Integrating text, images, sensors and social signals to understand population health, research trends, and societal dynamics.
Interdisciplinary, reproducible, and impactful work.
Our research spans multiple disciplines, combining computational methods, data science, and domain expertise to address fundamental scientific questions.
Developing advanced NLP techniques for text analysis, sentiment analysis, and information extraction from large-scale textual data across multiple languages and domains.
Applying machine learning and statistical methods to extract insights from complex datasets, with focus on social media data, healthcare data, and business intelligence.
Creating innovative text mining approaches for knowledge discovery, pattern recognition, and automated information extraction from unstructured textual data.
Using computational methods to study social phenomena, online behavior, and information diffusion in digital platforms and social networks.
Committed to fostering the next generation of researchers and innovators through engaging courses and hands-on mentorship.
An introduction to object‑oriented programming (OOP) with Java. Students learn core OOP concepts (classes, objects, abstraction, encapsulation, inheritance, polymorphism), Java syntax and control structures, and how to design, implement, test and document small to medium programs using sound software‑engineering practices.
Covers data structures and advanced programming techniques in Java. The module deepens OOP knowledge, introduces advanced language features and design principles, and develops problem‑solving skills for implementing algorithms in contemporary software settings, including collaborative, team‑based development.
Our research portfolio spans diverse areas, from fundamental science to practical applications, all aimed at pushing the boundaries of knowledge.
This study examines the dynamics of Chinese fashion aesthetics through social media analysis using multimodal data, and explores how fashion trends are represented, communicated, and diffused online.
Funding: Funding welcome
Learn MoreAn intelligent platform integrating multimodal data to predict chronic disease flare-ups and recommend personalized behavioral changes, and will evolve into a digital twin powered by federated learning for privacy-preserving, adaptive healthcare.
Funding: Funding welcome
Learn MoreAn assistive algorithm for visually impaired users that combines multi-camera vision to enhance spatial perception and object awareness and integrating vLLM for contextual understanding and optional LiDAR input for enhanced depth sensing, aiming to deliver robust, real-time assistance to improve user independence and environmental interaction.
Funding: Funding welcome
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