Machine Generalize Learning in Agent-Based Models: Going Beyond Surrogate Models for Calibration in ABMs.
S. Najafzadehkhoei, G. Vega Yon, B. Modenesi, D. S. Meyer. arXiv preprint, 2025.
A novel approach for classifying Monoamine Neurotransmitters by applying Machine Learning on UV plasmonic-engineered Auto Fluorescence Time Decay Series (AFTDS).
M. Mohammadi, S. Najafzadehkhoei, G. Vega Yon, Y. Wang. arXiv, July 9, 2025.
arXiv:2507.07227
Manuscripts in Preparation
imaginarycss: An R package for Cognitive Social Structures.
S. Najafzadehkhoei, G. Vega Yon, K. Tanaka. In preparation (Sept. 2025).
Software
epiworldRcalibrate — R package for ML-based calibration in ABMs.
Status: CRAN/JOSS submission in preparation.
imaginarycss — R package for CSS analysis (data model, error taxonomy, accuracy metrics, null models).
Talks & Presentations
Mar 26, 2025 — ENAR Spring Meeting (Oral): “Automatic Calibration of Agent-Based Models using Deep Neural Networks.” New Orleans, LA.
Aug 2025 — JSM 2025 (Selections): Oral & Poster accepted (unable to attend). Nashville, TN.
Jan 2025 — DELPHI Data Science Initiative (Poster): “Automatic Calibration of Agent-Based Models using Deep Neural Networks.”
Jul 11–12, 2024 — CDC (Oral): “Comparing the Performance of Different Rt Estimations: Insights from an Agent-Based Network Model Study.” Atlanta, GA.