Thinking is hope

Currently Research Projects


LLMs x Generative AI - Center for Socially Responsible Artificial Intelligence, Pennsylvania State University

The "LLMs x Generative AI" project aims to explore, analyze, and demonstrate the capabilities of cutting-edge Generative AI technologies, with a particular focus on Large-Scale Language Models (LLMs). As Artificial Intelligence continues to advance, LLMs such as GPT-4 have emerged as a transformative force, capable of generating human-like text based on the input they receive. This project will delve into the architecture, training, and functionality of these LLMs, investigating their potential to revolutionize industries from content creation and customer support to scientific research and policy analysis. Beyond examining their capabilities, this initiative also seeks to critically evaluate the ethical considerations and potential biases inherent in these systems, striving to outline best practices for their responsible and equitable deployment. Engaging with industry experts, academic researchers, and policymakers, this project aims to produce a comprehensive set of resources—including whitepapers, case studies, and software tools—that illuminate the workings of LLMs and help to guide their future development and application.This is an ongoing project.

Affective Computing in Human Living Environments - Future Lab, Tsinghua University

This project plans to study the theory and method of multimodal affective computing and its application in a human habitat. Using video, voice and other input channels, we obtain the facial expressions, body postures, speech semantics, and other characteristics of humans in a habitat. classified and annotated into a database of human affects, which can open new research explorations in natural human-computer interaction applications in an intelligent human living environments.



Collaboration in AI Drawing - Collaboration and Innovation Laboratory, Pennsylvania State University

The aim of the project is to explore human collaboration and knowledge transmission in AI drawing tasks, i.e., how human users can collaborate with each other, encourage innovation, etc. in this environment. This is an ongoing project.

Computational Aesthetics - Future Lab, Tsinghua University

This study combines aesthetic principles in design with computable image features and, via optimizing a series of key problems, integrates experts' prior knowledge in visual presentation, text semantics, design principles, and cognitive understanding into the multimedia computing framework that facilitates computable automatic design.