Miguel Ángel C. has significant work experience in the field of machine learning and research. Miguel Ángel'smost recent position was as a Machine Learning Engineer at Invofox, starting in March 2022. In this role, Miguel applies state-of-the-art machine learning models, mainly focusing on NLP, to solve complex problems. Miguel Ángel utilizes PyTorch and Hugging Face libraries and is also gaining experience with SageMaker for model deployment.
Prior to their current position, Miguel worked as a Research Engineer (Machine Learning) at the Graphics and Imaging Lab from May 2021 to February 2022. During this time, they collaborated with the startup DIVE-Medical on a health research project related to visual pathologies. Miguel was responsible for analyzing raw eye tracker data and implementing various neural network models such as LSTM, GRU, Transformers, and MLPs.
Before their role as a Research Engineer, Miguel held the position of Junior Researcher at the Graphics and Imaging Lab from July 2019 to November 2020. Miguel Ángel worked on a research project on transient imaging in collaboration with a research group from the University of Wisconsin. Miguel contributed to the development and modification of the Phasor Fields framework in MATLAB and a transient renderer in C++. Miguel Ángel'swork on this project led to a research paper accepted at the International Conference on Computer Vision (ICCV 2021) for oral presentation.
Overall, Miguel Ángel C. has a strong background in machine learning, with specific expertise in NLP, eye tracking data analysis, and neural network model implementation.
Miguel Ángel C. pursued their education at the Universidad de Zaragoza. From 2013 to 2019, they completed a Bachelor's degree in informatics engineering with a specialization in computer science. Following this, they decided to continue their academic journey by enrolling in a Master's program at the same university from 2019 to 2021. The Master's degree they pursued was in Modeling, Mathematical Research, Statistics, and Computing, focusing on fields such as Mathematics, Statistics, and Computing.
In addition to their formal education, Miguel Ángel C. also obtained two certifications. In September 2021, they completed a course titled "Getting Started with AI on Jetson Nano" provided by the NVIDIA Deep Learning Institute. Furthermore, in October 2020, they obtained the First Certificate in English (FCE) from the University of Cambridge.
Sign up to view 0 direct reports
Get started