Role
Thomas Johnson is a Lecturer in the Department of Computer Science within the School of Science and Technology. In this role he splits his time between teaching as a lecturer and also working towards completing his PhD in Pervasive Computing and Data Science.
Thomas is involved in teaching the following modules:
- Degree Apprenticeship:
- Mobile Platform Applications (Module Leader)
- Database Eng & Internet Application Programming
- Level 6
- Mobile Platform Applications (Module Leader)
- Mobile Platform Development
He also supervises project work of Level 6 BSc and MSc Level 7 students.
Career overview
Thomas was awarded a BSc. (Hons) Information and Communications Technology in 2016 and a MSc Computing Systems in 2017 both from Nottingham Trent University. He went on to be awarded in 2018 a PGCE in Primary Education within the Wider Curriculum with Qualified Teaching Status (QTS) from the University of Derby.
Tom joined Nottingham Trent University in September 2019 as an Academic Associate and was elevated to Lecturer in 2022 in the Department of Computer Science.
More information about Tom's research are available from his Linkedin, Twitter (@tomwjohnson) and ResearchGate
Research areas
PhD project title: Multimodel Sensor Fusion Approach to study the impact of Environment on Wellbeing.
Director of Studies: Professor. Eiman Kanjo
2nd Supervisor: Professor. Saeid Sanei
Thomas is part of the Smart Sensing Lab team. His research focuses on how stressors within the environment (such as: particulates, noise, gases) can have an impact towards mental wellbeing.
External activity
STEM for Britain. Selected as a finalist in the competition held at Houses of Parliament - Engineering category. (March 2023)
Invited talk at Clean Air Research Futures Group (CARFG): "Making it personal - will small / portable sensors transform air pollution management and research?” (October 2021)
IEEE International Smart Cities Conference: Sensor Fusion and The City: Visualisation and Aggregation of Environmental & Wellbeing Data (September 2021).
Publications
A full list of publications can be found at: https://www.researchgate.net/profile/Thomas-Johnson-43
- Johnson, T., Kanjo, E. & Woodward, K. DigitalExposome: quantifying impact of urban environment on wellbeing using sensor fusion and deep learning. Computational Urban Science. 3, 14 (2023). https://doi.org/10.1007/s43762-023-00088-9
- Johnson T., Kanjo E,. (2023) Episodes of Change: Emotion Change in Semantic Trajectories of Multimodal Sensor Data. The 21st International Conference on Pervasive Computing and Communications (PerCom 2023: EmotionAware Workshop).
- Johnson T., Kanjo E. (2023) Designing an Interactive Mobile Assessment Tool to Quantify Impact of the Environment on Wellbeing. Proceedings of the 2023 HCII Conference.
- Johnson T., Kanjo E. (2021) Sensor Fusion and The City: Visualisation and Aggregation of Environmental & Wellbeing Data. Proceedings of the 2021 IEEE International Smart Cities Conference.
- Woodward, K., Kanjo, E., Anderez, D. O., Anwar, A., Johnson, T., & Hunt, J. (2020). DigitalPPE: Low cost wearable that acts as a social distancing reminder and contact tracer: Poster abstract. SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems. https://doi.org/10.1145/3384419.3430600
- Johnson T, Kanjo E, Woodward, K. (2020) Sensor Data and the City: Urban Visualisation and Aggregation of Well-Being Data. (Preprint)
Magazines:
Johnson T., Kanjo E., & Woodward, K. (2021) Real-time Environmental Changes Impacts Mental Wellbeing. (Published February 2021)