Muhammad K - Quantitative Researcher

Muhammad K

Quantitative Researcher

Oxford, England, United Kingdom

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Summary

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Senior

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Top School

Muhammad K is a quantitative researcher with 14 years of experience who holds a DPhil from the University of Oxford and bridges cutting-edge AI research with real-world productisation, having co-founded two Oxford spinouts. He has published work featured in Science and Nature Physics and built simulation and ML tools in high-energy-density science and medical physics during his postdoc. Now at Tudor Investment Corporation’s Xantium Group, he applies scientific computing and numerical methods to quantitative problems, drawing on deep open-source contributions to SciPy and PyTorch—including a performant Voigt ufunc and complex-number kernels with CPU/CUDA implementations. Comfortable coding in C++ and Python, he combines algorithmic rigor with systems-level engineering and a track record of turning academic code into deployable technology. An under-the-radar strength is his experience scaling numerical kernels and addressing overflow/underflow issues, a rare skillset for quants working with production ML stacks.

13 years of coding experience

8 years of employment as a software developer

Bachelor of Engineering (B.Eng.) Electrical and Electronics Engineering, Bachelor of Engineering (B.Eng.) Electrical and Electronics Engineering at Institut Teknologi Bandung

Doctor of Philosophy (DPhil) Particle Physics, Doctor of Philosophy (DPhil) Particle Physics at University of Oxford

Github Skills (36)

pytorch10

algorithms10

scipy10

c-language10

python10

email-notifications10

authentication10

user-authentication10

google-app-engine10

complex-numbers10

numpy10

f10

webapp10

account-management10

cuda10

Programming languages (8)

C++ShellCSSCRustJupyter NotebookRubyPython

Github contributions (5)

pytorch/pytorch

Feb 2020 - Jan 2023

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Role in this project:

Back-end Developer

Contributions:101 reviews, 30 commits, 29 PRs in 3 years

Contributions summary:Muhammad primarily contributed to the implementation of complex number support within the PyTorch codebase, specifically focusing on the `log1p` and `logcumsumexp` functions. Their work involved writing C++ code, including kernel implementations for CPU and CUDA, and creating corresponding unit tests. They also addressed overflow and underflow issues, and optimized performance by applying Sklansky algorithm for scan operations.

pythongpu-accelerationdeep-learninggpunumpy

coto/gae-boilerplate

Jun 2012 - Jul 2012

Google App Engine Boilerplate

Role in this project:

Back-end Developer

Contributions:20 commits in 1 month

Contributions summary:Muhammad contributed to the back-end functionality of the Google App Engine boilerplate project. Their commits focused on user authentication, account management, and email notifications. The changes involved modifying handlers, implementing features for email verification and password resets, and integrating language localization support. They also addressed login-related bug fixes and integrated account activation.

google-apppythonboilerplateapp-enginegoogle

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