Geet Rakala

Skills

Quantum Computing & Algorithms: PennyLane, Parameterized Quantum Circuits, Quantum Machine
Learning, Quantum Monte Carlo, Quantum Metric Tensor, Physics-Informed Neural Networks
High-Performance Computing: C/C++, MPI, SLURM, GNU Parallel, Parallel Computing, Distributed
Computing, HPC Workflows
Programming & Frameworks: Python, C++, Boost Graph Library, NumPy, SciPy, Pandas, JAX, Matplotlib
Machine Learning & Optimization: XGBoost, Gradient Descent, L-BFGS, Adam, Optax, Stochastic
Optimization, Time Series Forecasting, Feature Engineering, Scientific Computing: Monte Carlo Methods, Stochastic Processes, Numerical Simulation, Algorithm Design, Statistical Analysis, Complex Systems Modeling

About

High-Performance Simulation: Designed and implemented massively parallel simulation workflows
using C++/MPI/SLURM, optimising execution for Quantum/Classical Monte Carlo methods and
graph renormalisation algorithms.
Quantum Algorithms & ML: Engineered GPU-accelerated implementations of Quantum Cognition
Machine Learning (QCML) and Quantum Physics-Informed Neural Networks (QPINNs) using the
JAX differentiable programming framework.