Transfer Learning Enabled Deep Learning Model for the Prediction of Battery Performance from Electrolyte Formulations
- 2022
- ECS Meeting 2022
Vidushi Sharma (Ph.D.) is currently a Staff Research Scientist in Energy Storage Group at IBM Almaden Research Center. She received her Ph.D degree in Mechanical Engineering from New Jersey Institute of Technology (NJIT) and in her thesis titled "Electro-chemo-mechanics of the interfaces in 2D-3D heterostructure electrodes" she computationally studied chemical and mechanical properties of interfaces formed by two dimensional materials such as Graphene and MXene with bulk alloying electrodes and their following electrochemical impact. After completing her doctorate in 2021, Vidushi joined IBM Research as a Research Scientist.
Her research is focussed on driving new material design and discovery with in-silico approaches that widely range from deep learning, artificial intelligence, molecular dynamics, ab-initio simulations, kinetic monte carlo, and lately to quantum computing. Besides having major experience in working on battery materials, she also have some background in design, simulation and synthesis of pharmaceutical molecules, catalysts and nano medicine.