About me

I grew up in The Netherlands in a town called Lisse, centered in the Dune and Bulb Region. I received a BSc in Mechanical Engineering (2007) and a MSc in Systems & Control (2010) from TU Delft. During my masters, I conducted my thesis research at UC Berkeley in the Hybrid Systems Lab, under the guidance of Professor Alessandro Abate and Professor Claire Tomlin.
Since Fall 2013, I am pursuing 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. My main interests are in modernizing our energy systems through developing tools and data-driven methods to do analysis and control. I also enjoy collaborating with systems biologists and scholars from the social sciences (STS, ethics and philosophy). Our group is connected to the Berkeley Artificial Intelligence Research (BAIR) Lab and located in the Center for Information Technology Research in the Interest of Society (CITRIS).

I am interested in understanding social implications of automation technologies, and how to best prepare ourselves to anticipate these. With a few peers, I wrote an article on this topic to explore some relevant questions. More recently, I have been teaching about issues of social justice and how these relate to our work as research and engineering professionals.

Within the university, I enjoy improving our organizational culture and standards around graduate student wellness via EECS Peers.

After graduating from Delft and before starting my PhD, I gained experience in industry and the public sector. First, I participated in the Nationale DenkTank where I worked on trust and citizen participation in public institutions. Consecutively, I 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, I 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, I 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.

In my free time, I enjoy traveling, culture, music and exercise. In the first years back at Berkeley, I have enjoyed developing my vocal and jazz skills, serving as a baritone in the Cal Jazz Choir.