Scholar
Alexandre Day
Google Scholar ID: OQK_iFEAAAAJ
Director of Data Science at Capital One
Citations & Impact
Citations
2,164
H-index
10
i10-index
10
Publications
19
Co-authors
8
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Published multiple papers on machine learning and its applications in physical sciences, participated in projects such as developing self-consistent scalable clustering algorithms, writing an introductory guide to ML for physicists, and exploring the phase diagram of quantum state preparation via Q-learning.
Research Experience
- Serves as a Director of Data Science at Capital One; has conducted research on the application of machine learning in physical sciences, including self-consistent scalable clustering, an introductory review to ML, and reinforcement learning for quantum control.
Education
- Ph.D. from Boston University, supervised by Pankaj Mehta. Focused on using reinforcement learning (e.g., Q-learning, MCTS) and unsupervised learning (e.g., clustering, auto-encoders, embeddings) to tackle issues in physics and biology.
Background
- A Director of Data Science at Capital One. Research interests include applying machine learning methods to problems in quantum statistical physics and applied computational biology for cancer immunotherapy.
Miscellany
- Open to impromptu chats about ML, physics, and science in general, welcoming emails with questions.
