Physics × Data Science × Machine Learning × Quantum Computing
I’m a final‑year Physics undergraduate at National University of Singapore (NUS), completing a second major in Data Science & Analytics. My passion sits at the intersection of physics, statistics and cutting‑edge AI — from physics‑informed neural networks that solve PDEs to quantum algorithms that push the frontier of computation.
| Project | Brief | Tech |
|---|---|---|
| Final‑Year Project: Quantum Autocloning Machine (ACM) | Derving a hybrid model of quantum autoencoder + quantum cloning to better clone a qutrit (3d quantum states) in qubit's subspace | JAX · NumPy · Qiskit · HPC GPU |
| Physics‑Informed Neural Networks (PINNs) | Meta‑learning PINNs for Grad‑Shafranov and inverse problems; exploring enhanced sensitivity loss terms | JAX · Flax · Optax |
| Variational Autoencoder (VAE) for Micronutrient Deficiency Prediction | Modified VAE model that predicts micronutrient deficiencies based on genetics data | Python · PyTorch · Ray · TensorBoard |
- ML / Deep Learning: PyTorch • TensorFlow • JAX • scikit‑learn • Ray
- Quantum: Qiskit • QuTiP • PennyLane
- Data & Viz: pandas • NumPy • Matplotlib • seaborn
- Languages: Python • Java • (some) JavaScript/TypeScript
- Dev & Ops: Git • Linux • Bash • HPC Slurm/PBS
- Writing / Docs: LaTeX • Markdown
- Physics‑informed ML & scientific computing
- Quantum information & variational algorithms
- Meta‑learning & optimization for inverse problems
- Statistical modelling & uncertainty quantification
- Diffusion models for generative science
- Graph Neural Networks for material property prediction
- Large Language Models
- Student Tutor for DSA1101: Introduction to Data Science @ NUS
“The curious mind is never satisfied — it merely finds better questions.”