Integrating biological concepts

Looking at how exaggerated media stimuli trigger heightened responses in humans and decisions through a supernormal stimulus lens.

Supernormal stimuli are exaggerated versions of natural stimuli that elicit stronger responses than the original, evolutionary-relevant triggers.

Online content often amplifies market narratives through sensational headlines, vivid visuals, and emotionally charged language - acting as supernormal stimuli. This triggers heightened fear, greed, or excitement, leading to exaggerated reactions like panic selling during downturns or speculative buying during market bubbles, disrupting rational decision-making and fueling volatility.

Simulating data using AI

Use experimental data associated to market contexts to generate synthetic data.

Biometric data gathering

Collect Neural, Eye-tracking and Biometric (NEB) data from carefully crafted experiments that isolate how supernormalization triggers choice on markets

AI Market Predictions

Use biometric and synthetic data as additional predictor in forecasting market prices and financial bubbles crashes

Synthetic datasets creation

Generate biometric datasets corresponding to experimental market conditions using statistical and AI techniques

About me

I am a lecturer at Bucharest Business School, part of the Bucharest University of Economic Studies.

Before joining the university, I was a Fulbright scholar and later a postdoctoral researcher in decision neuroscience at the California Institute of Technology, where I studied asset bubbles and the role of supernormal stimuli in financial decision-making under the supervision of Colin Camerer.

My research focuses on the biological underpinnings of human behavior and decision-making, with a particular interest in using AI to optimize choices in finance, consumer behavior, and online social media dynamics.

Please feel free to reach out on any of the above topics.