Projects

AI and Design Inspiration

Jing Liao, Qing Chai, Rui Zhao, Chunlei Chai*, (2019)

AI is experiencing the third tide. Interests of a broad applications of AI are increasingly growing. This project aims to explore possibilities of AI supports for early design activities, e.g., idea finding, idea delivery and idea evaluation. We will study theories of inspiration mechanism in design, psychology, and design cognition. Besides, an experimental study would be conducted with HCI principles and methods for practical applications. Finally, (1) a framework of design ideation with AI will be built; (2) novel design supports will be designed for practical design ideation; and (3) implications of barriers and guidelines will be discussed.

Data-driven Business Intelligence Support

Jing Liao, Zitong Chen, Jiawei Zhou, Hanjia Zheng, Chunlei Chai*, (2018)

Data analysis and visualization is playing an increasingly important role in business decision-making. This project aims to provide a computational tool, including automatic information extraction, summarization and visualization to support business judgement. We consider both technological aspects and human aspects to provide reliable and user-friendly interaction. We will study text analysis in Natural Language Processing (NLP), the model of stakeholders (companies, designers, users) in Human-Computer Interaction.

Design Optimization with Genetic Algorithm (DOGA)

Defu Bao, Jing Liao, Chunlei Chai*, Suihuai Yu*, (2017)

This project focus on communicable and reusable computational design tools for industrial design. We propose a software based on SolidWorks, and provide interactive tools for both the model and color design of products. The design tools are driven by Genetic Algorithm (GA). The GA is based on computational analogy of biological process of natural selection. By defining some general metrics for individual (a product), the population (a set of product candidates) gradually evolves towards desirable directions in design space. Designers can interfere the evolve process by selecting desirable individuals. This allows features in the selected individuals are very likely preserved and interleaved during exploration of design space.

Undersampling Method for Pattern Recognition in Non-stationary Environment

Jing Liao, Yuzhe Luo, Yu Jin, Lianghao Xia, Zijing Chen, (2016)

This is the first project conducted during undergraduate years. I invited four classmates to apply research fund from “National university independent research project for undergraduate students”. We worked on pattern recognition problem in condition that data distribution is neither evenly distributed nor static. The research is supervised by Prof.W.W.Y NG. His research covers optimization of neural network and classification problems in machine learning. The findings are summarized in the conference paper “Effects of Different Base Classifiers to Learn++ Family Algorithms for Concept Drifting and Imbalanced Pattern Classification Problems”.