Limin Wang

Limin Wang is a data scientist fellow at Techlent since September 2022, where a machine learning model was developed to predict loan defaults, aimed at assisting clients and financial institutions in reducing risk and maximizing profit. Prior to this role, Limin served as a postdoctoral associate at Rutgers University from August 2019 to August 2022, focusing on predicting bandgap sizes using supervised machine learning and contributing to advancements in transparent conductors and low-power electronics. From August 2014 to July 2019, Limin worked as a faculty specialist at the University of Maryland, investigating potential superconductors and topological materials through DFT calculations. Earlier experience includes a position as a research associate at BNL from January 2011 to December 2013, where significant findings regarding the electronic structure of Ru122 were published in the Physical Review Letters. Limin Wang holds an education from Nanjing University.