Carlos H. Mendoza-Cardenas

I am an electrical engineer with industry and graduate research experience in statistical and machine learning methods, data wrangling and data cleaning of large (>2TB) data sets, and execution of experiments in high-performance clusters. I also have a strong background in digital signal processing, and extensive experience as a Linux user and administrator.

I enjoy developing and applying my statistical and computational thinking to solve complex and impactful problems. I am currently developing data-driven methods to discover patterns in the electrical activity of the human brain. I am applying my methods to long neural time series recorded from the brain of patients with epilepsy, but they could be used to other types time series. In one of my projects, I found patterns that are interpretable and predictive (93% in a classification task), which could then be used to predict seizures and understand their underlying physiological mechanisms. This work represents a novel approach to the analysis of time series of electrical brain activity that can offer not only predictive power but also new insights for the study of the brain physiology.

Although I enjoy environments where I can keep learning and growing, I also find meaning in teaching and mentoring others. I have more than 6 years of experience in mentoring and teaching, from middle and high school kids to undergrad students.

I am fluent in MATLAB, Python, English, and Spanish.

I did my B.E. in Electronics Engineering and my M.Sc.Eng. at the Universidad de Antioquia (Colombia), with a concentration in digital signal processing and digital communications. I am currently a senior Ph.D. student at the Department of Electrical and Computer Engineering of the University of Delaware, with expected graduation date of December 2022, and under the supervision of Dr. Austin J. Brockmeier.