Book

Cheng, T., Bowers, K., Longley, P., Shawe-Taylor, J., Trevor, A., Davies, T., ...Shen, J. (2016). CPC: Crime, Policing and Citizenship - Intelligent Policing and Big Data. UCL SpaceTimeLab: UCL.
Ivan, I., Benenson, I., Jiang, B., Haworth, J., Horak, J., Inspektor, T. (Eds.), (2015). Geoinformatics for Intelligent Transportation. Switzerland: Springer International Publishing.
Cheng, T., Longley, P., Ellul, C., Chow, A.H.F. (Eds.), (2011). Proceedings of the 11th International Conference of GeoComputation, July 20-22. London, UK: University College London.
Cheng, T., Longley, P., Ellul, C., Chow, A.H.F. (Eds.), (2011). Proceedings of the International Symposium of Spatial-temporal Analysis and Data Mining (STDM 2011), July 18-19. London, UK: University College London.

Chapter

Cheng, T., Chen, T. (2021). Urban Crime and Security. In Urban Book Series. (pp. 213-228). .
Cheng, T., Shen, J. (2018). Grouping people in cities: from space-time to place-time based profiling. In Human Dynamics Research in Smart and Connected Communities. Cham: Springer.
Sari Aslam, N., Cheng, T. (2018). Smart Card Data and Human Mobility. In Longley, P., Cheshire, J., SINGLETON, A. (Eds.), Consumer Data Research. UK: UCL Press.
Cheng, T., Haworth, J., Anbaroglu, B., Tanaksaranond, G., Wang, J. (2013). Spatiotemporal Data Mining. In Fischer, M., Nijkamp, P. (Eds.), Handbook of Regional Science. (pp. 1173-1193). Springer.
Wang, J., CHENG, T., Haworth, J. (2012). Space-time kernels. In Shi, W., Goodchild, M., Lees, B. (Eds.), Advances in geospatial information science. Leiden, NL: CRC Press.
Wang, J., CHENG, T., Haworth, J. (2012). Space-time kernels. In Shi, W., Goodchild, M., Lees, B. (Eds.), Advances in geospatial information science. Leiden, NL: CRC Press.
Skarlatidou, A., Wardlaw, J., Haklay, M., CHENG, T. (2011). Advances in Cartography and GIScience. Volume 1. In Ruas, A. (Ed.), Advances in Cartography and GIScience. Volume 1. (pp. 219-238). Berlin: Springer-Verlag.
Skarlatidou, A., Wardlaw, J., Haklay, M., CHENG, T. (2011). Understanding the influence of specific Web GIS attributes in the formation of non-experts' trust perceptions. In Ruas, A. (Ed.), Advances in cartography and GIScience. (pp. 219-238). Berlin: Springer-Verlag.
Skarlatidou, A., Wardlaw, J., Haklay, M., Cheng, T. (2011). Understanding the Influence of specific Web GIS Attributes in the formation of Non-Experts’ Trust Perceptions. In Advances in Cartography and GIScience; Volume 1; Selection from ICC 2011, Paris. (pp. 219-238). Springer.
CHENG, T., Anbaroglu, B. (2010). Spatio-Temporal Clustering of Road Network Data. In Wang, F.L., Deng, H., Gao, Y., Lei, J. (Eds.), Artificial Intelligence and Computational Intelligence Part I. (pp. 116-223). Belin: Springer.
CHENG, T., Anbaroglu, B. (2010). Spatio-temporal clustering of road network data. In Deng, H., Wang, L., Wang, F.L., Lei, J. (Eds.), Artificial Intelligence and Computational Intelligence. (pp. 116-123). New York: Springer-Verlag New York Inc.
Cheng, T., Li, Z., Gong, J. (2008). An activity-based spatio-temporal data model for epidemic transmission analysis. In Tang, X., Liu, Y., Zhang, J., Kainz, W. (Eds.), Advances in Spatio-Temporal Analysis. (pp. 135-146). Taylor & Francis.
Cheng, T., Molenaar, M., Stein, A. (2008). Fuzzy approach for integrated coastal zone management. In Yang, X. (Ed.), Remote Sensing and GIS for Coastal Ecosystem Assessment and Management: Principles and Application. (pp. 67-90). Berlin, Germany: Springer-Verlag.
CHENG, T., Wang, J., Li, X. (2008). Space-time series forecasting by artificial neural networks. In Li, D., Gong, J., Wu, H. (Eds.), International Conference on Earth Observation Data Processing and Analysis (ICEODPA) (Proceedings Volume). Society of Photo Optical.
CHENG, T., Wang, J. (2007). Application of a dynamic recurrent neural network in spatio-temporal forecasting. In Popovich, V.V., Schrenk, M., Korolenko, K.V. (Eds.), Information fusion and geographic information systems. (pp. 173-186). Berlin: Springer Verlag.
CHENG, T., Li, Z., Li, D., Li, D. (2006). An integrated cloud model for measurement errors and fuzziness. In Riedl, A., Kainz, W., Elmes, G.A. (Eds.), Progress in Spatial Data Handling. (pp. 699-718). Springer Verlag.
CHENG, T., Fisher, P., Li, Z. (2005). Double vagueness: effect of scale on the modelling of fuzzy spatial objects. In Fisher, P.F. (Ed.), Developments in spatial data handling. (pp. 299-313). Springer-Verlag New York Inc.
Fisher, P., Wood, J., Cheng, T. (2005). Fuzziness and ambiguity in multi-scale analysis of landscape morphometry. In Cobb, M., Petry, F., Robinson, V. (Eds.), Fuzzy Modeling with Spatial Information for Geographic Problems. (pp. 209-232). New York: Springer.
Cheng, T. (2005). Modelling and visualising linear and cyclic Changes. In Fisher, P., Unwin, D. (Eds.), Re-Presenting GIS. (pp. 205-213). John Wiley & Son.
Raper, J., Miller, H., Guhathakurta, S., Muetzelfeldt, R., Cheng, T. (2005). Time as well: an introduction. In Fisher, P., Unwin, D. (Eds.), Re-Presenting GIS. (pp. 195-198). John Wiley & Sons.
CHENG, T., Molenaar, M., Bouloucos, T. (1997). Identification of fuzzy objects from field observation data. In Hirtle, S.C., Frank, A.U. (Eds.), Spatial information theory. (pp. 241-259). Springer Verlag.
Cheng, T., Haworth, J., Anbaroglu, B., Tanaksaranond, G., Wang, J. (1900). Spatio-Temporal Data Mining. In .
Cheng, T., Haworth, J., Anbaroglu, B., Tanaksaranond, G., Wang, J. (1900). Spatio-Temporal Data Mining. In .

Conference abstract/presentation slides

Cheung, Y., Cheng, T. (2019). Forecasting Ridership to Plan New Public Transport by Using Smartphone Data.
