Ismael Solis is a data scientist and performance analyst for IBM at Mexico Software Lab. He got his Masters from the National Center of Research and Technological Development in Mexico and his Ph.D. from the University of Leeds in the UK. Ismael has participated as a technical leader in different projects related to big data analytics and machine learning within IBM and other companies. These include the University of Leeds, The UK Datacenter Alliance, and Apollo MIS researching predictive algorithms for Google, Alibaba, and the British Premier League. Ismael has about 20 international publications in prestigious computing science journals. He has participated as a speaker in over 25 international conferences related to data science and machine learning, and co-authored patents to improve data center energy efficiency by exploiting big data. Ismael has collaborated as a researcher in the field of data science at the University of Leeds in the UK, The National University of Defense and Technology as well as The University of Aeronautics and Astronautics in China. In Mexico, he has collaborated with The National Institute of Electricity and Clean Energy and The National Center of Advance Technology architecting solutions for reducing energy consumption in smart cities. Ismael’s current work at IBM is focused on analyzing performance data and developing machine learning mechanisms to improve the performance of large distributed storage systems by analyzing big data.