Carlos A. Rincon C. Ph.D.

I am an Instructional Assistant Professor of the Computer Science Department at the University of Houston. I was born in Maracaibo, Venezuela. After working in the industry for two years, I joined the Department of Computer Science at Universidad del Zulia in Maracaibo, Venezuela, in 2001. After completing my Master’s in Telematics, I started working on the performance analysis of local area networks. In 2008, my research interests shifted to Information Theory, using compression theory to present solutions to different studied problems. In 2014, I joined the Ph. D. program at the University of Houston, working with Dr. Albert Cheng on Real-time systems scheduling using Information Theory principles.

Teaching Philosophy

My goal as a professor of Computer Science is to disseminate knowledge in the theory and application of computing, ensuring that students learn how to solve real-life problems by using the theoretical background explained in class.

I believe that algorithmic thinking is an essential skill that every computer science student must develop. From my experience, I have learned that first-year students tend to struggle more in computer science classes because they need help finding a clear definition of the steps necessary to solve a particular problem. My strategy to approach this issue is to encourage students to fully understand the problem they are trying to solve before developing a solution.

I use a variety of learning methods to motivate my students. My lectures usually are bi-directional, allowing students to communicate their doubts and opinions about the discussed topics. From my experience as a researcher, I have learned that, in most cases, the right solution to a problem may be found only after multiple unsuccessful attempts to solve that problem. I encourage my students to participate in class by showing them they also learn when they are wrong, given that mistakes are learning opportunities.

To summarize, my teaching philosophy boils down to two key goals: to provide my students with the tools needed to become excellent computer scientists and always challenge myself to become a better professor by constantly exploring and implementing new learning techniques to improve my students’ learning experience.

Research Philosophy

My research interests are in the areas of real-time systems, and storage systems. My work is driven by a strong desire to bridge the Information Theory methods to measure the uncertainty of a system and real-time system scheduling, providing practical solutions for embedded systems. My main research area focuses explicitly on the Scheduling of Hard Real-time Systems based on Information Theory Principles.

My research philosophy places a strong emphasis on finding solutions that can be implemented to solve real-life problems. Real-time systems scheduling for multiprocessors is one of the areas in computer science where theoretical results are often put into practice, with many challenging problems that are usually NP-complete or undecidable. I offer my research as part of my student’s learning experience, showing them my current work and its relationship with the theoretical background of the class.