Category: projects – old

  • Human-AI Collaboration – LLM for Qualitative Analysis

    Human-AI Collaboration – LLM for Qualitative Analysis

    The recent breakthrough in Large Language Models (LLMs), such as chatGPT, and generative models, such as Stable Diffusion, can be tremendously valuable in supporting analysis and creative tasks. While powerful, such models can be difficult to use, especially for domain experts, such as qualitative researchers and visual artists, who are not experts in machine learning.…

  • Human-AI Collaboration: Generative Models for Artistic Creation

    Human-AI Collaboration: Generative Models for Artistic Creation

    The recent breakthrough in Large Language Models (LLMs), such as chatGPT, and generative models, such as Stable Diffusion, can be tremendously valuable in supporting analysis and creative tasks. While powerful, such models can be difficult to use, especially for domain experts, such as qualitative researchers and visual artists, who are not experts in machine learning.…

  • Visual Analytic for Sensemaking

    Visual Analytic for Sensemaking

    What is Visual Analytics? Visual Analytics is closely related to Data Visualisation, which is also known as Information Visualisation, that helps users discover insights (from data) by presenting it visually. This takes advantage of the visual cognition system (brain is part of it), which is a very powerful computer for detecting certain patterns (we became…

  • Provenance for Sensemaking

    Provenance for Sensemaking

    What is Provenance? The word provenance originally was mainly used for art work, refers to ‘the history of ownership of a valued object or work of art or literature’. For a painting, this includes the information of who painted it when and how the painted changed hands over time. More recently, the concept is expanded…

  • Data Science Provenance

    Data Science Provenance

    Background While there are some efforts to automate the process of build machine learning model (commonly known as ‘AutoML‘), there are many tasks in the different stages of a data science pipeline (see the diagram below) cannot be fully automated. For example, for ‘Data Wrangling’ a decisions have to be made on which dataset to…