Amy Ingold
Education and qualifications
PhD in Soft Robotics, University of Bristol (Oct 2020 – Sept 2024)
Title: From Functional to Fun: Social and Affective Soft Robotics
Supervisors: Professor Jonathan Rossiter and Professor Helen Manchester
After completing a foundational taught year on the EPSRC funded CDT in Digital Health & Care Program, my research was conducted from Bristol Robotics Laboratory within the Soft Robotics Group.
MSc Neuroscience, University College London (UCL) (Sep 2015 – Oct 2016)
Project conducted within Neuroinflammation Group, furthering understanding of mitochondrial trafficking dynamics across dorsal root network.
BSc (1st Class Hons) Psychology, Goldsmiths, University of London (Sep 2011 – Jun 2014)
Research employment
Postdoctoral Research Associate, University of Bristol (Sep 2024 – present)
Lead co-design research on inclusive social-play technologies for blind and visually-impaired preschoolers and their sighted peers. Contributions include project design, ethics, co-design with families and educators, and development of novel play artefacts.
Research Assistant, University of Bristol (Jul 2021 – Jul 2022)
Improved a therapeutic soft-robotic device through machine learning on an EPSRC-IAA–Brigstow project. Contributed to proposal development, enhanced personalisation and usability, led sensor integration and portability, and ran user testing. Developed intelligent sensing for adaptive behaviour and supervised an MSc student during data collection.
STEM Outreach Lead, Industrial Liaisons Office (University of Bristol) (May 2022 – Jul 2022)
Team leader for workshops introducing coding skills to autistic children at Venturers Academy. Trained team members in technical and soft skills, and acted as lead facilitator during sessions.
Publications
Journals (in final review)
Ingold, A., Lee, L. Y., Diteesawat, R. S., Roshan, A., Zekaria, Y., Hall, E-C., Werner, E., Rahman, N., Czech, E., & Rossiter, J. M. 2025. Soft Robotic Technological Probe for Speculative Fashion Futures. ACM Transactions on Human-Robot Interaction (THRI).
Conference proceedings (in final review)
Fan, Z., Li, M. S., Deng, J., Ingold, A., and Metatla, O. 2026. triMorph: Bridging Shape-Change and Cross-Sensory Correspondences for Haptic Interaction. In Proceedings of CHI Conference on Human Factors in Computing Systems (CHI ’26). ACM, New York, NY, USA, 49 pages. In review.
Li, M. S., Fan, Z., Roberts-Morgan, T., Ingold, A., & Metatla, O. 2026. Rough Meanings: Cross-Sensory Correspondences Linking Surface Textures with Sound Symbolism, Colours, and Emotions. I In Proceedings of CHI Conference on Human Factors in Computing Systems (CHI ’26). ACM, New York, NY, USA, 34 pages.
Czech, E., Bennett, D., Stangroome, G., Hanschke, V. A., Ingold, A., Marshall, P., & Metatla, O. 2026. Let’s Make a Community [of Practice]: Using Community-Based Participatory Design to Support Interdependence. In Proceedings of CHI Conference on Human Factors in Computing Systems (CHI ’26). ACM, New York, NY, USA, 33 pages.
Conference proceedings (accepted)
Roberts-Morgan, T., Morris, B., Li, M. S., Deng, J., Ingold, A., Fan, Z., et al. 2025. “Blue tastes like salt. It just does”: Exploring generational differences in the construction of cross-sensory metaphors. In Proceedings of the 24th Interaction Design and Children (IDC ’25). ACM. DOI:10.1145/3713043.3727060
Extended abstracts (accepted)
Ingold, A., Cauchard, J. R., Thomas, L. M., Balaam, M., Weir, E., Roudaut, A., Haynes, A. C., Winters, A., and Fan, Z. 2026. Everything Is a Robot (and Nothing Is). In Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems (CHI EA ’26), April 13–17, 2026, Barcelona, Spain. ACM, New York, NY, USA, 5 pages. https://doi.org/10.1145/3772363.3778719
Grants, awards and honours
Green Apple Scheme Grant (Awarded Nov 2025)
For delivery of educational PhD level workshop on sustainable materials for rapid prototyping.
1st Place in the Functional Fashion Competition (Awarded Oct 2023)
IEEE/RSJ International Conference on Intelligent Robots and Systems.
Enterprising Women 3.0 (Feb 2023 – Jul 2023)
NatWest-funded pre-incubation programme for entrepreneurial women, providing expert-led business training, mentoring, and networking opportunities.
Invited talks, panels and posters
Panel guest Seminar Theme: Changing Colours, Bristol Vision Institute (Nov 2025)
Speaker Dorkbot, Pervasive Media Studios (Oct 2025)
Title: Forage to Fabricate: Slow Materials for Rapid Prototyping
Poster Social Connection Workshops, ETH Zurich (Sep 2025)
Speaker Dorkbot, Pervasive Media Studios (Jul 2024)
Title: Throwing Shapes with the Sumbrella (Building a Soft-Robotic Hat)
Teaching and mentoring
Teaching University of Bristol (Nov 2025 – Apr 2026)
Course design and delivery in Environment and Wellbeing, on Contemporary Issues in Psychology, for 3rd year undergraduates.
Mentor University of Bristol (Sep 2021 – present)
Advisor for PhD and MSc students in engineering and HCI, providing guidance on co-design methods, soft-robotic fabrication, and user study design.
Alumni Panel Member CDT Digital Health & Care (Jun 2025)
Offered information and support on PhD progression, viva preparation, and career pathways.
Invited Academic Mentor Southwest UK Pre-CHI (Apr 2025)
One of two academic mentors offering guidance to students in the robotics stream Doctoral Consortium event.
Professional experience
Peer reviewer (2025 – present)
CHI Conference on Human Factors in Computing Systems (CHI), Designing Interactive Systems (DIS), and Interaction Design and Children (IDC).
Collaborator (Apr 2025 – Aug 2025)
Project, C2CSI: Co-imagining robots for enhancing child-to-child social interactions.
Demonstrator, Public Engagement, Digital Health Week (7th – 15th Aug 2021)
Industry experience
Associate Data Scientist, Hodge (Feb 2020 – Sep 2020)
Developed, compared, and optimised sales forecast and mortgage prediction models in the FinTech sector, using innovative modelling and scenario-based stress testing.
Graduate Data Scientist, Propel Finance (May 2019 – Jan 2020)
Improved sales forecasting models, integrated outputs into business intelligence pipelines using Tableau, and presented results to C-suite stakeholders.
Trainee Data Scientist, GoCompare (Oct 2018 – May 2019)
Handled and cleaned large datasets and developed exploratory scripts using Python (pandas, scikit-learn, seaborn).
Competencies
- Proficient: SPSS, SAS for statistical analysis, and NVivo for thematic analysis.
- Intermediate: Python and R programming languages, experienced in using Pandas, NumPy, and Regex for data manipulation, analysis, and preprocessing, and adept at data visualization with Matplotlib, Seaborn, and Tableau.
- Foundational: machine learning and scientific computing tools including Scikit-learn, TensorFlow, SciPy, and MATLAB. Text analysis using NLTK and app development with React Native. Core ability in electronics with Arduino (C/C++).