Emma Hu is an assistant professor in the School of Materials Science and Engineering at Georgia Tech. Her group will use quantum mechanical modelling combined with materials informatics to understand the underlying mechanisms of energy harvesting and utilization at the atomic level, and reveal structure-property-performance relationships for knowledge/data-driven materials design.

Her research seeks to accelerate the discovery of materials with complex properties to solve time-sensitive problems involving green energy production and climate remediation.

Hu obtained her Ph.D. in Physical Chemistry in 2018 from the University of California, Riverside, and her B.S. in Chemistry in 2013 from University of Science and Technology of China. She then spent two years as a postdoctoral scholar in the Center for Nanophase Materials Sciences at Oak Ridge National Laboratory from 2018-2020. Before joining Georgia Tech, Hu was an Assistant Professor at City University of New York from 2020-2023.

Suhas S. Jain is an Assistant Professor in the Woodruff School of Mechanical Engineering at Georgia Tech. He received his bachelor’s from NIT-Karnataka (India) in 2014, M.S. and Ph.D. from Stanford University in 2018 and 2022, respectively, all in mechanical engineering. Before coming to Georgia Tech, he was a postdoctoral fellow at the Center for Turbulence Research, Stanford University (2022-2023), a researcher at the Institute of Fluid Dynamics, Helmholtz-Zentrum Dresden-Rossendorf, Germany (2014-2015), and a project assistant at the Indian Institute of Science (2015-2016).

His research interests include computational modeling of fluid flows (multiphase flows; turbulent flows; compressible flows; and fluid-structure interaction) with a current focus on modeling atomization, sprays, and phase change for propulsion applications; ice accretion and aerodynamics for sustainable energy and aerospace design; and air-sea interaction modeling for understanding climate change; and modeling of fluid-solid and solid-solid systems for biomedical and high-speed applications. Through the integration of numerical modeling, high-performance computing, and data-driven approaches, Suhas and his group aim to address key challenges in these areas.