Academic Staff

My research focuses on integrating behavioral, environmental, and biological data to develop personalized and holistic mental health interventions. I aim to create innovative, scalable methods—such as gamified experimental paradigms—to objectively quantify cognitive and emotional responses, including attention, emotional bias, strategic flexibility, and achievement. These assessments are complemented by physiological measures like EEG and biomarker analyses from biological samples, providing multi-dimensional insights into individual mental health profiles.

A key element of my approach involves employing advanced analytical techniques for high-throughput, cost-effective detection of a broad spectrum of chemical compounds and pollutants. This capability supports environmental monitoring efforts, such as assessing water sources for antibiotic residues and antimicrobial resistance (AMR) genes—factors increasingly linked to gut microbiota disruption and systemic inflammation that influence mental health.

To integrate these diverse data streams, I am constructing a knowledge graph platform that employs triplet extraction and merges multiomics datasets—including genomics, transcriptomics, proteomics, epigenomics, and metabolomics. This comprehensive system aims to elucidate the biological mechanisms underlying mental health conditions and facilitate the development of precision medicine and nutrition strategies. Insights derived from environmental monitoring, combined with biological data, support personalized risk assessment and targeted interventions.

Additionally, I am developing the Art Sentiment Intelligence Analysis Platform, which quantifies how visual art influences emotional states. This project leverages the world's largest visual art expression database and deep learning techniques to transform subjective art appreciation into objective, data-driven insights. By analyzing the relationship between artworks and human emotions—such as positive arousal and negative emotion mitigation—this platform provides valuable support for art-based emotional research and therapeutic interventions. Its core strengths lie in its robust technological foundation and extensive resource base, encompassing diverse art forms and styles, all deeply annotated via AI to facilitate precise analysis of emotional responses.

Furthermore, my research explores the complex interplay between environmental factors—such as waterborne AMR—and mental health outcomes. Recent evidence suggests that antibiotic exposure can disrupt gastrointestinal microbiota and is associated with an increased risk of depression, highlighting the importance of monitoring environmental reservoirs of AMR. By utilizing advanced water monitoring techniques, including metagenomic analysis and chemical profiling, I seek to detect and quantify AMR genes and antibiotic residues in water sources, providing early indicators of environmental stressors that may influence mental health.

Ultimately, my research endeavors to establish an interconnected, multidisciplinary framework that leverages cutting-edge analytical tools, behavioral science, environmental monitoring, and multiomics integration. This integrated approach aspires to enable personalized, evidence-based interventions addressing both psychological symptoms and their underlying biological and environmental factors. By fostering an open, interdisciplinary research ecosystem, I aim to promote holistic strategies for mental well-being, combining art-based therapies, precision nutrition, and environmental health strategies to mitigate the impact of environmental AMR on mental health.