Profile

Dr. Matt Willis earned his PhD in Information Science & Technology from Syracuse University. He has been a researcher in academic, government, and private institutional settings including Sandia National Laboratories, the U.S. Department of Veterans Affairs, and several university affiliated research centres where he was a contributor to multiple grants from the National Science Foundation (NSF), National Institutes of Health (NIH), Defence Advanced Research Projects Agency (DARPA), and Intelligence Advanced Research Projects Activity (IARPA).

Matt joined the Oxford Internet Institute to work on a project sponsored by The Health Foundation entitled “The Future of Healthcare: Computerisation, Automation, and General Practice Services.” The project seeks to understand the impact of automation in the NHS and how automation can support the provision of healthcare within the NHS.

His intellectual foundation and research approach are informed by the disciplines of Social Informatics, Computer Supported Cooperative Work, Human-Computer Interaction, Sociotechnical Systems, Health Communication, and Social Shaping of Technology. His interests are in the design, use, and consequences of current and emerging technology in healthcare, from personal health records to artificial intelligence and blockchain. As a researcher, Matt values interdisciplinary collaboration and multi-methodological quantitative and qualitative approaches to both data collection and analysis.

Research interests

sociotechnical systems in healthcare, computer supported cooperative work, digital assemblages, human-computer interaction, digital research methods

Positions held at the OII

  • Research Associate, October 2019-
  • Researcher, June 2016 – September 2019

Research

Past projects

  • The Future of Healthcare: Computerisation and Automation, and General Practice Services

    Participants: Professor Eric T. Meyer, Dr Michael A. Osborne, Dr Angela Coulter, Dr Matt Willis, Dr Paul Duckworth

    The Future of Healthcare: Computerisation, Automation, and General Practice Services project is a collaboration between the Oxford Internet Institute, the Oxford Department of Engineering Science, and the Oxford Martin School, at the University of Oxford.

Chapters

Conference papers

  • WILLIS, M. and Jarrahi, M.H. (2019) "Automating Documentation: A critical perspective into the role of artificial intelligence in clinical documentation.", Lecture Notes in Computer ScienceLecture Notes in Computer Science. iConference. Springer Verlag. 11420 LNCS 200-209.
  • Willis, M. and Meyer, E.T. (2018) "Work that Enables Care: Understanding Tasks, Automation, and the National Health Service", Lecture Notes in Computer ScienceLecture Notes in Computer Science. iConference. Springer Verlag. 10766 LNCS 544-549.
  • Sharma, S., Willis, M., Snyder, J., Osterlund, C. and Sawyer, S. (2015) "Using an Ethnography of Email to Understand Distributed Scientic Collaborations", Proceedings of the 2015 iConference. Illinois Digital Environment for Access to Learning and Scholarship.
  • Willis, M., Sharma, S., Snyder, J., Brown, M., Østerlund, C. and Sawyer, S. (2014) "Documents and distributed scientific collaboration", Proceedings of the companion publication of the 17th ACM conference on Computer supported cooperative work & social computing - CSCW Companion '14. the companion publication of the 17th ACM conference, 15 – 19 February 2014. ACM Press. 257-260.
  • Raybourn, E., Fabian, N., Tucker, E. and WILLIS, M. (2010) "Beyond game effectiveness part II : A qualitative study of multi-role experiential learning.", I/ITSEC 2010 Proceedings. Interservice/ Industry Training, Simulation and Education Conference. National Defense Industrial Association. 1-11.
  • Willis, M. and Raybourn, E.M. (2009) "Leveraging Mobile Devices to Develop Intercultural Competency for Digital Students", Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Berlin Heidelberg. 5621 LNCS 545-553.

Journal articles

Reports

Teaching

  • Qualitative Data Analysis

    This course is designed to provide students with the knowledge and skills to carry out qualitative data analysis of a variety of kinds of data (e.g. text, photos, videos) collected from both online and offline settings.

Blog