Wang, J., CHENG, T. (2012). A local measure of spatial-temporal autocorrelation in traffic road network.
CHENG, T., Williams, D. (2012). Space-time patterns of crime incidents in Central London.
Tsapakis, I., CHENG, T., Bolbol, A. (2011). Effect of adverse weather conditions on urban speeds and travel time reliability of bus lane and non-bus lane users.
Bolbol, A., CHENG, T., Tsapakis, I., Skarlatidou, A. (2011). Identifying intermediary modes from GPS data.
CHENG, T. (2011). Integrated spatio-temporal analysis of road network performance.
Manley, E., CHENG, T. (2011). Modelling the impact of unexpected interruptions on road network performance using agent-based simulation.
CHENG, T., Manley, E. (2011). Network complexity: space-time dynamics and tipping points.
Haworth, J., CHENG, T. (2011). Spatio-temporal autocorrelations of networks and their implications for space-time modelling.
CHENG, T., Anbaroglu, B., Manley, E. (2011). Spatio-temporal scan statistics to analyse network emergence.
Skarlatidou, A., Haklay, M., CHENG, T. (2010). Cognitive walkthrough and heuristic evaluation for Web GIS usability and trust implications.
CHENG, T. (2010). Online spatio-temporal analysis of network data and road developments.
CHENG, T., Haworth, J. (2010). Space-time Kernels.
CHENG, T., Wang, J. (2010). STARIMA for journey time prediction in London.
CHENG, T., Wang, J. (2009). A hybrid model for space-time analysis.
CHENG, T., Wang, J. (2008). Integrated space-time series analysis for environmental data.
CHENG, T., Wang, J. (2007). Using dynamic recurrent neural networks for integrated spatio-temporal forecasting.
CHENG, T. (2004). Uncertainties of Spatial Objects: concepts, models and applications.
CHENG, T., Fisher, P., Li, Z. (2003). Effects of scale on modelling of fuzzy spatial objects.
CHENG, T., Fisher, P. (2002). Double Fuzziness: Fuzziness in Fuzzy Assignment of Duneness.
CHENG, T., Fisher, P., Rogers, P. (2002). Fuzziness in Multi-scale Fuzzy Assignment of Duneness.

Conference paper (text)

Kim, T.E., Lipani, A. (2022). A Multi-Task Based Neural Model to Simulate Users in Goal-Oriented Dialogue Systems.
Shi, Z., Ni, P., Wang, M., Kim, T.E., Lipani, A. (2022). Attention-based Ingredient Phrase Parser.
Feng, Y., Lipani, A., Ye, F., Zhang, Q., Yilmaz, E. (2022). Dynamic Schema Graph Fusion Network for Multi-Domain Dialogue State Tracking.
Ni, P., Yuan, Q., Khraishi, R., Okhrati, R., Lipani, A., Medda, F. (2022). Eigenvector-based Graph Neural Network Embeddings and Trust Rating Prediction in Bitcoin Networks.
Fu, X., Yilmaz, E., Lipani, A. (2022). Evaluating the Cranfield Paradigm for Conversational Search Systems.
Shi, Z., Feng, Y., Lipani, A. (2022). Learning to Execute Actions or Ask Clarification Questions.
Shi, Z., Zhang, Q., Lipani, A. (2022). StepGame: A New Benchmark for Robust Multi-Hop Spatial Reasoning in Texts.
Mungmeeprued, T., Ma, Y., Mehta, N., Lipani, A. (2022). Tab this Folder of Documents: Page Stream Segmentation of Business Documents.
Izzo, C., Lipani, A., Okhrati, R., Medda, F. (2021). A Baseline for Shapley Values in MLPs: from Missingness to Neutrality.
Okhrati, R., Lipani, A. (2021). A Multilinear Sampling Algorithm to Estimate Shapley Values.
Shelbourne, C., Linguaglossa, L., Zhang, T., Lipani, A. (2021). Inference of virtual network functions' state via analysis of the CPU behavior.
Zhang, Q., Lipani, A., Yilmaz, E. (2021). Learning Neural Point Processes with Latent Graphs.
Hofstatter, S., Lipani, A., Althammer, S., Zlabinger, M., Hanbury, A. (2021). Mitigating the Position Bias of Transformer Models in Passage Re-Ranking.
Radmard, P., Fathullah, Y., Lipani, A. (2021). Subsequence Based Deep Active Learning for Named Entity Recognition.
Sanchez, L., He, J., Manotumruksa, J., Albakour, D., Martinez, M., Lipani, A. (2020). Easing Legal News Monitoring with Learning to Rank and BERT.
Chen, T., Cheng, T. (2020). Identifying Optimal Scales for Spatio-temporal Crime Clusters.
Zhang, Y., Sari Aslam, N., Cheng, T. (2020). Inferring Demographics from Spatial-Temporal Activities Using Smart Card Data.
Hofstätter, S., Lipani, A., Zlabinger, M., Hanbury, A. (2020). Learning to Re-Rank with Contextualized Stopwords.
Bulathwela, S., Pérez-Ortiz, M., Lipani, A., Yilmaz, E., Shawe-Taylor, J. (2020). Predicting Engagement in Video Lectures.
Zhang, Q., Lipani, A., Kirnap, Ö., Yilmaz, E. (2020). Self-Attentive Hawkes Processes..
ZHANG, Y., Cheng, T., Sari Aslam, N. (2019). Deep Learning for Demographic Prediction based on Smart Card Data and Household Survey.
Cheng, T., Chen, T., Zhang, Y. (2019). Exploring the Homogeneity of Offenders in Crime Hotspots.
Zhang, Y., Cheng, T., Sari Aslam, N. (2019). Exploring the relationship between travel pattern and social-demographics using smart card data and household survey.
Lipani, A., Carterette, B., Yilmaz, E. (2019). From a User Model for Query Sessions to Session Rank Biased Precision (sRBP).
Zhang, Q., Liang, S., Lipani, A., Ren, Z., Yilmaz, E. (2019). From Stances’ Imbalance to their Hierarchical Representation and Detection.
Zhu, D., Cheng, T., Liu, Y. (2019). Geo-propagation from Incomplete Spatial Distribution Data: A Case Study of House Price Estimation.
Chen, H., Cheng, T., Zhang, Y. (2019). Locating stations in bike-sharing service: a special maximal covering location problem.
Shelbourne, C., Linguaglossa, L., Lipani, A., Zhang, T., Geyer, F. (2019). On the Learnability of Software Router Performance via CPU Measurements.
Zhang, Q., Lipani, A., Liang, S., Yilmaz, E. (2019). Reply-Aided Detection of Misinformation via Bayesian Deep Learning.
