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pranav997/README.md

👋 Hi, I'm Pranav Kairon!

I'm a Physics PhD student at UIUC, working at the intersection of machine learning, quantum computing, and condensed matter theory. Previously, I completed my Master’s at UBC, where I worked with Prof. Roman Krems on quantum machine learning and classical bayesian ML applied to condensed matter systems.

Outside of research, I enjoy hiking, cricket, writing code, and documenting ideas via blog posts.

Coding

🧪 What I Work On

  • Quantum Machine Learning: Variational circuits, supervised learning of quantum states, and data-driven Hamiltonian discovery
  • Quantum Many-Body Physics: Symmetry-protected topological phases, entanglement structure, and numerical simulation of lattice models
  • ML for Physics: Equivariant neural nets, representation learning, and generative models for physical systems
  • Classical ML: Scientific regression tasks, time series models, anomaly detection, and reinforcement learning
  • Computational Physics: DMRG, tensor networks, ED, and Markov chain methods on quantum/statistical models

🧰 Toolbox

  • Languages: Python, C++, Bash, LaTeX
  • Libraries & Frameworks: PyTorch, NetKet, JAX, TenPy, NumPy, SciPy, Matplotlib
  • Tools: Git, Overleaf, VSCode, Linux, Conda, SLURM

🎓 Education & Past Work

  • PhD in Physics, UIUC (present)
  • MSc in Physics, UBC (2024)
  • Research: Equivariant QML, E-ph physics, topological order, thermal state learning

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