Fernando Gama received the electronic engineer degree from the University of Buenos Aires, Argentina, in 2013, the M.A. degree in statistics from the Wharton School, University of Pennsylvania, in 2017, and the Ph.D. degree in Electrical and Systems Engineering from the University of Pennsylvania, Philadelphia, PA, in 2020.

He has been a visiting researcher at TU Delft, the Netherlands, in 2017, a research intern at Facebook Artificial Intelligence Research, Montreal, Canada, in 2018, and a postdoctoral scholar in the department of electrical engineering and computer sciences at the University of California, Berkeley, CA.

He has been awarded a Fulbright scholarship for international students, he has received a best student paper award at EUSIPCO 2019, and he has authored one of the top 25 TSP downloaded articles from IEEEXplore in 2020.

His research interests are in the area of machine learning and signal processing for data with irregular structure, with a focus on graph neural networks (GNNs).

He has worked on developing architectures, theoretical foundations, and novel applications of GNNs to physical networks including robotics, communications, control, and smart grids.