Sari Aslam, N., Cheng, T., Cheshire, J., Zhang, Y. (2019). Trip purpose identification using pairwise constraints based semi-supervised clustering.
Sari Aslam, N., Cheng, T., Cheshire, J., ZHANG, Y. (2019). Trip purpose identification using pairwise constraints based semi-supervised clustering.
Sari Aslam, N., Cheng, T., Cheshire, J., Zhang, Y. (2019). Trip purpose identification using pairwise constraints based semi-supervised clustering.
Sari Aslam, N., Cheng, T., Cheshire, J.A. (2018). Behavioural Analysis of Smart Card Data.
Zhang, Y., Cheng, T. (2018). Inferring Social-Demographics of Travellers based on Smart Card Data.
Liu, Y., Cheng, T. (2017). Characterising Passengers’ Travel Patterns in London Public Transit.
Lipani, A., Lupu, M., Palotti, J., Zuccon, G., Hanbury, A. (2017). Fixed Budget Pooling Strategies Based on Fusion Methods.
Lipani, A., Palotti, J., Lupu, M., Piroi, F., Zuccon, G., Hanbury, A. (2017). Fixed-Cost Pooling Strategies Based on IR Evaluation Measures.
Bantis, T., Haworth, J., Holloway, C., Twigg, J. (2017). Mapping spatiotemporal patterns of disabled people: The case of the St. Jude’s storm emergency.
Lipani, A., Lupu, M., Hanbury, A. (2017). Visual Pool: A Tool to Visualize and Interact with the Pooling Method.
Lipani, A. (2016). Fairness in Information Retrieval.
Shi, Y., Taalab, K., Cheng, T. (2016). Flood Prediction Using Support Vector Machines (SVM).
Anbaroglu, B., Heydecker, B., Cheng, T. (2016). How travel demand affects detection of non-recurrent traffic congestion on urban road networks.
Haworth, J. (2016). INVESTIGATING THE POTENTIAL OF ACTIVITY TRACKING APP DATA TO ESTIMATE CYCLE FLOWS IN URBAN AREAS.
Williams, D., Haworth, J., Cheng, T. (2016). Predicting public confidence in the police with spatiotemporal Bayesian hierarchical modelling..
Williams, D., Haworth, J., Cheng, T. (2016). Predicting public confidence in the police with spatiotemporal Bayesian hierarchical modelling..
Lipani, A., Lupu, M., Hanbury, A. (2016). The Curious Incidence of Bias Corrections in the Pool.
Lipani, A., Zuccon, G., Lupu, M., Koopman, B., Hanbury, A. (2016). The Impact of Fixed-Cost Pooling Strategies on Test Collection Bias.
Lipani, A., Lupu, M., Kanoulas, E., Hanbury, A. (2016). The Solitude of Relevant Documents in the Pool.
Wise, S., Cheng, T. (2015). A Model Officer: An Agent-based Model of Policing.
Adepejue, M., Cheng, T., Rosser, G. (2015). A new metric of crime hotspots for operational Policing.
Rosser, G., Cheng, T. (2015). A self-exciting point process model for predictive policing: implementation and evaluation.
Lipani, A., Lupu, M., Aizawa, A., Hanbury, A. (2015). An Initial Analytical Exploration of Retrievability.
shen, J., Cheng, T. (2015). Clustering Analysis of Officer's Behaviours in London Police Foot Patrol Activities.
Piroi, F., Lipani, A., Lupu, M., Hanbury, A. (2015). DASyR(IR) - document analysis system for systematic reviews (in Information Retrieval).
Chen, H., Cheng, T., Wise, S. (2015). Designing Daily Patrol Routes For Policing Based On Ant Colony Algorithm.
Williams, D., Haworth, J., Cheng, T. (2015). Exploratory spatiotemporal data analysis and modelling of public confidence in the police in central London.
Williams, D., Haworth, J., Cheng, T. (2015). Exploratory spatiotemporal data analysis and modelling of public confidence in the police in central London.
Shen, J., Cheng, T. (2015). Group Behaviour Analysis of London Foot Patrol Police.
Bantis, A., Haworth, J., Holloway, C., Twigg, J. (2015). Mapping Spatio-Temporal Patterns of Disabled People in emergencies: A Bayesian approach.
Juntao, L., Cheng, T., Lansley, G. (2015). Spatio-Temporal Patterns of Passengers’ Interests at London Tube Stations.
Lipani, A., Lupu, M., Hanbury, A. (2015). Splitting Water: Precision and Anti-Precision to Reduce Pool Bias.
Lipani, A., Lupu, M., Hanbury, A., Aizawa, A. (2015). Verboseness Fission for BM25 Document Length Normalization.
Haworth, J., Cheng, T. (2014). A COMPARISON OF NEIGHBOURHOOD SELECTION TECHNIQUES IN SPATIO-TEMPORAL FORECASTING MODELS.
Haworth, J., Cheng, T. (2014). A COMPARISON OF NEIGHBOURHOOD SELECTION TECHNIQUES IN SPATIO-TEMPORAL FORECASTING MODELS.
Lipani, A., Piroi, F., Andersson, L., Hanbury, A. (2014). An Information Retrieval Ontology for Information Retrieval Nanopublications.
Lipani, A., Piroi, F., Andersson, L., Hanbury, A. (2014). Extracting Nanopublications from IR Papers.
Lipani, A., Andersson, L., Piroi, F., Lupu, M., Hanbury, A. (2014). TUW-IMP at the NTCIR-11 Math-2.
Cheng, T., Adepejue, M. (2013). Detecting Emerging Space-Time Crime Patterns by Prospective STSS.
Sfyridis, A., Cheng, T., Vespe, M. (2013). Detecting vessels carrying migrants using machine learning.
Haworth, J., Cheng, T., Manley, E. (2013). Improving Forecasting under Missing Data on Sparse Spatial Networks.
Haworth, J., Cheng, T., Manley, E. (2013). Improving Forecasting under Missing Data on Sparse Spatial Networks.
Manley, E., Cheng, T., Haworth, J. (2013). Markov Chain Topological Route Selection.
Cheng, T., Manley, E., Haworth, J. (2013). Markov Chain Topological Route Selection.
Chen, C., Wang, Y., Wan, H., Cheng, T. (2012). Determinations of low breast screening uptake using geographically weighted regression model.
Tsapakis, I., Turner, J.T., CHENG, T., Heydecker, B., Emmonds, A.E., Bolbol, A.B. (2012). Effects of tube strikes on journey times in the transport network of London.
Bolbol, A., CHENG, T., Tsapakis, I. (2012). Inferring the travel mode from sparse GPS data using SVM classification: Case study of Greater London.
Chow, A.H.F., Santecreu, A., Tsapakis, I., Tanaksaranond, G., CHENG, T. (2012). Nature and causes of urban traffic congestion - a case study of London.
