Dynamical systems & filtering
Kalman filtering, data assimilation, and fixed-point smoothing to reconstruct dynamical states from sensor observations and system matrices.
Discuss this work ↗Applied Mathematician · Data Scientist
Mathematical models.
Computational insight.
Better decisions.
I’m Teona Zurabashvili, an Applied and Computational Mathematics Ph.D. student at Virginia Tech. My background spans professional data science, computer science, and information systems.
Currently based atVirginia TechBlacksburg, Virginia
01 · Profile
“I develop computational methods for extracting reliable insight from dynamic, uncertain, and data-rich systems.”
My doctoral work centers on computational modeling and predictive simulation using stochastic differential equations, nonlinear-system analysis, and finite-element methods for PDEs.
Additional work in filtering and data assimilation focuses on reconstructing dynamical systems from sensor observations and known system matrices. Together with industry experience in data science, these projects connect mathematical theory, computation, and real-world data.
02 · Research
Models, methods
& uncertainty.
My research examines systems governed by uncertainty, from reconstructing PDE states using noisy observations to calibrating stochastic volatility models against market data.
Stochastic & financial models
Heston stochastic volatility simulation and parameter calibration using indirect inference, GARCH-based time-series analysis, and S&P 500 return data.
Discuss this work ↗Nonlinear systems & PDEs
Computational analysis of nonlinear systems using numerical PDEs, spectral and finite-element methods, optimization, and matrix computations.
View toolkit ↓03 · Experience
Data science
in practice.
2021-22Data Scientist
Risk analysis, customer behavior modeling, and banking analytics
TBI Bank · Sofia, Bulgaria
·2020-21Data Scientist
Predictive models, analytical tools, reports, and client dashboards
BDO Digital · Tbilisi, Georgia
·2017Developer Intern
Front-end and back-end development for e-commerce platforms
iSenseLabs · Sofia, Bulgaria
·04 · Education
Mathematical depth,
computational range.
Python, SQL, MATLAB, C++, R, Java, and C#. Additional strengths include predictive modeling, machine learning, state estimation, time series, Git, MySQL, Excel, DAX, Stata, and Overleaf.
- 2028 Ph.D., Applied & Computational Mathematics Virginia Tech · Expected
- 2025 M.S., Applied & Computational Mathematics Virginia Tech
- 2019 B.A., Mathematics American University in Bulgaria · Minors in CS & Information Systems
05 · Contact
Let’s solve something
challenging.
Open to opportunities in data science, quantitative modeling, scientific computing, and applied research.