: Core Infrastructure from Coursera | Google in April 2022.
- Implementando un motor con Alibaba Cloud y ElasticSearch from Coursera in April 2021.
- Fundamentos da Transformação Digital from LinkedIn in March 2021.
- Introduction to GPT-3: A Leap in Artificial Intelligence from LinkedIn in March 2021.
- Introdução à Governança de Dados from LinkedIn in March 2021.
- RESTful API with HTTP and JavaScript from Coursera (exact completion month not specified) in 2021.
- Sequences, Time Series and Prediction from Coursera in May 2020.
- TensorFlow in Practice from Coursera in May 2020.
- Natural Language Processing in TensorFlow from Coursera in April 2020.
- Convolutional Neural Networks in TensorFlow from Coursera in March 2020.
- Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning from Coursera in March 2020.
- Convolutional Neural Networks from Coursera in April 2018.
- Deep Learning Specialization from Coursera in April 2018.
- Sequence Models from Coursera in April 2018.
- Fundamentals of Deep Learning for Computer Vision from Qwiklabs in January 2018.
- Structuring Machine Learning Projects from Coursera in October 2017.
- Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization from Coursera in September 2017.
- Neural Networks and Deep Learning from Coursera in August 2017.
- Programming GPUs using CUDA C/C++ from Qwiklabs in April 2017.
- Python Getting Started from Qwiklabs in April 2017.
May, 2022 - present