Cheng, T., Williams, D. (2012). SPACE-TIME ANALYSIS OF CRIME PATTERNS IN CENTRAL LONDON.
Tsapakis, I., Turner, J., Heydecker, B., CHENG, T. (2012). Understanding the effects of tube strikes on macroscopic and link travel times.
Chow, A.H.F., Heydecker, B.G., Cheng, T. (2012). Urban traffic data fusion.
Chow, A.H.F., Tsapakis, I., Tanaksaranond, G., Cheng, T., Heydecker, B., Emmonds, A. (2012). Urban traffic data fusion.
Tanaksaranond, G., CHENG, T., Chow, A. (2011). A star-schema OLAP to support multi-dimensional traffic analysis.
Chow, A.H.F., Santacreu, A., Tsapakis, I., Tanaksaranond, G., Cheng, T. (2011). Empirical analysis of urban traffic congestion – A case study of Greater London Area.
Skarlatidou, A., Haklay, M., Cheng, T., Bolbol, A. (2011). Investigating non-experts trust perceptions in Spatial Decision Support Systems for public use.
CHENG, T., Haworth, J., Shawe-Taylor, J. (2011). Kernel regression for traffic prediction under missing data.
CHENG, T., Wang, J., Haworth, J., Heydecker, B., Chow, A. (2011). Modelling dynamic space-time autocorrelations of urban transport network.
Manley, E., Cheng, T. (2011). Multi-Agent Simulation of Drivers Reactions to Unexpected Incidents on Urban Road Networks.
Manley, E., CHENG, T. (2011). Multi-agent simulation of drivers reactions to unexpected incidents on urban road networks.
Wang, J., CHENG, T., Heydecker, B., Chow, A. (2011). Parameter calibration of STARIMA model.
Cheng, T., Anbaroglu, B., Manley, E. (2011). Spatio-Temporal Scan Statistics to Analyse Network Emergence.
Manley, E., CHENG, T., Emmonds, A. (2011). Understanding route choice by using agent-based simulation.
CHENG, T., Skarlatidou, A., Wardlaw, J., Haklay, M. (2011). Understanding the influence of specific Web GIS attributes in the formation of non-experts’ trust perceptions.
Bolbol, A., CHENG, T., Haworth, J. (2011). Using a moving window SVM classification to infer travel mode from GPS data.
Bolbol, A., CHENG, T., Haworth, J. (2011). Using a moving window SVMs classification to infer travel mode from GPS data.
Anbaroglu, B., CHENG, T. (2011). Where and when does the traffic congestion begin and end? A spatio-temporal clustering approach to detect congestion.
Skarlatidou, A., Haklay, M., Cheng, T. (2010). Cognitive walkthrough and heuristic evaluation for Web GIS usability and trust implications.
Cheng, T., Anbaroglu, B. (2010). Defining dynamic spatiooral neighbourhood of network data.
CHENG, T., Anbaroglu, T. (2010). Defining spatio-temporal neighbourhood of network data.
Bolbol, A.S.Z., Cheng, T., Paracha, A. (2010). GEOTRAVELDIARY: Towards Online Automatic Travel Behaviour Detection.
Bolbol, A., CHENG, T. (2010). GPS data collection setting for pedestrian activity modelling.
Cao, Z., Haklay, M., Cheng, T. (2010). IDW implementation in Map calculus and commercial GIS products.
CHENG, T., Tanaksaranond, G., Emmonds, A., Sonoiki, D. (2010). Multi-scale visualisation of inbound and outbound traffic delays in London.
Bolbol, A., CHENG, T. (2010). On-line travel diary: towards automatic travel behaviour detection.
Skarlatidou, A., Cheng, T., Haklay, M. (2010). Preliminary investigation of Web GIS trust: the example of the “WIYBY” website.
Wang, J., CHENG, T., Haworth, J. (2010). Space-time kernels.
Wang, J., CHENG, T., Haworth, J. (2010). Space-time kernels.
CHENG, T. (2010). Spatio-temporal analysis of network data and road developments.
CHENG, T., Anbaroglu, B. (2010). Spatio-temporal clustering of road network data.
Wang, J., CHENG, T., Heydecker, B., Haworth, J. (2010). STARIMA for journey time prediction in London.
Skarlatidou, A., Haklay, M., Cheng, T., Francis, N. (2010). Trust in web GIS: A preliminary investigation of the environment agency’s WIYBY website with non-expert users.
Manley, E., Cheng, T. (2010). Understanding Road Congestion as an Emergent Property of Traffic Networks.
CHENG, T., Manley, E. (2010). Understanding road congestion as an emergent property of traffic networks.
Deng, M., Liu, Q., Li, G., Cheng, T. (2009). A local distribution based spatial clustering algorithm.
CHENG, T., Anbaroglu, B. (2009). Methods on defining spatio-temporal neighbourhoods.
CHENG, T., Anbaroglu, B. (2009). Spatio-temporal outlier detection in environmental data.
Cheng, T., Wang, J., Li X, Z., W. (2008). A hybrid approach to model nonstationary space-time series.
Cheng, T., Wang, J. (2008). Integrated space-time series analysis for environmental data.
Cheng, T., Wang, J., Li, X. (2008). Space-time series modelling by artificial neural network.
Cheng, T., Deng, M., Li, Z. (2007). A unified representation for indeterminate spatial objects.
Cheng, T., Wang, J. (2007). Application of a dynamic recurrent neural network in spatio-temporal forecasting.
Wang, J., Cheng, T. (2007). Nonlinear integration of spatial and temporal forecasting by Support Vector Machines.
Cheng, T., Wang, J., Li, X. (2007). Spatio-temporal data mining and forecasting by support vector machines.
Cheng, T., Wang, J. (2007). Using dynamic recurrent neural networks for integrated spatio-temporal forecasting.
Cheng, T., Li, Z.L., Li, D.A.L., D. (2006). An integrated cloud model for measurement errors and fuzziness.
Cheng, T., Wang, J. (2006). Applications of spatio-temporal data mining and knowledge discovery (STDMKD) for forest fire prevention.
Cheng, T., Wang, J. (2006). Applications of spatio-temporal data mining and knowledge for forest fire.
Liu, W., Chen, J., Zhao, R., Cheng, T. (2005). A refined line-line spatial relationship model for spatial conflict detection.
Cheng, T., Li, Z., Gong, J. (2005). Conceptual design of an activity-based spatio-temporal data model for SARS transmission analysis.
Liu, W., Chen, J., Li, Z., Zhao, R., Cheng, T. (2005). Detection of spatial conflicts between rivers and contours in topographical database updating.
Cheng, T., Li, Z. (2005). Representing cyclic change in polar coordinate systems.
Cheng, T., Li, Z., Deng, M., Xu, Z. (2005). Representing indeterminate spatial objects by cloud theory.
