School of Engineering


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  • Daniel Norbert Congreve

    Daniel Norbert Congreve

    Assistant Professor of Electrical Engineering

    BioDan Congreve received his B.S. and M.S. from Iowa State in 2011, working with Vik Dalal studying defect densities of nano-crystalline and amorphous silicon. He received his PhD from MIT in 2015, studying under Marc Baldo. His thesis work focused on photonic energy conversion using singlet fission and triplet fusion as a downconverting and upconverting process, respectively. He joined the Rowland Institute at Harvard University in August 2016 as a Rowland Fellow. He started as an Assistant Professor of Electrical Engineering at Stanford in Fall 2020. His current research interests include engineering nanoscale materials and using them to solve challenging problems.

  • Riley Culberg

    Riley Culberg

    Ph.D. Student in Electrical Engineering, admitted Autumn 2019

    BioMy research focuses on resolving the near-surface and internal structure of the continental ice sheets in Greenland and Antarctica using airborne ice penetrating radar systems. I am particularly interested in understanding the coupling between firn structure and near-surface hydrology in Greenland, the evolution of this system in a warming climate, and its influence on the large scale ice sheet mass balance and hydrology. Additionally, I am interested in deep englacial structure as a reflection of past climate processes and ice sheet age structure. My approach to these questions involves the synthesis of electromagnetic theory, radar signal and system constraints, and in-situ observations to develop both forward and inverse methods that link physical conditions of interest within the ice sheets to their expression in radar sounding data. Applying these tools to the analysis of radar sounding data allows me to place observational constraints on state of the englacial system at scales and resolutions that bridge the gap between field measurements and numerical models. In addition, I have applied some of these same techniques to study the optimal system design parameters for future high altitude or satellite-based radar systems.