David P. Larson

I am a PhD candidate in MAE at UC San Diego. My advisor is Carlos Coimbra and I work in the Coimbra Research Group on developing forecasting models for solar power plants.

I have a MS in Mechanical Engineering from UC San Diego and a BS in Mechanical Engineering from UC Merced. During my time at UC Merced, I participated in the UC LEADS and Cal NERDS summer research programs.

Outside of research, I act as an instructor for ENG 10 and regularly present technical workshops, in collaboration with the IDEA Student Center.

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I am interested in machine learning, convex optimization and renewable energy systems. My current work focuses on developing forecast models to accurately predict power output of solar power plants.

Direct Power Output Forecasts from Remote Sensing Image Processing
D.P. Larson and C.F.M. Coimbra
(submitted), 2017

Day-Ahead Forecasting of Solar Power Output from Photovoltaic Plants
D.P. Larson, L. Nonnenmacher and C.F.M. Coimbra
Renewable Energy, 2016
doi / bibtex

We present a forecast methodology for producing day-ahead (24h-36h) power output predictions of photovoltaic (PV) plants. Four years of power data from two, 1 MWp PV plants is used to evaluate our methodology.


I currently teach ENG 10: Fundamentals of Engineering Applications, a hands-on course that provides students with an introduction to engineering mathematics and design. From Fall 2013 to Spring 2016, I was a TA for a freshmen engineering seminar (ENG 1-3: Orientation to Engineering I-III).

(This website is great!)