Fisher, P., Wood, J., Cheng, T. (2005). The uncertainty of uncertainty: higher order vagueness in geographical information.
Cheng, T., Li, Z. (2004). A hybrid approach to detect spatio-temporal outliers.
Cheng, T., Li, Z. (2004). A multi-scale approach to detect spatio-temporal outliers.
Cheng, T., Fisher, P., Li, Z. (2004). Double vagueness: effect of scale on the modelling of fuzzy spatial objects.
Cheng, T. (2004). Double Vaugeness: Effect of Scale on the Modeling of Fuzzy Spatial Objects.
Cheng, T. (2004). Uncertainties of Spatial Objects: concepts, models and applications.
Cheng, T., Fisher, P., Li, Z. (2003). Effects of Scale on Modeling of Fuzzy Spatial Objects.
Cheng, T., Li, Z. (2003). Measure the semantic change after merging operation.
Cheng, T., Fisher, P. (2002). Double Fuzziness: Fuzziness in Fuzzy Assignment of Duneness.
Cheng, T., Fisher, P., Rogers, P. (2002). Fuzziness in Multi-scale Fuzzy Assignment of Duneness.
Cheng, T. (2001). Quality assessment of model-oriented generalization.
Shan, Y., Cheng, T., and Lin, H. (2001). Spatio-temporal data mining in GIS.
Cheng, T., Wang, D. (2001). Visualizing cyclic spatio-temporal patterns in polar coordinate system.
Wang, D., Cheng, T. (2000). A process-oriented spatio-temporal data model for activity-based travel demand modeling.
Cheng, T., Lin, H. (2000). Uncertainties in multi-scale generalization.
Cheng, T., Molenaar, M. (1999). Syntactic representation of three fuzzy object models.
Cheng, T., Molenaar, M. (1998). A process-oriented spatio-temporal data model to support physical environmental modeling.
Cheng, T. (1998). Change of fuzzy objects.
Cheng, T., Molenaar, M., Bouloucos, T. (1998). Fuzzy object models and their application.
Molenaar, M., Cheng, T. (1998). Fuzzy spatial objects and their dynamics.
Cheng, T., Molenaar, M. (1998). The identification and monitoring of objects with fuzzy spatial extent.
Cheng, T., M.o.l.e.n.a.a.r. (1997). Dynamics of fuzzy objects.
Cheng, T., Molenaar, M., Bouloucos, T. (1997). Identification of fuzzy objects from field observation data.
Cheng, T., Kainz, W., Van Zuidam, R.A. (1996). Coupling GIS and environmental modelling: the implications for spatio-temporal data modeling.
Cheng, T., Van Zuidam, R.A., Kaniz, W. (1995). A unified spatio-temporal data model for 4-D GIS.
Cheng, T., Eleveld, M.A., Van Zuidam, R.A. (1995). Creation of a 4-D GIS working platform for coastal environmental monitoring and management.
Cheng, T. (1995). Development of a spatio-temporal GIS shell to support coastal environment modelling.
Eleveld, M.A., Cheng, T., Van Zuidam, R.A. (1995). Towards a decision support system for coastal zone management by applying morphodynamic modeling with remote sensing data input in a 4-D GIS environment.
Li, D., Cheng, T. (1994). KDG - Knowledge Discovery from GIS: propositions on the use of KDD in an Intelligent GIS.
Cheng, T., Li, D., Shu, N. (1992). An expert system of grass resource investigation by using remote sensing data.
Haworth, J., Cheng, T., Manley, E. (1900). Improving forecasting under missing data on sparse spatial networks.

Journal article

Olsen, F., Schillaci, C., Ibrahim, M., Lipani, A. (2022). Borough-level COVID-19 forecasting in London using deep learning techniques and a novel MSE-Moran’s I loss function. Results in Physics, 35 doi:10.1016/j.rinp.2022.105374
Luft, H., Schillaci, C., Ceccherini, G., Vieira, D., Lipani, A. (2022). Deep Learning Based Burnt Area Mapping Using Sentinel 1 for the Santa Cruz Mountains Lightning Complex (CZU) and Creek Fires 2020. Fire, 5 (5), doi:10.3390/fire5050163
Kizilcec, V., Spataru, C., Lipani, A., Parikh, P. (2022). Forecasting Solar Home System Customers’ Electricity Usage with a 3D Convolutional Neural Network to Improve Energy Access. Energies, 15 (3), doi:10.3390/en15030857
Liu, X., Chen, M., Claramunt, C., Batty, M., Kwan, M.-.P., Senousi, A.M., ...Wilson, J. (2022). Geographic information science in the era of geospatial big data: A cyberspace perspective. The Innovation, 3 (5), doi:10.1016/j.xinn.2022.100279
Cheng, T., Chen, T., Liu, Y., Aldridge, R.W., Nguyen, V., Hayward, A.C., Michie, S. (2022). Human mobility variations in response to restriction policies during the COVID-19 pandemic: An analysis from the Virus Watch community cohort in England, UK. Frontiers in Public Health, 10 doi:10.3389/fpubh.2022.999521
Franklin, R.S., Delmelle, E.C., Andris, C., Cheng, T., Dodge, S., Franklin, J., ...McLafferty, S. (2022). Making Space in Geographical Analysis. Geographical Analysis, doi:10.1111/gean.12325
Cheng, T., Liu, J., Liu, Y., Zhang, X., Gao, X. (2022). Measures to prevent nosocomial transmissions of COVID-19 based on interpersonal contact data. Primary Health Care Research & Development, 23 doi:10.1017/S1463423621000852
Cheng, T., Zhang, Y., Haworth, J. (2022). Network and graph-based SpaceTimeAI: conception, method and applications. Cehui Xuebao/Acta Geodaetica et Cartographica Sinica, 51 (7), 1629-1639. doi:10.11947/j.AGCS.2022.20220236
Cheng, T., Zhang, Y., Haworth, J. (2022). Network and graph-based SpaceTimeAI: conception, method and applications. Cehui Xuebao/Acta Geodaetica et Cartographica Sinica, 51 (7), 1629-1639. doi:10.11947/j.AGCS.2022.20220236
