Hammad Mazhar is a Senior Engineering Manager in the San Francisco Bay Area with 16 years of deep expertise in high-performance physics simulation, GPU-accelerated computing, and parallel systems engineering. At NVIDIA he progressed from intern to senior individual contributor and now leads engineering teams that bridge simulation, robotics, and deep learning, applying hands-on optimization experience to scale complex codebases. His PhD work and long stint at University of Wisconsin–Madison underpin a strong foundation in massively parallel collision detection and heterogeneous CPU/GPU clusters. An active contributor to the Chrono physics library, he has implemented and optimized fluid dynamics and constraint handling within Chrono::Parallel, demonstrating practical mastery of particle interactions and pressure constraints. Colleagues know him for combining research-grade simulation rigor with production-focused performance tuning—often finding low-level optimizations that yield large speedups on real hardware. He brings a rare blend of academic depth and industry leadership that accelerates both algorithmic innovation and reliable product delivery.
16 years of coding experience
14 years of employment as a software developer
Doctor of Philosophy (PhD) Mechanical Engineering, Doctor of Philosophy (PhD) Mechanical Engineering at University of Wisconsin-Madison
High-performance C++ library for multiphysics and multibody dynamics simulations
Role in this project:
Back-end Developer & Physics Simulation Engineer
Contributions:2241 commits, 2 PRs, 157 pushes in 7 years
Contributions summary:Hammad primarily contributed to the core functionality of the physics simulation library, specifically focusing on implementing and improving fluid dynamics simulations. Their work involved updates to existing fluid demo code, including refinements to particle interactions, contact force calculations, and the integration of features like pressure constraints. The user demonstrated expertise in parallel computing by integrating and optimizing these changes within the Chrono::Parallel framework. In addition, they added the capability to work with different types of constraints, allowing for more flexible simulations.
Contributions:191 commits, 42 pushes in 4 years 4 months
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Hammad Mazhar - Senior Engineering Manager at NVIDIA