Scholar
Daniel Beaglehole
Google Scholar ID: wO-FY_4AAAAJ
PhD Student, UCSD
Citations & Impact
Citations
284
H-index
8
i10-index
8
Publications
13
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- Selected publications: 'Mechanism for feature learning in neural networks and backpropagation-free machine learning models', 'xRFM: Accurate, scalable, and interpretable feature learning models for tabular data', 'Toward universal steering and monitoring of AI models', 'Sampling Equilibria: Fast No-Regret Learning in Structured Games'.
Research Experience
- Student Researcher at Google DeepMind working on feature learning; ML Research intern at Goldman Sachs.
Education
- PhD: Computer Science and Engineering, UC San Diego, advised by Professor Mikhail Belkin; MS: Computer Science, Columbia University, mentored by Professor Alexandr Andoni.
Background
- Research interests: conceptually-driven machine learning and algorithmic methods; feature/representation learning; deep learning (theory + applications); steering and monitoring LLMs; tabular/scientific data.
Miscellany
- Contact: dbeaglehole@ucsd.edu; supported by the ARCS Foundation Fellowship.
Co-authors