US Food and Drug Administration (August 2023- Present)

At FDA, I have developed an image registration based automated lesion correspondence and matching (RAMAC) algorithm and have designed the algorithm into a regulatory science tool (RST). This algorithm is designed to dynamically track both target and non-target entities, addressing the variability observed across different timepoints and radiologists in longitudinal data analysis. I am performing joint modelling of the longitudinal and time-to-event data for Metastatic breast cancer (mBC) progression risk prediction and performing lesion and organ segmentation by various deep learning frameworks on our dataset. I actively participate in reviewing consults related to AI/ML, medical imaging devices and diagnostics and attend regulatory discussion meetings at FDA.

Analog Garage (May-September 2022)

During my summer internship at Analog Garage, Boston I worked on the Advanced Battery Monitoring (ABM) project. I was responsible for developing novel transfer learning based statistical algorithms for EV battery state of health (SOH) and State of Power (SOP) estimation. I also developed synthetic battery aging models in Ansys following protocols like that of real experiments to produce simulation data which can serve as digital twinning with experimental data.

Michigan State University (2018-2023 (July))

During my PhD, I worked as Research Associate on several projects being funded by EPRI, GTI, various CAAP programs.

Ericsson (2015-2018 (June))

I was a part of the Work Force Management (WFM) team, which advices large service organizations with the optimal ways of scheduling and managing their field service work force. For general operations, we usually used the Click Service Optimization Suite. We were also involved in the development of novel routines for mobile customization using HTML5, C# and JQuery that enable dispatchers and technicians to communicate feedbacks in real time. My roles included developing and executing optimal algorithms and policies in order to assist clients in efficiently handling scheduling and communication assignments to their field force.