Edgar Ek Chacón
Mexico City, Mexico
Doctor in Computer Science
Local Time - 09:47 PM
About Me
During my Ph.D. program, I worked on several machine learning projects, focusing on supervised and semi supervised learning. In the supervised learning framework, our research led to the publication of LSTM Classification under Changes in Sequence Order, where we evaluated LSTM performance on sequences of varying lengths. Additionally, we published Semi Supervised Training for Pre Stack Seismic Data Analysis in an internationally recognized journal, applying a semi supervised approach to enhance the estimation of acoustic impedance, a key parameter in oil exploration. My thesis, Contributions to Pattern Recognition with Massive Unlabeled Data, introduced a novel semi supervised methodology to address the challenge of working with large scale unlabeled data alongside limited labeled samples. Throughout these projects, I primarily developed models using TensorFlow and Python.
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