I develop explainable AI systems that predict how consumers respond to marketing in digital environments—analyzing 13+ million social media posts to understand what drives engagement, emotion, and action.
My research combines machine learning, natural language processing, and causal inference to decode brand communication during critical moments: from CEO messaging during war to consumer behavior towards AI. Published in the Journal of Public Policy & Marketing and presented at EMAC and AMS, my work bridges computational social science and marketing strategy.
I translate these insights into the classroom, teaching Applied AI for Marketing and Digital Marketing Analytics to MSc students (rated 4.9/5.0). My courses equip future marketers with hands-on skills in Python, machine learning, and AI-powered consumer analytics.
Currently seeking tenure-track positions in digital marketing & AI. Open to research collaborations and AI education partnerships.
🔍 Explore
- 👉 Research
- 👉 Teaching
- 👉 Download CV