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My name is Mahshid Ahmadian. I am currently a Ph.D. candidate in System Modeling and Analysis with a concentration in Statistics and Data Science in the Department of Statistical Sciences and Operations Research at Virginia Commonwealth University. I have a Master's degree in Economical and Environmental Statistics. |
I have a passion for solving complex, real-world problems through statistical modeling, machine learning, and high-performance computing (HPC). My expertise spans Bayesian statistics, spatiotemporal modeling, predictive analytics, and statistical computing, allowing me to work across environmental science, healthcare, and finance. With extensive experience in statistical consulting, I have guided individuals and organizations through challenging academic and industrial problems, demonstrating my ability to extract insights from any dataset, regardless of complexity or field.
Education
- Virginia Commonwealth University, Systems Modeling and Analysis (Concentration in Statistics and Data Science), Ph.D.
- Isfahan University of Technology, Economical and Environmental Statistics, M.Sc.
- Isfahan University of Technology, Statistics, B.Sc.
Technical Expertise
- Statistical Modeling & Data Science: Predictive Modeling & forecasting, Machine Learning , Bayesian analysis & inference, Longitudinal data analysis, High-dimensional data analysis, Spatiotemporal modeling
- Computational & Mathematical Techniques: Optimization, High-Performance Computing (HPC) & parallel computing, Rcpp (integrating C++ in R)
- Programming & Statistical Software: R, Python, RC++, SQL, SPSS, SAS, Excel
Research
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About
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As a data scientist specializing in spatiotemporal modeling, I develop high-performance computational algorithms for imputing and predicting location data from acoustic tracking receivers. My research directly supports data-driven decision-making in fisheries management, optimizing large-scale models using High-Performance Computing (HPC) and parallelization techniques. I leverage Rcpp to integrate efficient C++ implementations within R, accelerating Bayesian inference and spatial statistics computations.
My expertise spans predictive analytics, spatial statistics, machine learning, and statistical computing (R, Python, C++), enabling scalable solutions for analyzing sparse, irregular, and high-dimensional datasets in complex real-world applications. |
Scholarships and Awards
- NSF Participation Award,
Awarded for participating in the NSF Workshop on Data-driven Modeling and Prediction of Rare and Extreme Events. - Best poster presentation award,
ASA Virginia Chapter 2023 Annual Meeting, Richmond, VA, Oct. 2023. link. - 2023 VASG Graduate Research Fellowship,
Virginia Sea Grant, Virginia, Sep 2023. link. - Boyd Harshburger Travel Award,
Southern Regional Council on Statistics, the 2022 Research Conference. - Scholarship Award of the Honor Society of Phi Kappa Phi,
College of Humanities and Sciences, Virginia Commonwealth University, Richmond, VA, Apr. 2022. - NSF Graduate Travel Award,
Southern Regional Council on Statistics, the 2021 Research Conference.
Publications
- Reid, J., Ahmadian, M., Jennings, D., Abad Pepperl, A., Golding, S. E., & Johnson, A. A. (2025). Saying It Aloud: Inclusive Teaching Statements Impact on Student Success and Engagement. Journal of College Science Teaching. (Accepted).
- A New Perspective to Fish Trajectory Imputation: A Methodology for Spatiotemporal Modeling of Acoustically Tagged Fish Data (submitted)
- Forecasts of Motor Vehicle Traffic Fatalities in the United States using Time Series Regression Models (submitted)
Leadership and Community Engagement
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Community Involvement
Mentoring experiences Volunteering Experience |
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