Profile

Roel Dobbe received a BSc in Mechanical Engineering (2007) and a MSc in Systems & Control (2010) from TU Delft. During his masters, he conducted thesis research at UC Berkeley in the Hybrid Systems Lab, under the guidance of Professor Alessandro Abate and Professor Claire Tomlin.

From 2013 to 2018, he completed a PhD degree in Electrical Engineering & Computer Sciences at UC Berkeley, under the guidance of Professor Claire Tomlin in the Hybrid Systems Group and co-advised by Duncan Callaway in the Energy & Resources Group. From 2018 to 2020, he was an inaugural postdoc with the AI Now Institute at New York University.

His main interests are in modernizing critical infrastructure and sensitive decision-making through developing data-driven tools for analysis and control that promote safe, sustainable and democratically just societal systems.

In addition, Roel enjoys improving organizational culture and standards around employee wellness. While at Berkeley, he started a student-run organization to stimulate cross-disciplinary and engaged scholarship around technology and its societal implications, called Graduates for Engaged and Extended Scholarship in and around Engineering (GEESE).

After graduating from Delft and before starting my PhD, Roel gained experience in industry and the public sector. First, he participated in the Nationale DenkTank where he worked on trust and citizen participation in public institutions. Consecutively, he was a management consultant with A.T. Kearney at their Amsterdam office - working on a variety of projects for utility, healthcare and financial organizations. In 2016, Roel worked as a Data Scientist at C3 IoT in Silicon Valley, helping them to deliver better machine learning products to their energy customers (utilities and providers), by developing tools to increase interpretability and diagnosis and aiding the launch of platform tools with which end users can do data science and machine learning without explicit programming. In 2017, Roel was a Research Affiliate at Lawrence Berkeley National Labs in the Grid Integration Group with Daniel Arnold, working on state estimation and decentralized learning for distribution grids