cv

You can a find more complete CV, including publications, at the link above. Below is a brief overview:

General Information

Name Daniel Waxman
Website danwaxman.github.io
Address Department of Electrical & Computer Engineering, Stony Brook University

Education

  • 2021-Present
    Ph.D. in Electrical Engineering
    Stony Brook University, Stony Brook, New York
  • 2018-2021
    B.S. in Mathematics & Applied Mathematics and Statistics
    Stony Brook University, Stony Brook, New York

Research Talks

  • 2024
    2024 SIAM New York-New Jersey-Pennsylvania Section Conference
    • Optimizing Observation Locations via Minimizing Information Loss
  • 2023
    Acoustics Research Institute of the Austrian Academy of Sciences
    • Talk Title: Causal Discovery via Quantifying Influences
  • 2023
    Bellairs Workshop on Machine Learning and Statistical Signal Processing for Data on Graphs
    • Talk Title: Bayesian Combination

Teaching

  • Spring 2025
    Understanding Machine Learning (ESE 188 @ SBU, Instructor)
  • Summer 2022
    Random Signals and Systems (ESE 306 @ SBU, Graduate TA)
  • Spring 2022
    Random Signals and Systems (ESE 306 @ SBU, Graduate TA)
  • Fall 2021
    Programming Fundamentals (ESE 124 @ SBU, Graduate TA)

Outreach and Service

  • 2021-2025
    Stony Brook University Graduate Student Organization
    • Primary Senator, Department of Electrical and Computer Engineering
    • Graduate Student Representative for Graduate Council
    • Reviewer for the Distinguished Travel Award
  • 2022-2023
    SBU Strategic Planning Steering Committee
    • Member of the Strategic Planning Steering Committee, helping to identify priorities for upcoming strategic plan.
    • Member of the Project REACH Visioning Committee that drafted a new vision statement for the university

Mentoring

  • CUNY Directed Reading Program
    • Mike Prebil, Gaussian Processes and Bayesian Optimization.
    • Edgar Cuapio Diaz, Gaussian Processes and Bayesian Optimization.
    • Jonathan Jaimangal, Hamiltonian Monte Carlo. [Winner of Outstanding Poster Award
    • Masroor Khokhodzhaev, Dynamic Programming and Reinforcement Learning.
    • Percy Martinez, Fourier Analysis and Its Applications.
    • Isabella Chittumuri, Elements of Statistical Learning.
  • Stony Brook University Directed Reading Program
    • Shailen Smith, Probabilistic Machine Learning.
  • Bayesian Data Analysis for the Global South (GSU)
    • Volunteer Teaching Assistant for online course aimed at the Global South and other underrepresented groups taught by Aki Vehtari