An app to assist with field behavioral analysis

A collection of functions and scripts designed to create, manipulate, and analyze FaceGen faces and face models

Projects, essays, and reports for the Mind, Brain and Behavior program at JLU Giessen.

A deep exploration of how human psychology shapes fraud behavior and how those patterns become measurable signals in transaction data. This article reveals the behavioral, cognitive, and economic forces behind fraud, explaining how ML models detect deviations, anomalies, and intent hidden within financial transactions.

An exciting Big Data project done during a course I took at the Technion university

Deep behavioral and machine learning analysis explaining why mobile users systematically report lower satisfaction with AI systems. Includes SHAP explainability, cognitive load modeling, device-context effects, interaction metadata analysis, and end-to-end reproducible research code and visuals.

Simulate people with GPT models and generate response statistics

EHTYGA is an open-source, human-centered content tool designed to synthesize persuasive messaging while critically filtering for cognitive manipulation. It algorithmically identifies rhetorical techniques—scarcity, urgency, fear—that often erode trust, nudging creators toward ethically sound communication.

Eatopia gives you personalized nutrition help, recipe ideas, and photo-based meal tracking so you can stick to your health goals.

Do you understand what a “95% confidence interval” means?

The Behavioral Economics Simulator models the decisions of agents (consumers/investors) influenced by psychological biases in a dynamic, simplified market environment. It was programmed using Eclipse IDE for Java Developers codespace and uses AI bias modeling.

R-based ETL and quality control pipeline for ELAN annotation files used in infant motor behavior research

A minimalist macOS productivity timer using behavioral psychology (variable ratio reinforcement & BRAC cycles) to enhance focus and productivity.

Behavioral analytics project combining Psychology and Machine Learning. Uses XGBoost & SHAP to decode retention drivers and predict turnover.

This repository explores the activation patterns of A2 noradrenergic neurons in fear-conditioned rats, using statistical analyses like t-tests and linear regression in R. It focuses on the differences in dopamine β-hydroxylase (DbH) neuron activation between various environmental conditions.

Abu Hasnat Abdullah's personal website.

Possible projects on Behavioral Machine Learning

Collection of scripts to perform various experiments with behavioral messages