Meet Andrei Kirilenko, Ph.D.

Associate Professor & Graduate Coordinator

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Education

• Ph.D. Computing Center of Russian Academy of Science, Russia
• M.S. Moscow State University, Russia
• Postdoctoral research: US Environmental Protection Agency, USA; European Forest Institute, Finland

Andrei Kirilenko CV – February 2026

Mailing Address

FLG 190B
P.O. Box 118208
Gainesville, FL 32611-8208

Biography

Andrei Kirilenko is an Associate Professor and the Graduate Coordinator in the Department of Tourism, Hospitality & Event Management at the University of Florida. His research sits at the intersection of tourism and sustainability, geospatial analytics, and artificial intelligence. He uses data mining, GIS, and machine learning—including large language models—to analyze tourists’ digital traces (e.g., online reviews, social media content, mobility proxies, and other digital footprints) and citizen-science observations. A complementary line of work applies virtual reality (VR) to tourism research, using immersive stimuli and experimental designs to measure how people experience virtual travel to real destinations and fantasyscapes.

Research Focus

• Data mining and AI for tourism and hospitality research (text, image, and video analytics).
• GIS and spatial analysis of tourism phenomena (flows, clustering, colocation, and place-based behavior).
• Large language models for scalable analysis of destination image, authenticity, and online discourse.
• Social media, volunteer geographical information, and other tourists’ digital traces (reviews, influencer content, platform comparisons).
• Sustainability, climate and environmental communication, and pro-environmental behavior.
• Citizen-science data (e.g., biodiversity/greenspace observations) to connect recreation, well-being, and conservation outcomes.
• Virtual reality tourism (traditional vs hyperreality VR) and technology-enabled measurement of visitor experiences.

Methods & Toolkits

• Machine learning and statistical modeling for prediction, classification, clustering, and forecasting.
• Natural language processing (including LLM-assisted topic modeling and qualitative-to-quantitative pipelines).
• Multimodal analytics that combine text, images, and video signals from digital platforms.
• GIS workflows for spatial joins, hotspot analysis, movement inference, and spatial econometrics.
• Social network analysis and platform-level comparisons (who influences whom, and where).
• Experimental methods, including VR-based experiments, neuromarketing, and measurement of user responses.

Courses

• Data Mining with Social Data (HMG 6583C / LEI 4905)
• Research Methods (HLP 6535 / LEI 4880)
• Evaluation Procedures in Health and Human Performance (HLP 6515)

Links

Google Scholar: https://scholar.google.com/citations?user=HqV8fnwAAAAJ&hl=en

ResearchGate: https://www.researchgate.net/profile/Andrei-Kirilenko