Foundation Models Enabling Multi-Scale Battery Materials Discovery: From Molecules To DevicesVidushi SharmaAndy Teket al.2025NeurIPS 2025Workshop paper
Extracting Electrolyte Design from Interpretable Data-Driven MethodsVidushi SharmaMaxwell Giammonaet al.2025ACS Spring 2025Talk
Quantum Computer-Enhanced Surface Reaction Simulations for Battery Materials through Sample-Based Quantum Diagonalization and Local EmbeddingMarco Antonio Guimaraes Auad BarrocaRodrigo Neumann Barros Ferreiraet al.2025APS Global Physics Summit 2025Talk
KnowledgeHub: An end-to-end Tool for Assisted Scientific DiscoveryShinnosuke TanakaJames Barryet al.2024IJCAI 2024Demo paper
Formulation Graphs for Mapping Structure-Composition of Battery Electrolytes to Device PerformanceVidushi SharmaMaxwell Giammonaet al.2023J. Chem. Inf. Model.Paper
Understanding the role of mass transport and lithium interphase design in enabling conversion batteriesMurtaza ZohairMaxwell Giammonaet al.2023ACS Fall 2023Talk
AI-directed discovery of high entropy electrolyte formulations for batteries using interhalogen cathodes and lithium metal anodesMaxwell GiammonaVidushi Sharmaet al.2023ACS Fall 2023Talk
Accelerated Electrolyte Discovery using Data Driven ApproachVidushi SharmaMaxwell Giammonaet al.2023ACS Fall 2023Poster
Going beyond High Throughput Screening towards AI in Accelerated Electrolyte DiscoveryVidushi SharmaMaxwell Giammonaet al.2022MRS Fall Meeting 2022Conference paper
Transfer Learning Enabled Deep Learning Model for the Prediction of Battery Performance from Electrolyte FormulationsVidushi SharmaMaxwell Giammonaet al.2022ECS Meeting 2022Talk