Contact details
Address
Northampton Square
London EC1V 0HB
United Kingdom
About
Overview
Monica Visani Scozzi has recently joined HCID as a PhD student.
Her research focuses on how to support users interacting with conversational Generative AIs, minimising potential harms and maximising benefits. Monica has previously worked in the IT industry implementing and deploying solutions, with a passion for data and information, helping others get the most out of systems.
She has experience in conducting observational studies, understanding user needs and behaviours and how those relate to their motivation.
Monica's PhD investigates User experience with Generative AI. After becoming public, Generative AIs have gone through a phase of hype and high expectations. To size at best the opportunities that these powerful tools offer, research is needed to investigate and clarify how best users can be supported to get the most out of them. In the initial phase of her PhD research, Monica will look at researchers' use of Generative AIs. In her first study, she will be conducting naturalistic observations, using Thematic Analysis to identify themes in researchers' interactions.
Qualifications
- Ingegnere Gestionale, Politecnico di Milano, Italy
- MSc Human Computer Interaction, University College London, United Kingdom
Employment
- Student Research, City, University of London, Jul 2024 – present
- Senior Product Manager, Matillion, Jan 2022 – May 2023
- Senior Business Analyst, BBC Studios, Apr 2016 – Dec 2021
- Senior Business Analyst and Team Lead, BBC, Jun 2012 – Apr 2016
- IT Business Analyst, B2B Integration, Shell, Sep 2011 – May 2012
Languages
English (can read, write, speak, understand spoken and peer review) and Italian (can read, write, speak, understand spoken and peer review).
Research
1st supervisor
- Dr Stephann Makri, Senior Lecturer
2nd supervisor
- Dr Pranava Madhyastha, Senior Lecturer
Publications
Publications by category
Conference paper/proceedings
- Visani Scozzi, M., Iacovides, I. and Linehan, C. (2017). A Mixed Method Approach for Evaluating and Improving the Design of Learning in Puzzle Games. CHI PLAY '17: The annual symposium on Computer-Human Interaction in Play. doi:10.1145/3116595.3116628