Summary
Masud Rana is a hydraulic control and optimization engineer with nine years of experience applying control theory, machine learning, and numerical modeling to urban and natural water systems. Based in Leander, TX, he develops real-time optimal operation algorithms for water distribution systems that balance cost, leakage reduction, GHG emissions, and reliability under stochastic demand. At Xylem and previously as a graduate researcher at the University of Cincinnati and Virginia Tech, he has led SWMM/EPANET modeling, system diagnostics, calibration, and the integration of ML methods (ANFIS, Bayesian Neural Nets, SOM) with global optimizers (GA, DREAM, MCMC). Comfortable in C/C++, Python, Go and Fortran, he bridges advanced research and production software, bringing academic rigor to practical utility-sector problems. An understated strength is his cross-disciplinary fluency—from tracer-based field studies and solute transport to large-scale reservoir and groundwater modeling—enabling solutions grounded in both data and physical process understanding.
9 years of coding experience
13 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Environmental Engineering Technology/Environmental Technology, Doctor of Philosophy (Ph.D.), Environmental Engineering Technology/Environmental Technology at University of Cincinnati
Virginia Tech
Bachelor of Science (BSc), Civil Engineering, Bachelor of Science (BSc), Civil Engineering at Bangladesh University of Engineering and Technology
English, Bengali