Anvay Sanil
Third-year CS undergraduate (Manipal University Jaipur) specialising in Scientific Machine Learning, Physics-Informed AI. Gold Tier, WorldQuant IQC 2026 (top 6.9%, rank 20,522 of 297,056).
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About
Gold Tier, WorldQuant IQC 2026 (top 6.9%, rank 20,522 of 297,056). Second-year CS undergraduate (Manipal University Jaipur) specialising in Scientific Machine Learning, Physics-Informed AI, and Quantitative Research. Conducted a 22-phase ablation study on Neural Quantum States achieving 99.5% thermodynamic accuracy; co-built a neural operator engine delivering 500× speedup over classical AdS/CFT PDE solvers at 3% L2 error.
Core stack: JAX, PyTorch, PennyLane, NetKet, FastAPI, Python.
Experience
Quantitative Researcher at WorldQuant International Quant Championship (IQC) (2026 – 2026)
- Achieved Gold Tier in WorldQuant’s global IQC Challenge, placing in the top 6.9% worldwide (rank 20,522 of 297,056 competitors).
- Engineered an automated alpha mining pipeline in Python using Gemini 2.5 Pro on Vertex AI, backtesting and submitting 10 alphas against WorldQuant BRAIN with IC, Sharpe, and turnover as primary evaluation metrics.
Education
Bachelor of Technology in Computer Science & Engineering – Manipal University Jaipur (2024-10)
