Research Group


Welcome to the webpage of the  Intelligent and Resilient Energy System (IRES) Research Group. Our group is a team of Ph.D., graduate, and undergraduate researchers at the Computer & Electrical Engineering and Computer Science Dept. of the Florida Atlantic University, directed by Prof. Yufei Tang. Our expertise is in Computational Intelligence, Data Processing, and Smart Grid. We work enthusiastically in these research fields to expand the theoretical understanding and provide novel high-impact solutions.


Our research focuses on the theoretical understanding and algorithmic solution of important problems in data analysis, machine intelligence, and smart grid.

                          data-analysis                                          data-analysis                                        Image result for energy systems icon
                       Data Processing                        Machine Intelligence                                      Smart Grid

Some specific research topics that we are currently working are:

Data Processing and Machine Intelligence: Bio-inspired learning, such as deep learning, reinforcement learning, and adaptive/approximate dynamic programming. Smart Grid: Adaptive and intelligent control and optimization for smart grid based on CI techniques, smart grid data analysis and signal processing, such as data-intensive MCM/PHM, multi-contingency analysis, cascading outage modeling, false data injection attack detection, and proactive defense design.


Graduate Students:

  • Min Shi, Ph.D. Student, Electrical Engineering;

  • Brit Freeman, Ph.D. Student, Electrical Engineering;

  • David Wilson, Master Student, Computer Science;

Undergraduate Students:

Image result for Nathan Witztum

  • Nathan Witztum, Undergraduate Student, Mechanical Engineering;

Here are some VALUES that we shared in our group and want to see in you:

  • Hard work: We expect you to have a strong work ethic. Many of us work evenings and weekends because we love our work and are passionate about the research goals. We also value velocity, and like people that get things done quickly.
  • Flexibility: You should be willing to dive into different facets of a project. For example, besides developing control and machine learning algorithms, you may also need to work on system benchmark modeling or do data acquisition. This may also require going outside your comfort zone, and learning to do new tasks in which you’re not an expert.
  • Learning: You should have a strong growth mindset, and want to learn continuously. This can involve reading papers and books, taking coursework, talking to experts, or re-implementing research papers. We will also prioritize your learning and help point you in the right direction; but you need to put in the work to take advantage of this.
  • Teamwork: We work together in small teams. You are expected to support and collaborate with others; in turn you will also receive support from your teammates.