Madan Timalsina is a postdoctoral fellow in the NERSC NESAP for Data program at Lawrence Berkeley National Laboratory, where he works on performance engineering and workflow modernization for large-scale scientific computing. His expertise includes GPU acceleration, parallel I/O, containers, checkpoint/restart, HPC workflow orchestration, and AI/ML pipeline optimization. He collaborates with domain scientists and NERSC staff to improve simulation, data analytics, and machine learning workflows for DOE science projects, including DUNE and LZ. Madan received his Ph.D. in nuclear and particle physics from the South Dakota School of Mines and Technology in 2022, where his research focused on calibration and simulation for the LZ (LUX-ZEPLIN) dark matter experiment.