Navaratnam, A.M.D., Shrotri, M., Nguyen, V., Braithwaite, I., Beale, S., Byrne, T.E., ...Hoskins, S. (2022). Nucleocapsid and spike antibody responses post virologically confirmed SARS-CoV-2 infection: An observational analysis in the Virus Watch community cohort. International Journal of Infectious Diseases, doi:10.1016/j.ijid.2022.07.053
Beale, S., Patel, P., Rodger, A., Braithwaite, I., Byrne, T., Fong, W.L.E., ...Navaratnam, A. (2022). Occupation, work-related contact and SARS-CoV-2 anti-nucleocapsid serological status: findings from the Virus Watch prospective cohort study. Occupational and Environmental Medicine, doi:10.1136/oemed-2021-107920
Aguilera, Q., Lombardo, L., Tanyas, H., Lipani, A. (2022). On the prediction of landslide occurrences and sizes via Hierarchical Neural Networks. Stochastic Environmental Research and Risk Assessment,
Lyu, H., Shao, Z., Cheng, T., Yin, Y., Gao, X. (2022). Sea-Surface Object Detection Based on Electro-Optical Sensors: A Review. IEEE Intelligent Transportation Systems Magazine, 2-27. doi:10.1109/mits.2022.3198334
Panella, F., Lipani, A., Boehm, J. (2022). Semantic segmentation of cracks: Data challenges and architecture. Automation in Construction, 135 104110. doi:10.1016/j.autcon.2021.104110
Lu, Y., James, T., Schillaci, C., Lipani, A. (2022). Snow detection in alpine regions with Convolutional Neural Networks: discriminating snow from cold clouds and water body. GIScience & Remote Sensing, 59 (1), 1321-1343. doi:10.1080/15481603.2022.2112391
Chen, T., Bowers, K., Zhu, D., Gao, X., Cheng, T. (2022). Spatio-temporal stratified associations between urban human activities and crime patterns: a case study in San Francisco around the COVID-19 stay-at-home mandate. Computational Urban Science, 2 (1), doi:10.1007/s43762-022-00041-2
Zhu, R., Anselin, L., Batty, M., Kwan, M.-.P., Chen, M., Luo, W., ...Cheng, C. (2022). The effects of different travel modes and travel destinations on COVID-19 transmission in global cities. Science Bulletin, doi:10.1016/j.scib.2021.11.023
Zhang, X., Cheng, T. (2022). The impacts of the COVID-19 pandemic on multimodal human mobility in London: A perspective of decarbonizing transport. Geo-spatial Information Science, doi:10.1080/10095020.2022.2122876
Aslam, N.S., Ibrahim, M.R., Cheng, T., Chen, H., Zhang, Y. (2021). ActivityNET: Neural networks to predict public transport trip purposes from individual smart card data and POIs. Geo-spatial Information Science, doi:10.1080/10095020.2021.1985943
James, T., Schillaci, C., Lipani, A. (2021). Convolutional Neural Networks for Water segmentation using Sentinel-2 Red, Green, Blue (RGB) composites and derived Spectral Indices. International Journal of Remote Sensing (TRES), doi:10.1080/01431161.2021.1913298
Ibrahim, M., Haworth, J., Christie, N., Cheng, T., Hailes, S. (2021). Cycling near misses: A review of the current methods, challenges and the potential of an AI-embedded system. Transport Reviews, doi:10.1080/01441647.2020.1840456
Ibrahim, M., Haworth, J., Christie, N., Cheng, T., Hailes, S. (2021). Cycling near misses: A review of the current methods, challenges and the potential of an AI-embedded system. Transport Reviews, doi:10.1080/01441647.2020.1840456
Ibrahim, M.R., Haworth, J., Christie, N., Cheng, T. (2021). CyclingNet: Detecting cycling near misses from video streams in complex urban scenes with deep learning. IET Intelligent Transport Systems, doi:10.1049/itr2.12101
Ibrahim, M.R., Haworth, J., Christie, N., Cheng, T. (2021). CyclingNet: Detecting cycling near misses from video streams in complex urban scenes with deep learning. IET Intelligent Transport Systems, doi:10.1049/itr2.12101
Gezici, G., Lipani, A., Saygin, Y., Yilmaz, E. (2021). Evaluation metrics for measuring bias in search engine results. Information Retrieval Journal, doi:10.1007/s10791-020-09386-w
Priscillia, S., Schillaci, C., Lipani, A. (2021). Flood susceptibility assessment using artificial neural networks in Indonesia. Artificial Intelligence in Geosciences, 2 215-222. doi:10.1016/j.aiig.2022.03.002
Lipani, A., Carterette, B., Yilmaz, E. (2021). How Am I Doing?: Evaluating Conversational Search Systems Offline. ACM Transactions on Information Systems, doi:10.1145/3451160
Schillaci, C., Perego, A., Valkama, E., Märker, M., Saia, S., Veronesi, F., ...Gamper, H.A. (2021). New pedotransfer approaches to predict soil bulk density using WoSIS soil data and environmental covariates in Mediterranean agro-ecosystems. Science of The Total Environment, 780 146609. doi:10.1016/j.scitotenv.2021.146609
Anderson-Bell, J., Schillaci, C., Lipani, A. (2021). Predicting Non-Residential Building Fire Risk Using Geospatial Information and Convolutional Neural Networks. Remote Sensing Applications: Society and Environment, doi:10.1016/j.rsase.2021.100470
Cheng, T., Lu, T., Liu, Y., Gao, X., Zhang, X. (2021). Revealing spatiotemporal transmission patterns and stages of COVID-19 in China using individual patients’ trajectory data. Computational Urban Science, 1 (1), doi:10.1007/s43762-021-00009-8
Hayward, A., Fragaszy, E., Kovar, J., Nguyen, V., Beale, S., Byrne, T., ...Fong, W.L.E. (2021). Risk factors, symptom reporting, healthcare-seeking behaviour and adherence to public health guidance: protocol for Virus Watch, a prospective community cohort study. BMJ Open, 11 (6), doi:10.1136/bmjopen-2020-048042
Lipani, A., Piroi, F., Yilmaz, E. (2021). Towards More Accountable Search Engines: Online Evaluation of Representation Bias.
