Research Self-Supervised Learning on Stellar Light Curves First-author paper, ML4PS @ NeurIPS 2026. A self-supervised encoder pre-trained on unlabelled TESS light curves adds to engineered features on 7 of 10 tasks. ASTR199 — Stellar Parameter Prediction via Deep Learning Two-stage deep learning pipeline predicting stellar Teff, metallicity, and log g from 1M+ row multi-survey photometric catalog, driving log g R² from 0.519 to 0.833. PHY199 — Galaxy Spectra PCA Pipeline Automated high-dimensional spectra preprocessing and unsupervised PCA outlier filtering with Prof. Wittman at UC Davis. ML Engineering KataGo × LLM — LLM Post-Training & Edge Deployment Post-trained Qwen3-8B (SFT → GRPO) to play 9×9 Go and explain its moves; 4-bit edge deployment and multi-LoRA vLLM serving. Breaking Barriers Hackathon Real-time anomaly detection system deployed on AWS. Top 8 of 32 teams at AWS × Deloitte × AT&T. Other Course Projects A collection of course projects from UCSD.
