Diego Ayala

Diego Ayala has work experience in various roles and positions. Diego started their professional career as a PhD candidate at McMaster University from May 2010 to June 2014, where they focused on designing and developing parallel scientific software and preparing documents for publication in scientific journals. Following this, they worked as a Junior Researcher at McMaster University from July 2014 to August 2014.

Later, Diego joined the University of Michigan as a Postdoctoral Fellow from September 2014 to August 2017. During this time, their research primarily focused on fundamental aspects of fluid dynamics, and they also taught two courses per academic year.

Currently, Diego is working at Spectrum Effect as a Senior System Engineer, starting from April 2022. Prior to this role, they were employed as a Systems Engineer and a Wireless Systems Engineer at Spectrum Effect from August 2017, and these positions do not have specified end dates.

Overall, Diego Ayala's work experience spans research, teaching, and engineering roles in academia and industry.

Diego Ayala has a strong educational background in applied mathematics. Diego obtained a Doctor of Philosophy (Ph.D.) degree in Applied Mathematics from McMaster University, where they studied from 2010 to 2014. Prior to their doctoral studies, they earned a Master of Science (MSc) in Applied Mathematics from McMaster University, completing it from 2008 to 2010.

Diego's educational journey also includes two master's degrees from the Universidad Nacional Autónoma de México. Diego pursued a Master's degree in Applied Mathematics from 2006 to 2008. During the same period, they also completed a Master of Science (MSc) in Applied Mathematics at the same institution.

Before their graduate studies, Diego Ayala attended Tecnológico de Monterrey, where they received a Bachelor of Engineering (BEng) degree in Electronic and Communication. Diego completed their undergraduate studies from 2001 to 2005.

Additionally, they have an additional certification in the Deep Learning Specialization from Coursera, which they obtained in April 2018.