Applied mathematics · Statistics · Ocean science
I study phytoplankton physiology, marine primary production, and ocean carbon cycling—connecting mechanistic models, statistical inference, and machine learning with observations.
Small organisms,
planetary significance.
Current appointment
Postdoctoral Fellow · CUNYNew York City College of Technology
Collaborative research
Terra Data to Insights Lab (Terra D2I)& LEAP at Columbia University
Based in
Brooklyn, New YorkUnited States
My work connects biological mechanisms with the patterns we observe in the ocean. I develop models that explain how organisms respond to their environment and methods that quantify what we can learn from marine data.
Modelling photosynthetic responses to light, including photoinhibition and environmental variability, to understand their consequences for marine primary production.
Read the photoinhibition paperDeveloping statistical and machine-learning approaches for surface-ocean pCO₂ reconstruction, with a focus on predictive uncertainty and probabilistic methods.
Explore related publicationsUsing fractional calculus and differential equations to study how past conditions influence microbial growth, ecological interactions, and complex biological dynamics.
Read the microbial memory paper20 works
Open research resources for studying phytoplankton photosynthesis—from fitting individual light-response curves to analysing measurements across marine environments.
Open-source R package
Fit and analyse photosynthesis–irradiance curves, including photoinhibition. Estimate surface irradiance and phytoplankton absorption within a common workflow.
Marine photosynthesis dataset
A compilation of photosynthesis–irradiance measurements from ¹⁴C incubation experiments, developed for Fisheries and Oceans Canada.
More research code on GitHub.
My background spans pure and applied mathematics, statistics, and oceanography. I now bring these perspectives together in research on marine ecosystems and ocean carbon.
Full curriculum vitaeNew York City College of Technology
City University of New York, USA
Surface-ocean pCO₂ reconstruction and uncertainty quantification. Working with the Terra Data to Insights Lab (Terra D2I) & LEAP at Columbia University.
Dalhousie University, Canada
Marine Microbial Macroecology Lab
Department of Oceanography. Phytoplankton photophysiology, environmental variability, and development of piData and piCurve.
Dalhousie University, Canada
Thesis: Modelling Phytoplankton Growth Rates under Changing Resource Conditions.
Supervisor: Dr. Andrew J. Irwin.
Tarbiat Modares University, Iran
Thesis: Fractional Calculus Models of Complex Dynamics in Biological Elements.
Malayer University, Iran
In Iran’s 2013 National M.Sc. Entrance Examination, ranked 237th in applied mathematics and 261st in pure mathematics among 9,230 candidates.
Environmental Management; Ecological Informatics; Qualitative Theory of Dynamical Systems; Scientific Reports; Biogeosciences.
Modelling Primary Production · Split, CroatiaFaculty of Science. Tutorial on piCurve and a research talk on phytoplankton photoinhibition modelling.
Modelling Primary Production · New York, USAFlatiron Institute. Joint presentation with Andrew Irwin on quantifying the effects of photoinhibition on photosynthetic rate.
MM Amirian, G Accarino, V Acquaviva, Improving Global Ocean Surface pCO₂ Prediction Using Biogeographic Residual Correction, American Geophysical Union
G Accarino, MM Amirian, V Acquaviva, Beyond Point Predictions: Diffusion-Based Probabilistic Reconstruction of Global Surface Ocean pCO₂, American Geophysical Union
MM Amirian, E Devred, S Clay, Z Finkel, AJ Irwin. A compilation of photosynthetic rate incubation experiments and analysis using common models CBIOMES Annual Meeting, Flatiron Institute, NY, USA.
MM Amirian, P Fahimi, Z Finkel, E Devred, S Clay, AJ Irwin. Ecophysiological Modeling of Marine Photosynthesis. Ocean Science Meeting .
MM Amirian, P Fahimi, Z Finkel, E Devred, S Clay, AJ Irwin. Ecophysiological Modeling of Marine Photosynthesis. CBIOMES Annual Meeting, Flatiron Institute, NY, USA.
K Kam, E Devred, S Clay, MM Amirian, AJ Irwin, D Atamanchuk, D.W.R Wallace. Re-evaluating methodologies for estimating marine primary productivity in the Labrador Sea using satellite and in situ observations Ocean Optics Conference.
