Adam Lewis is a physicist-turned R&D leader who heads Innovation for SandboxAQ's AISim unit, applying nine years of experience to building "Large Quantitative Models" for drug, chemical, and materials discovery. He began by writing GPU code for gravitational-wave simulations and advanced algorithms for quantum field–black hole interactions, later translating that numerical and scientific rigor into industry-scale ML and distributed linear algebra (notably a multi-TPU JAX library used for record-size O(N^3) DFT simulations). At SandboxAQ he has driven technical strategy, business development with pharma and materials customers, and now leads a growing team developing what he believes are revolutionary discovery tools. He also contributed backend improvements to the popular TensorNetwork project—adding robust linear-algebra solvers and multi-backend testing across NumPy, JAX, PyTorch and TensorFlow—demonstrating a rare combination of deep scientific computation and production-grade software engineering.
A library for easy and efficient manipulation of tensor networks.
Role in this project:
Back-end Developer
Contributions:64 reviews, 50 commits, 74 PRs in 3 months
Contributions summary:Adam primarily contributed to the back-end functionality of the tensornetwork library. Their work involved adding and modifying code related to linear algebra operations within the library, specifically focusing on implementing GMRES and other related methods. Furthermore, the user was involved in testing these methods across various backends, including NumPy, JAX, PyTorch, and TensorFlow, ensuring consistent functionality. Additionally, the user added support for new features like pivot, abs, sign, and diagflat.
Contributions:26 commits, 21 pushes, 1 branch in 17 days
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.