Team

Simone Stumpf

Simone is a Senior Lecturer at City, University of London and leads this project as Principal Investigator. She has been researching end-user interactions with machine learning systems for many years, and is very interested in the opportunities of AI for accessibility. Her recent research projects include activity detection for use by people with dementia and/or Parkinson’s disease, personal information management for people living with HIV, and investigating the intelligibility of a computer vision system for blind and partially sighted users. She teaches Inclusive Design as part of the MSc in Human-Computer Interaction Design.

Toby Harris

Toby is an creative technologist with a PhD in human interaction. At Queen Mary, University of London, he developed a series of live performance experiments to investigate performer–audience dynamics. One of which involved teaching a humanoid robot some stagecraft. His research aims to get us beyond screens and devices to technological infrastructures that support us in our world.

At City, he is responsible for ORBIT’s apps and services: “a good first step in getting AI to help the visually impaired is to give them a tool to tell us what’s important in their world”.

Lida Theodorou

Lida is a multidisciplinary researcher interested in the different ways we can use technology to measure human behaviour. Her research is focused on experience-centered design approaches in order to measure user engagement during social situations. She holds a PhD in human interaction from Queen Mary University of London where she focused on the collection and analysis of sensor and video data to detect audience engagement levels during live dance performances.
In this project she is responsible for conducting the user studies with visual impaired people and setting out the methodology with which to gather the data sets through an iPhone app.

Luisa Zintgraf

Luisa is a second year PhD student at the University of Oxford under the Microsoft Research Scholarship, co-supervised by Prof Shimon Whiteson (Oxford) and Katja Hofmann (Microsoft Research). The focus of her PhD is on meta-learning and reinforcement learning. For this project, she will be part of evaluating the dataset using state of the art few-shot learning methods and pushing forward the application of these for personalised object recognition.

Daniela Massiceti

Daniela recently completed her PhD in Machine Learning at the University of Oxford with Professor Philip Torr where her research drew together computer vision and NLP with application to interactive assistive tools for people with visual impairments. She will be joining MSR Cambridge as a postdoctoral researcher and focussing on machine learning with a human-in-the-loop as a way to personalise solutions for assistive and healthcare applications. She is specifically interested in models that can flexibly and quickly learn from small amounts of data provided by users in real-world scenarios. Her role on this project is as a machine learning researcher.

Ed Cutrell

Ed Cutrell is a Senior Principal Researcher at Microsoft Research where he explores computing for disability, accessibility, and inclusive design in theMSR Ability group. Over the years, he has worked on a broad range of HCI topics, including input tech, visual perception and graphics, intelligent notifications and disruptions, interfaces for search and personal information management, and technologies for people living in underserved communities in the global south. Ed has worked in the field of human-computer interaction (HCI) since 2000; he is trained in cognitive neuropsychology, with a PhD from the University of Oregon. He is advising on this project about AI approaches for accessibility.