This is the personal website of Mark Dimond. Hello!
I'm a Principal Consultant at Integrated Transport Planning Ltd, where I get to work on all sorts of exciting transport data science and research. Lots of the recent stuff looks at trying to exploit OpenStreetMap topology for better modelling of transit and infrastructure services. I am formerly the Associate in a two-year Knowledge Transfer Partnership between ITP and the University of Nottingham. The partnership looked at a wide range of transport problems, from disability access information to travel time modelling.
My research interests are mostly in geographic data mining and machine learning, and particularly the application of data mining to human geography problems.
My doctoral thesis, successfully defended in 2014, attempted to improve pedestrian GPS-based route prediction by investigating one of its main preprocessing components, the extraction of discrete journeys from longer GPS position histories. It investigated the notion that a common user-held concept of a journey is what prediction algorithms typically try to reproduce, and hence that better approximation of these could improve route prediction..
I undertook my doctorate as one of the first candidates at the Horizon Centre for Doctoral Training (CDT). Taught work and project work whilst at the CDT allowed me to develop technical skills in statistics, mathematics and geographic applications development. Before coming to Nottingham I worked with public sector GIS and database systems in a number of different roles. My first degree is in Human Geography and Computer Science from the University of Keele (2006).
D. Golightly, M. Dimond, N. Hughes, S. Sharples and E. Taylor, 2018. Promoting walking and cycling through a dashboard interface; in proc. of Association of Geospatial Labs Europe ('AGILE') 2018, Lund, Sweden.
M. Dimond, D. Brenig-Jones, and N. Taylor, 2017. Exploiting OpenStreetMap topology to aggregate and visualise public transport demand; in proc. of GIS Research UK ('GISRUK') 2017, Manchester.
M. Dimond, N. Taylor, and R. Houghton, 2016. Estimating and Editing Transit Topology over the road graph using supply data feeds; in proc. of Assoc. of Geospatial Information Laboratories Europe (AGILE) 2016, Helsinki.
M. Dimond, G. Smith and J. Goulding, 2013. Improving Route Prediction through User Journey Detection; in proc. of ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Orlando.
M. Dimond, G. Smith and J. Goulding, 2012. Evaluating Extraction Functions for Detection of Users’ Journeys; in proc. of Springer Symposium on Location-Based Services 2012, Munich.
M. Dimond, G. Smith, J. Goulding, M. Jackson and X. Meng, 2012. Comparing predefined and learned trajectory partitioning with applications to pedestrian route prediction; in proc. of GISRUK 2012, 20th annual GIS Research UK, Lancaster.