MM Amirian, JT Siddons, AJ Irwin. Extending the Monod model of microbial growth with memory and an application to phytoplankton community dynamics. ASLO Meeting.
MM Amirian, Z Finkel, AJ Irwin. A New Model of Phytoplankton Photoinhibition. CDOGS Annual Meeting, Dalhousie.
MM Amirian, JT Siddons, AJ Irwin. Quantify the Cell Memory and Its Influence on Phytoplankton Resource Competition. CBIOMES Annual Meeting, Flatiron Institute, NY, USA.
MM Amirian, AJ Irwin. Extending the Monod Model of Microbial Growth with Memory. CBIOMES Annual Meeting, Flatiron Institute, NY, USA.
MM Amirian, AJ Irwin. A New Mechanistic Growth Model: Monod-Memory. CBIOMES Annual Meeting, Flatiron Institute, NY, USA.
MM Amirian, Y Jamali. Fractional Calculus Applied to Model Cell Viscoelasticity. 22nd Iranian Conference on Biomedical Engineering (ICBME) - Mathematics in Biomedical Engineering.
MM Amirian, Y Jamali. Prediction of Local Measurement of Cell Viscoelasticity with Fractional Calculus Approach. 3rd Dubai International Conference on New Approaches in Sciences Engineering & Technology, 2015 December 9-10 Zayed University.
MM Amirian, A Mazarei. Prediction of Action Potential in Neuron with Fractional Calculus Approach. 3rd Dubai International Conference on New Approaches in Sciences Engineering & Technology, Zayed University, December 9–10.
R (advanced); working knowledge of Python, Julia, and MATLAB. Differential-equation modelling, parallel computing, data processing, and visualisation.
LaTeX, Jupyter, and Pluto.
Farsi (native); English (fluent).
Generalised additive models, mixed-effects models, Bayesian modelling, regularisation, and nonlinear model fitting.
Predictive modelling with tidymodels, XGBoost, random forests, and kernel methods.
My teaching spans introductory statistics, probability, mathematical modelling, and data science. My mentoring connects mathematical methods with questions in marine science and biological dynamics.
Course instructor · Dalhousie University
Summer 2024 · Fall 2025, sections 01 & 02
2026 — present · Columbia University
Symbolic regression methods for global pCO₂ reconstruction.
2025 — present · Dalhousie University
Quantifying mathematical sources of uncertainty in net primary production estimates.
2023 · Independent researcher
Fractional-order models of neural dynamics and stability analysis. This collaboration resulted in a publication in Cognitive Neurodynamics.
Conversations, collaborations, and a PhD defence—moments from my research journey in mathematics and ocean science.
Learning the Earth with Artificial Intelligence & Physics
Hosted by LEAP, an NSF Science and Technology Center based at Columbia University, bringing together the Earth science, artificial intelligence, and physics communities.
Simons Foundation · New York City
An opportunity to consolidate ideas and collaborations as CBIOMES approaches its tenth and final year.
CBIOMES workshop · New York City & online
As machine learning plays a growing role in ocean science, CBIOMES researchers met to advance shared tools for modelling the ocean’s dynamic biological systems.
Faculty of Science · Split, Croatia
A workshop on modelling primary production, including my piCurve tutorial and a research talk on phytoplankton photoinhibition.
Dalhousie University · Halifax, Canada
Defending my PhD in Statistics: Modelling Phytoplankton Growth Rates under Changing Resource Conditions.
Simons Foundation · New York City
Nearly sixty collaborators came together for three days of face-to-face connection, scientific exchange, and collaborative momentum.
Simons Foundation · New York City
A three-day workshop on modelling primary production, bringing researchers together to discuss how to represent and understand phytoplankton productivity.
Behind the Paper · Springer Nature · 2025
The story behind my work on modelling phytoplankton photoinhibition.
Read the articleResearch coverage · CBIOMES · 2025
Coverage of our phytoplankton photoinhibition research.
Read the featureMedia coverage · Scienmag · 27 August 2025
Scienmag coverage of our paper on modelling phytoplankton photoinhibition.
Read the coverage
