Andre Goncalves
About Andre Goncalves
Andre Goncalves is a Research Staff member specializing in Machine Learning at Lawrence Livermore National Laboratory. He holds a Bachelor's degree in Computer Science, a Master's degree in Computer Engineering, and a Ph.D. in Electrical and Computer Engineering, with expertise in various machine learning sub-fields and a focus on uncertainty quantification and model interpretability.
Work at Lawrence Livermore National Laboratory
Currently, Andre Goncalves serves as Research Staff in Machine Learning at Lawrence Livermore National Laboratory. He has been in this role since 2018, contributing to various projects that involve designing machine learning models. His work focuses on creating models that deliver accurate predictions while also providing insights and explanations for scientific phenomena. He previously held the position of Postdoctoral Researcher at the same laboratory from 2017 to 2018, where he engaged in projects requiring uncertainty quantification in machine learning predictions.
Education and Expertise
Andre Goncalves holds a Doctor of Philosophy (Ph.D.) in Electrical and Computer Engineering from Universidade Estadual de Campinas, where his thesis was recognized as the best in Computer Engineering in 2016. He also earned a Bachelor's degree in Computer Science from Universidade Estadual de Londrina and a Master's degree in Computer Engineering from the same institution. His expertise spans a wide range of machine learning sub-fields, including generative models and representation learning, and he is proficient in programming languages and tools such as Python, Matlab, C++, and R.
Background
Andre Goncalves has a diverse academic and professional background. He began his career as a Bioinformatics Intern at Embrapa from 2008 to 2009. He then worked as a Research Assistant at the State University of Campinas from 2009 to 2013. Following this, he served as a Research Assistant at the University of Minnesota from 2013 to 2014, collaborating with Prof. Arindam Banerjee on machine learning models for applications including Alzheimer's disease progression assessment and climate forecasting. He also worked as a Researcher at the Center for Research and Development in Telecommunication (CPqD) from 2015 to 2017.
Achievements
Andre Goncalves has received recognition for his academic work, particularly for his Ph.D. thesis, which was awarded as the best in Computer Engineering at Universidade Estadual de Campinas in 2016. His collaborative research at the University of Minnesota involved developing machine learning models for significant applications, demonstrating his contributions to the field of machine learning and its practical applications.