Time Series Clustering for Monitoring Fueling Infrastructure Performance with Kalai Ramea – #300
Today we are joined by Kalai Ramea, Data Scientist at PARC, a Xerox Company. With a background in transportation, energy efficiency, art, and machine learning, Kalai has been fortunate enough to follow her passions through her work. In this episode we discuss:
Her environmentally efficient pursuit that lead to the purchase of a hydrogen car, and the subsequent journey and paper that followed assessing fueling stations Kalai’s next paper, looking at fuel consumption at hydrogen stations using temporal clustering to identify signatures of usage over time, grouping the stations into categories With the construction of fueling stations is planned to increase dramatically in the next 5 years, building reliability on their performance is crucial A sneak peek into how Kalai incorporates her love of art into her work! Check out the show notes, and the refresh, at twimlai.com!