Machine Learning & Computational Science Researcher

Yeganeh Abdollahinejad

Building trustworthy machine learning for health, human signals, and information integrity.

I'm a researcher at Michigan State University working at the intersection of machine learning, computational modeling, and data science. My work spans trustworthy multimodal ML, EEG and physiological signal analysis, and mathematical models for medicine — with a steady focus on making models that are accurate, calibrated, and explainable.

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Research areas

What I work on

Trustworthy & multimodal ML

Misinformation detection, cross-modal reasoning, and models that stay calibrated and honest under real-world shift.

Human signals & affective computing

EEG and physiological signals for emotion and fatigue recognition that generalize to unseen people.

Computational modeling for health

Mechanistic models, Bayesian inference, and ML for oncology, nanoparticle transport, and clinical decision support.

Explainable & responsible AI

Saliency, uncertainty, and fairness — making model decisions legible, especially in medicine.

Selected publications

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Recent notes

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