Curriculum Vitae
Samantha Magid
Applied and computational mathematician studying scientific productivity, stochastic processes, computational social science, and generative modeling.
Research Interests
- Complex systems
- Science of science
- Estuarine and intertidal systems
- Stochastic processes
- Application of natural phenomena
- Scientific productivity
- Sequential neural networks
- Generative modeling
- Metaresearch
- Coupled air-sea climate systems
Education
Master of Science in Complex Systems and Data Science
University of Vermont
Vermont Complex Systems Institute
Expected Spring 2028
- UVM Graduate Merit Scholar
Bachelor of Science in Data Science and Environmental Science
Boston University
Faculty of Computing & Data Sciences
- Lara Vincent Undergraduate Researcher
Research Experience
Research Assistant
Science and Humanities Lab | Vermont Complex Systems Institute May 2026–present
- Develop models of scientific productivity, including autoregressive, hurdle, self-exciting, and history-dependent processes.
- Fit and simulate generative models using longitudinal publication data.
- Compare simulated and empirical patterns in productivity, inactivity, cumulative output, rank persistence, career-stage variation, and year-to-year fluctuations.
- Investigate whether temporary opportunity structures, recent productivity, and prior inactivity can explain persistent differences in scientific output without invoking fixed individual traits.
- Design statistical tests for history dependence, Markov-order violations, self-excitation, dropout, restart behavior, and long-range trajectory persistence.
- Evaluate models using distributional, predictive, and trajectory-level diagnostics, including cross-validation, bootstrap confidence intervals, rank-mixing analyses, goodness-of-fit tests, and held-out simulations.
- Produce publication-ready figures, technical summaries, and research materials for an ongoing study of scientific productivity as a complex stochastic process.
Undergraduate Principal Investigator
Uca spp. Bioturbation Survey | Boston University Marine Program
September 2022–January 2023
- Proposed and led an independent study of fiddler-crab overpopulation as a complex biophysical system.
- Investigated how stochastic bioturbation feedback cycles contribute to salt-marsh erosion.
- Designed and fabricated a custom tidal-forcing generator for controlled simulation of periodic intertidal conditions.
- Developed an experimental system for studying feedback-driven marsh dynamics without disrupting field sites.
- Coordinated with marine scientists and field experts as one of the program’s youngest principal investigators.
- Completed the project’s first phase and produced reusable tools for future estuarine-modeling research
Publications
Publications and manuscripts are listed on the Publications page.
Presentations
Presentations, posters, and invited talks will be listed here.
Technical Skills
Programming: Python, R, SQL, Rust
Scientific computing and machine learning: pandas, NumPy, SciPy, scikit-learn, Matplotlib/seaborn, TensorFlow, XGBoost
Research and visualization tools: Git, GitHub, Jupyter, Quarto, LaTeX, QGIS, ArcGIS, Power BI, Tableau
Methods: Statistical modeling, stochastic simulation, time-series analysis, generative modeling, machine learning, geospatial analysis, and data visualization
Affiliations
- Vermont Complex Systems Institute | with Dr. Sam Zhang
- Boston University Faculty of Computing & Data Sciences | with Dr. Mayank Varia
- Boston University Spark! Program
- Boston University Marine Program | with Dr. Robinson Fulweiler
Contact
Email: samantha.magid@uvm.edu
GitHub: crabwife
LinkedIn: Samantha Magid