Research scientist specializing in crosscutting applications and advancement of sensor research to enable resilient real-time measurement and control of process variables within the nuclear and other critical industries. Current research advances sensor technologies and big data analytic techniques in (1) development of a non-intrusive and wireless measurement infrastructure for investigation of in-pile reactor phenomena during operation in harsh environments; (2) performance of online monitoring of plant structures, systems, and components to develop diagnostic and prognostic models; (3) performance of risk-informed predictive evaluation; and (4) evaluation and development of mitigation strategies related to digital instrumentation and control cyber-security.

Dr. Agarwal has authored 51 peer-reviewed publications, with an H-index of 10, 457 citations (Google Scholar), with impact factors up to 3.808. He has authored 1 book chapter and has 2 US Patent Applications Filed. To date, he has been involved in 13 research funded under diverse grant portfolio (8 as Principal Investigator, PI, and 5 as co-PI). He serves as a reviewer for the IEEE Transactions on Image Processing, Energy Conversion, Industrial Informatics, Industrial Applications, Power Delivery, Systems, Machine and Cybernetics, Instrumentation and Measurement, and the American Nuclear Society (ANS) Transactions on Nuclear Technology. He serves as an external reviewer for U.S. Department of Energy's Office of Science and Office of Nuclear Energy. He has been Section Editor for the Journal of Pattern Recognition Research since 2009. He has served as an Elected Member of the ANS Human Factors, Instrumentation and Controls Division since 2015 and the ASME Nondestructive Prognostics and Diagnostic Division since 2016.