Byrne, T., Patel, P., Shrotri, M., Beale, S., Michie, S., Butt, J., ...Aryee, A. (2021). Trends, patterns and psychological influences on COVID-19 vaccination intention: Findings from a large prospective community cohort study in England and Wales (Virus Watch). Vaccine, doi:10.1016/j.vaccine.2021.09.066
Schillaci, C., Saia, S., Lipani, A., Perego, A., Zaccone, C., Acutis, M. (2021). Validating the regional estimates of changes in soil organic carbon by using the data from paired-sites: the case study of Mediterranean arable lands.. Carbon Balance Manag, 16 (1), 19. doi:10.1186/s13021-021-00182-7
Ibrahim, M.R., Haworth, J., Lipani, A., Aslam, N., Cheng, T., Christie, N. (2021). Variational-LSTM autoencoder to forecast the spread of coronavirus across the globe.. PLoS One, 16 (1), e0246120. doi:10.1371/journal.pone.0246120
Ibrahim, M.R., Haworth, J., Lipani, A., Aslam, N., Cheng, T., Christie, N. (2021). Variational-LSTM autoencoder to forecast the spread of coronavirus across the globe.. PLoS One, 16 (1), e0246120. doi:10.1371/journal.pone.0246120
Ibrahim, M.R., Haworth, J., Lipani, A., Aslam, N., Cheng, T., Christie, N. (2021). Variational-LSTM autoencoder to forecast the spread of coronavirus across the globe.. PLoS One, 16 (1), e0246120. doi:10.1371/journal.pone.0246120
Ren, Y., Chen, H., Han, Y., Cheng, T., Zhang, Y., Chen, G. (2020). A hybrid integrated deep learning model for the prediction of citywide spatio-temporal flow volumes. International Journal of Geographical Information Science, doi:10.1080/13658816.2019.1652303
Lai, J., Lansley, G., Haworth, J., Cheng, T. (2020). A name-led approach to profile urban places based on geotagged Twitter data. Transactions in GIS, doi:10.1111/tgis.12599
Lai, J., Lansley, G., Haworth, J., Cheng, T. (2020). A name-led approach to profile urban places based on geotagged Twitter data. Transactions in GIS, doi:10.1111/tgis.12599
Zhang, Y., Cheng, T., Ren, Y., Xie, K. (2020). A novel residual graph convolution deep learning model for short-term network-based traffic forecasting. International Journal of Geographical Information Science, 1-27. doi:10.1080/13658816.2019.1697879
Bantis, T., Haworth, J. (2020). Assessing transport related social exclusion using a capabilities approach to accessibility framework: A dynamic Bayesian network approach. Journal of Transport Geography, 84 102673. doi:10.1016/j.jtrangeo.2020.102673
Xia, J., Zhou, Y., Li, Z., Li, F., Yue, Y., Cheng, T., Li, Q. (2020). COVID-19 risk assessment driven by urban spatiotemporal big data: a case study of Guangdong-Hong Kong-Macao Greater Bay Area. Cehui Xuebao/Acta Geodaetica et Cartographica Sinica, 49 (6), 671-680. doi:10.11947/j.AGCS.2020.20200080
Chen, T., Bowers, K., Cheng, T., Zhang, Y., Chen, P. (2020). Exploring the homogeneity of theft offenders in spatio-temporal crime hotspots. Crime Science, 9 (1), doi:10.1186/s40163-020-00115-8
Zhang, Y., Cheng, T. (2020). Graph deep learning model for network-based predictive hotspot mapping of sparse spatio-temporal events. Computers, Environment and Urban Systems, 79 101403. doi:10.1016/j.compenvurbsys.2019.101403
Sari Aslam, N., Zhu, D., Cheng, T., Ibrahim, M.R., Zhang, Y. (2020). Semantic enrichment of secondary activities using smart card data and point of interests: a case study in London. Annals of GIS, doi:10.1080/19475683.2020.1783359
Ibrahim, M.R., Haworth, J., Cheng, T. (2020). Understanding cities with machine eyes: A review of deep computer vision in urban analytics. Cities, 96 doi:10.1016/j.cities.2019.102481
Ibrahim, M.R., Haworth, J., Cheng, T. (2020). Understanding cities with machine eyes: A review of deep computer vision in urban analytics. Cities, 96 doi:10.1016/j.cities.2019.102481
Zhang, Y., Sari Aslam, N., Lai, J., Cheng, T. (2020). You are how you travel: A multi-task learning framework for Geodemographic inference using transit smart card data. Computers, Environment and Urban Systems, doi:10.1016/j.compenvurbsys.2020.101517
Zhang, Y., Cheng, T. (2019). A Deep Learning Approach to Infer Employment Status of Passengers by Using Smart Card Data. IEEE Transactions on Intelligent Transportation Systems, doi:10.1109/TITS.2019.2896460
Zhang, Y., Cheng, T., Ren, Y. (2019). A graph deep learning method for short‐term traffic forecasting on large road networks. Computer-Aided Civil and Infrastructure Engineering, doi:10.1111/mice.12450
Ren, Y., Cheng, T., Zhang, Y. (2019). Deep spatio-temporal residual neural networks for road-network-based data modeling. International Journal of Geographical Information Science, doi:10.1080/13658816.2019.1599895
Roegiest, A., Lipani, A., Beutel, A., Olteanu, A., Lucic, A., Stoica, A.-.A., ...Hauff, C. (2019). FACTS-IR: Fairness, Accountability, Confidentiality, Transparency, and Safety in Information Retrieval. SIGIR Forum, 53
Lipani, A., Losada, D., Zuccon, G., Lupu, M. (2019). Fixed-Cost Pooling Strategies. IEEE Transactions on Knowledge and Data Engineering, doi:10.1109/TKDE.2019.2947049
Bantis, T., Haworth, J. (2019). Non-Employment Activity Type Imputation from Points of Interest and Mobility Data at an Individual Level: How Accurate Can We Get?. ISPRS International Journal of Geo-Information, 8 (12), 560. doi:10.3390/ijgi8120560
Ibrahim, M.R., Titheridge, H., Cheng, T., Haworth, J. (2019). predictSLUMS: A new model for identifying and predicting informal settlements and slums in cities from street intersections using machine learning. Computers, Environment and Urban Systems, 76 31-56. doi:10.1016/j.compenvurbsys.2019.03.005
Ibrahim, M.R., Titheridge, H., Cheng, T., Haworth, J. (2019). predictSLUMS: A new model for identifying and predicting informal settlements and slums in cities from street intersections using machine learning. Computers, Environment and Urban Systems, 76 31-56. doi:10.1016/j.compenvurbsys.2019.03.005
Ibrahim, M., Haworth, J., Cheng, T. (2019). URBAN-i: From urban scenes to mapping slums, transport modes, and pedestrians in cities using deep learning and computer vision. Environment and Planning B: Urban Analytics and City Science, doi:10.1177/2399808319846517
Ibrahim, M., Haworth, J., Cheng, T. (2019). URBAN-i: From urban scenes to mapping slums, transport modes, and pedestrians in cities using deep learning and computer vision. Environment and Planning B: Urban Analytics and City Science, doi:10.1177/2399808319846517
Ibrahim, M.R., Haworth, J., Cheng, T. (2019). WeatherNet: Recognising Weather and Visual Conditions from Street-Level Images Using Deep Residual Learning. ISPRS International Journal of Geo-Information, 8 (12), 549. doi:10.3390/ijgi8120549
