Hi, welcome to this site that shares a bit of my professional portfolio and experience. My name is Sean Anderson, and my expertise is in controls engineering and machine learning for the purposes of decision making. I completed my Ph.D. in 2025 under the guidance of Professor João Hespanha at UC Santa Barbara in Electrical and Computer Engineering. Prior to this I completed by M.S. in Electrical and Computer Engineering at UCSB in 2022. Before graduate school I worked at New Sun Road, P.B.C. on controls, data science, and software engineering, for the purposes of enabling the optimal dispatch and control of energy assets in microgrids in remote developing communities. My undergraduate studies were in energy engineering at UC Berkeley from 2014-2018.

My research primarily focuses on the efficient collection and use of data for control, game theory, and online decision-making. These problems consider data-driven methods and address the importance of quality data. In other words, you may have a very large set of data to train your models on/make decisions from, but if the dataset has very little information in it, then the resulting performance will be poor. Conversely, you could collect a relatively small dataset with very informative datapoints. The benefits of this depend on the context but can lead to better decision making performance than a larger dataset, faster model training, and/or lower experimental costs for collecting the data.