Danish Alvi is a GPU Optimization Engineer with a decade of experience who blends deep theoretical training in mathematics and computing with hands-on high-performance computing work. Currently optimising vLLM for a green HPC datacenter, he pairs practical GPU performance engineering with research instincts honed during a Measurement-Based Quantum Computing internship at QuiX Quantum. His academic background spans Radboud University and LUMS, and he actively explores combinatorics, complexity, probability and quantum algorithms—areas that inform his interest in photonic processors, quantum cryptography, homomorphic encryption and neuromorphic computing. Comfortable bridging research and production, he has also engaged with quant teams through Citi’s MQA mentorship and holds industry exposure from early roles including Goldman Sachs. Notably, he frames his public coding presence with a playful “pretending to do Mathematics and Computing Science,” signalling a researcher-engineer mindset that pursues both rigor and experimentation.
9 years of coding experience
Bachelor's degree, Computer Science, SSE, Bachelor's degree, Computer Science, SSE at Lahore University of Management Sciences
Master of Science - MS, Mathematics and Computer Science, Master of Science - MS, Mathematics and Computer Science at Radboud University
We propose using Probabilistic Graphical Models such as Bayesian Networks and Hidden Markov Models to construct a global-macro trading strategy of the Crude Oil Markets.
Contributions:6 pushes, 1 branch in 1 year 9 months
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.