Scholar
Daniel Waxman
Google Scholar ID: _QM1YGQAAAAJ
PhD Candidate, Electrical Engineering, Stony Brook University
Citations & Impact
Citations
24
H-index
3
i10-index
0
Publications
9
Co-authors
6
list available
Publications
Resume (English only)
Academic Achievements
- Paper 'Tangent Space Causal Inference' accepted as a poster at NeurIPS 2024; Paper 'Dynamic Online Ensembles of Basis Expansions' accepted to Transactions on Machine Learning Research (TMLR); Presented 'DAGMA-DCE' at ICASSP 2024; Submitted paper 'Designing an Optimal Sensor Network via Minimizing Information Loss'; Submitted paper 'Bayesian Ensembling: Insights from Online Optimization and Empirical Bayes'.
Research Experience
- Currently a Research Intern at Basis; Mentor in the Directed Reading Programs at CUNY and SBU, guiding students in semester-long reading projects in math, machine learning, and statistics.
Education
- PhD Candidate, Department of Electrical and Computer Engineering, Stony Brook University; Undergraduate degree in Mathematics and Statistics from Stony Brook University.
Background
- Broadly interested in Bayesian machine learning and causality, with specific interests in online and continual learning and Gaussian processes. Particularly focused on advancing theoretical methods for applications in earth sciences and consciousness science.
Miscellany
- Senator in the SBU Graduate Student Organization; Former member of Project REACH and the SBU Strategic Planning Steering Committee.
