Daniel Van Hoesen received his Ph.D. in condensed matter Physics from Washington University in St. Louis where he studied liquid-solid phase transitions in metals and silicate glasses with a focus on the glass transition. He utilized electrostatic and electromagnetic levitators to study thermophysical properties (specific heat, viscosity, nucleation rate, and crystallization velocity) of liquids as they cool beneath the melting temperature. He also performed computational simulations of silicate gasses to understand and test the various theories of nucleation. He is currently a data scientist / scientific programmer at Impossible Sensing where he develops software and machine learning algorithms to aid in instrument development, automated spectroscopy classification, and in the development of novel data processing and visualization tools