Category: Visual Analytics
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An Approach to Human-Machine Teaming in Legal Investigations Using Anchored Narrative Visualisation and Machine Learning (International Workshop on AI and Intelligent Assistance for Legal Professionals in the Digital Workplace)
The First International Workshop on AI and Intelligent Assistance for Legal Professionals in the Digital Workplace (LegalAIIA 2019) During legal investigations, analysts typically create external representations of an investigated domain as resource for cognitive offloading, reflection and collaboration. For investigations involving very large numbers of documents as evidence, creating such representations can be slow and…
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Uncertainty of visualizations for SenseMaking in criminal intelligence analysis (EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization)
EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization (EuroRV3) 2018 Uncertainty in visualization is an inevitable issue for sensemaking in criminal intelligence. Accuracy and precision of adoptedvisualization techniques have got greater role in trustworthiness with the system while finding out insights from crime relateddataset. In this paper, we have presented a case study to…
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Combining Data Visualization with Machine Learning to Make Sense of Large Social Media Data (2018-2019, US$20,000)
Funder: Microsoft Azure Research Award Date: 2018-2019 Funding: US$20,000 In this project we utilise the Microsoft Azure to analyse over 1.5 billion tweets using an updated SAVI (Social Analytics VIsualisation) system.
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Organiser of the Dagstuhl Seminar on “Provenance and Logging for Sense Making”
Dagstuhl seminar is a series of Computer Science seminars hosted at the Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH in Germany. It is an invitation only seminar and a selected group of leading international experts on a certain topic spend a week in the Dagstuhl castle discussing the solutions to the most challenging research problems related…
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Analytic Provenance as Constructs of Behavioural Markers for Externalizing Thinking Processes in Criminal Intelligence Analysis (Community-Oriented Policing and Technological Innovations)
Chapter 10 of the book Community-Oriented Policing and Technological Innovations (2018) Studying how analysts use interaction in visualization systems is an important part of evaluating how well these interactions support analysis needs, like generating insights or performing tasks. Analytic Provenance commonly known as interaction histories contains information about the sequence of choices that analysts make…
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Analytic provenance for criminal intelligence analysis (Journal of Network and Information Security)
Chinese Journal of Network and Information Security (2018) In criminal intelligence domain where solution discovery is often serendipitous,it demands techniques to provide transparent evidences of top-down and bottom-up analytical processes of analysts while sifting through or transforming sourced data to provide plausible explanation of the fact.Management and tracing of such security sensitive analytical information flow…
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Evaluating interactive visualization of multidimensional data projection with feature transformation (Multimodal Technologies and Interaction)
Multimodal Technologies and Interaction 2017 There has been extensive research on dimensionality reduction techniques. While these make it possible to present visually the high-dimensional data in 2D or 3D, it remains a challenge for users to make sense of such projected data. Recently, interactive techniques, such as Feature Transformation, have been introduced to address this.…
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Member of the EPSRC Peer Review College
EPSRC stands for ‘Engineering and Physical Sciences Research Council’. It is the main funding body for UK research in the areas including engineering, mathematics, and physics. Computer Science is one of the EPSRC research areas. All the funding applications to EPSRC are reviewed by its Review College members.
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Phong Nguyen, 2017, PhD in Computer Science
Data Scientist at Red Sift, 2011-2017, “Spatial-Temporal Analysis of Online Social Information and its Provenance using Visual Analytics”, School of Engineering and Information Sciences, Middlesex University, UK.
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Invited talk at the data+visual meetup
This is the talk I given at the data+visual meeting in London in Aug 2016 http://www.slideshare.net/kaixu79/making-sense-of-big-data-visual-analytics-and-provenance
Human-AI Collaboration 