Anika Tabassum

Anika Tabassum is contributing towards developing deep Learning for multi-scale and multimodal data evolved from energy research. Her research interest broadly lies in robust and scalable domain-guided ML for scientific discovery. She has been selected as RISING STAR 2023 by UT Austin and an outstanding postdoctoral award from her division at ORNL in 2022. She received her Ph.D. from the Department of Computer Science at Virginia Tech where she worked on bringing domain-guided ML to address multiple challenges to prepare and mitigate power system failures and disaster vulnerabilities. Her Ph.D. research work was funded by NSF Urban Computing fellowship. She won 1st prize in designing the COVID-19 forecasting model for the Facebook-CDC challenge. She has published in multiple venues as NeuRIPS, AAAI, ACM SigKDD, CIKM, IEEE BigData, IAAI, and journals like ACM TIST and Elsevier.