Data scientist in both industry and academia have been using artificial intelligence (AI) and machine learning to make groundbreaking improvements across a variety of applications in oil and gas and biomedical systems. In this talk, I will present various research projects that I have been working on at Hewlett Packard Enterprise Data Science Institute, University of Houston, TX, USA. The first part of presentation will mainly focus in an overview on applications of machine learning techniques in oil and gas. The discussion will be mainly center around convolutional neural networks. The last part of the talk will be dedicated to the vast potential of machine learning in medical images and single cell analysis, improving possibilities for early diagnosis and prognosis of disease.
Dr. Pablo Guillen-Rondon
Is a Research Assistant Professor/Faculty at the HPE Data Science Institute, University of Houston, Houston, TX, USA. He holds a B. Sc. Degree in Mathematics and a M. Sc. Degree in Applied Mathematics, a PhD in Biomedical Engineering, and a Postdoc in Computational Science from University of Texas at El Paso, El Paso, TX, USA. During the last 20 years he has been working on Research and Development projects related to Oil, Gas, and Biomedical Sciences. These projects have been in different areas such as: Artificial Intelligence, Machine Learning, Data Mining, Data Reconciliation and Fault Diagnosis, Reservoir Simulation, Geophysics, Geothermal, Gas, Processing of Signals, Images, and Visualization. Universities and Companies funded these projects. He has been a keynote speaker in several Conferences, and he has over 115 papers published in Journals and Conferences.