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      Dr Leishi Zhang

      BA, MSc, PhD
      ROLE: Senior Lecturer Computing Science/ Data Intensive Systems
      SCHOOL: Science & Technology
      DEPARTMENT: Computer Science
      TELEPHONE: +44 (0)20 8411 2843
      EMAIL: L.X.Zhang@mdx.ac.uk
      1. Biography &
        Qualifications
      2. Learning &
        Teaching Interests
      3. Research Outputs &
        Interests
      4. Funded Research &
        Knowledge Exchange Projects
      5. Engagement &
        Impact

      • Biography &
        Qualifications

        Dr Leishi Zhang is Senior Lecturer of Data Intensive Systems at Middlesex University, London. Before joining Middlesex, she was a post-doc research scientist at Chair of Data Analysis and Visualization , University of Konstanz, Germany (2010-2013), working with Professor Daniel Keim and his group on a number of visual analytics projects . She was also a post-doc at the Computing Laboratory, University of Kent, UK (2007-2010) working with Dr. Peter Rodgers on the EPSRC funded project Visualization with Euler Diagrams .

        Dr Zhang received her Ph.D. from Brunel University, UK, under the supervision of Professor Xiaohui Liu. The title of her PhD thesis is Interactive Visualization for the Dynamic Modelling of Time Series Gene Expression Data.


        Languages Spoken

        Chinese (native), English, German (basic)

      • Learning &
        Teaching Interests

        Teaching

        Most recently involved in the teaching of the following modules:

        • CSD1200: Information In Organisations
        • CSD4030: Interaction and Visualization
        • BIS3214: Data Warehouse and Business Intelligence

        Project Supervision

        Most recently involved in the supervision of the following modules:

        • BIS4992: Postgraduate Computing Project
        • BIS3322: Information Systems Project
        • CMT3333: Software Development Project
        • CMT4141: Research Project (Individual)

      • Research Outputs &
        Interests

        A major theme Dr. Zhang's research is to develop data analysis and visualization techniques for extracting and visualizing patterns and relations in large complex data. There are three main strands to Dr. Zhang’s research: visual analytics on different application data, visualizing complex set relations and interactive visual projection techniques for analyzing patterns in high-dimensional data.

        Publication Feed

        Case-based reasoning of a deep learning network for prediction of early stage of oesophageal cancer

        Gao, Xiaohong W. and Braden, Barbara and Zhang, Leishi and Taylor, Stephen and Pang, Wei and Petridis, Miltos (2019) Case-based reasoning of a deep learning network for prediction of early stage of oesophageal cancer. In: 24th UK Symposium on Case-Based Reasoning (UKCBR 2019), 17 Dec 2019, Cambridge. (Accepted/In press)

        How analysts think: a preliminary study of human needs and demands for AI-based conversational agents

        Hepenstal, Sam and Wong, B. L. William and Zhang, Leishi and Kodagoda, Neesha (2019) How analysts think: a preliminary study of human needs and demands for AI-based conversational agents. Proceedings of the Human Factors and Ergonomics Society Annual Meeting , 63 (1). pp. 178-182. ISSN 2169-5067

        Algorithmic transparency of conversational agents

        Hepenstal, Sam and Kodagoda, Neesha and Zhang, Leishi and Paudyal, Pragya and Wong, B. L. William (2019) Algorithmic transparency of conversational agents. In: IUI 2019 Workshop on Intelligent User Interfaces for Algorithmic Transparency in Emerging Technologies, 17-20 Mar 2019, Los Angeles, CA, USA.

        Making machine intelligence less scary for criminal analysts: reflections on designing a visual comparative case analysis tool

        Jentner, Wolfgang and Sacha, Dominik and Stoffel, Florian and Ellis, Geoffrey and Zhang, Leishi and Keim, Daniel A. (2018) Making machine intelligence less scary for criminal analysts: reflections on designing a visual comparative case analysis tool. The Visual Computer , 34 (9). pp. 1225-1241. ISSN 0178-2789

        Towards an instrument for measuring sensemaking and an assessment of its theoretical features

        Alsufiani, Kholod and Attfield, Simon and Zhang, Leishi (2018) Towards an instrument for measuring sensemaking and an assessment of its theoretical features. In: Fourth International Conference on Emerging Research Paradigms in Business and Social Sciences (ERPBSS-2018), 16-18 Jan 2018, Dubai.

        182625

      • Funded Research &
        Knowledge Exchange Projects

      • Engagement &
        Impact

        Dr Zhang is the PC member of a number of conferences and workshops, most recent ones including: IS&T VDA'17, IDA'16, CGVC'16, SKG’16

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