Mahesh Narayanamurthi is a software engineer with 12 years of experience who blends rigorous academic training in numerical algorithms, simulation, and optimization with production experience at Google and startups. His PhD work focused on advanced time integration, sensitivity computation, and uncertainty quantification for PDE/ODE simulations, giving him deep expertise in scientific computing and algorithmic differentiation. He has a track record of turning research-grade numerical methods into robust software—previous roles include building real-time rail scheduling and network simulation systems and contributing open-source AD test suites used by the community. Comfortable across Fortran, C, Python, MATLAB and modern engineering stacks, he pairs low-level performance tuning with higher-level system design. Based in New York, he brings both academic rigor and practical systems thinking to complex simulation and optimization problems. A less obvious strength: he’s repeatedly bridged research and operational product delivery, from conference-presented AD research to scalable transportation planning tools.
12 years of coding experience
10 years of employment as a software developer
Master of Science - MS, Industrial and Systems Engineering (Operations Research), Master of Science - MS, Industrial and Systems Engineering (Operations Research) at Virginia Tech
Bachelor of Technology - BTech, Electrical, Electronics and Communications Engineering, Bachelor of Technology - BTech, Electrical, Electronics and Communications Engineering at Visvesvaraya National Institute of Technology
High School, High School/Secondary Diplomas and Certificates, High School, High School/Secondary Diplomas and Certificates at Padma Seshadri Bala Bhavan Senior Secondary School
Django based tool for monitoring huey task queue: https://github.com/coleifer/huey
Contributions:1 review, 2 pushes, 1 branch in 5 months
pythondjangotask-queuehueymonitoring
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Mahesh Narayanamurthi - Software Engineer at Google