Ibrahim, M.R., Haworth, J., Cheng, T. (2019). WeatherNet: Recognising Weather and Visual Conditions from Street-Level Images Using Deep Residual Learning. ISPRS International Journal of Geo-Information, 8 (12), 549. doi:10.3390/ijgi8120549
Cheshire, J.A., Cheng, T., Sari Aslam, N. (2018). A high-precision heuristic model to detect home and work locations from smart card data. Geo-Spatial Information Science, doi:10.1080/10095020.2018.1545884
Rollocks, D., Haworth, J., Blangiardo, M., Cheng, T. (2018). A Spatiotemporal Bayesian Hierarchical Approach to Investigating Patterns of Confidence in the Police at the Neighborhood Level. Geographical Analysis, doi:10.1111/gean.12160
Rollocks, D., Haworth, J., Blangiardo, M., Cheng, T. (2018). A Spatiotemporal Bayesian Hierarchical Approach to Investigating Patterns of Confidence in the Police at the Neighborhood Level. Geographical Analysis, doi:10.1111/gean.12160
Lipani, A., Roelleke, T., Lupu, M., Hanbury, A. (2018). A systematic approach to normalization in probabilistic models. Information Retrieval Journal, 21 565-596. doi:10.1007/s10791-018-9334-1
Chen, H., Cheng, T., Ye, X. (2018). Designing efficient and balanced police patrol districts on an urban street network. International Journal of Geographical Information Science, doi:10.1080/13658816.2018.1525493
Manley, E., Cheng, T. (2018). Exploring the Role of Spatial Cognition in Predicting Urban Traffic Flow through Agent-based Modelling. Transportation Research Part A: Policy and Practice, doi:10.1016/j.tra.2018.01.020
Taalab, K., Cheng, T., Zhang, Y. (2018). Mapping landslide susceptibility and types using Random Forest. Big Earth Data, 2 (2), 159-178. doi:10.1080/20964471.2018.1472392
Liu, Y., Cheng, T. (2018). Understanding public transit patterns with open geodemographics to facilitate public transport planning. Transportmetrica A: Transport Science, 1-28. doi:10.1080/23249935.2018.1493549
Chen, H., Cheng, T., Shawe-Taylor, J. (2017). A Balanced Route Design for Min-Max Multiple-Depot Rural Postman Problem (MMMDRPP): a police patrolling case. International Journal of Geographical Information Science, 1-22. doi:10.1080/13658816.2017.1380201
Twigg, J., Christie, N., Haworth, J., Osuteye, E., Skarlatidou, A. (2017). Improved Methods for Fire Risk Assessment in Low-Income and Informal Settlements. International Journal of Environmental Research and Public Health, 14 (2), 139. doi:10.3390/ijerph14020139
Lai, J., Cheng, T., Lansley, G. (2017). Improved targeted outdoor advertising based on geotagged social media data. Annals of GIS, 1-14. doi:10.1080/19475683.2017.1382571
Schillaci, C., Acutis, M., Lombardo, L., Lipani, A., Fantappie, M., Maerker, M., Saia, S. (2017). Spatio-temporal topsoil organic carbon mapping of a semi-arid Mediterranean region: The role of land use, soil texture, topographic indices and the influence of remote sensing data to modelling. Science of The Total Environment, 601-602 821-832. doi:10.1016/j.scitotenv.2017.05.239
Bantis, A., Haworth, J. (2017). Who you are is how you travel: A framework for transportation mode detection using individual and environmental characteristics. Transportation Research Part C: Emerging Technologies, doi:10.1016/j.trc.2017.05.003
Shen, J., Cheng, T. (2016). A framework for identifying activity groups from individual space-time profiles. International Journal of Geographical Information Science, 30 (9), 1785-1805. doi:10.1080/13658816.2016.1139119
Wise, S.C., Chen, H., Cheng, T. (2016). Developing an online cooperative police patrol routing strategy. Computers, Environment and Urban Systems, doi:10.1016/j.compenvurbsys.2016.10.013
Wise, S.C., Cheng, T. (2016). How Officers Create Guardianship: An Agent-based Model of Policing. TRANSACTIONS IN GIS, 20 (5), 790-806. doi:10.1111/tgis.12173
Rosser, G., Cheng, T. (2016). Improving the Robustness and Accuracy of Crime Prediction with the Self-Exciting Point Process Through Isotropic Triggering. Applied Spatial Analysis and Policy, 1-21. doi:10.1007/s12061-016-9198-y
Adepeju, M., Rosser, G., Cheng, T. (2016). Novel evaluation metrics for sparse spatio-temporal point process hotspot predictions - a crime case study. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 30 (11), 2133-2154. doi:10.1080/13658816.2016.1159684
Rosser, G., Davies, T., Bowers, K.J., Johnson, S.D., Cheng, T. (2016). Predictive Crime Mapping: Arbitrary Grids or Street Networks?. Journal of Quantitative Criminology, 1-26. doi:10.1007/s10940-016-9321-x
Manley, E.J., Orr, S.W., Cheng, T. (2015). A heuristic model of bounded route choice in urban areas. Transportation Research Part C: Emerging Technologies, 56 195-209. doi:10.1016/j.trc.2015.03.020
Li, S., Dragicevic, S., Castro, F.A., Sester, M., Winter, S., Coltekin, A., ...Stein, A. (2015). Geospatial big data handling theory and methods: A review and research challenges. ISPRS Journal of Photogrammetry and Remote Sensing, 115 119-133. doi:10.1016/j.isprsjprs.2015.10.012
Li, S., Dragicevic, S., Castro, F.A., Sester, M., Winter, S., Coltekin, A., ...Stein, A. (2015). Geospatial big data handling theory and methods: A review and research challenges. ISPRS Journal of Photogrammetry and Remote Sensing, 115 119-133. doi:10.1016/j.isprsjprs.2015.10.012
Anbaroglu, B., Cheng, T., Heydecker, B. (2015). Non-recurrent traffic congestion detection on heterogeneous urban road networks. Transportmetrica A: Transport Science, 11 (9), 754-771. doi:10.1080/23249935.2015.1087229
Manley, E.J., Addison, J.D., Cheng, T. (2015). Shortest path or anchor-based route choice: a large-scale empirical analysis of minicab routing in London. JOURNAL OF TRANSPORT GEOGRAPHY, 43 123-139. doi:10.1016/j.jtrangeo.2015.01.006
Cheng, T., Wang, J., Haworth, J., Heydecker, B., Chow, A. (2014). A Dynamic Spatial Weight Matrix and Localized Space–Time Autoregressive Integrated Moving Average for Network Modeling. Geographical Analysis, 46 (1), 75-97. doi:10.1111/gean.12026
Manley, E., Cheng, T., Penn, A., Emmonds, A. (2014). A framework for simulating large-scale complex urban traffic dynamics through hybrid agent-based modelling. Computers, Environment and Urban Systems, 44 27-36. doi:10.1016/j.compenvurbsys.2013.11.003
Bolbol, A., Cheng, T., Tsapakis, I. (2014). A spatio-temporal approach for identifying the sample size for transport mode detection from GPS-based travel surveys: A case study of London's road network. Transportation Research Part C: Emerging Technologies, 43 176-187. doi:10.1016/j.trc.2013.11.006
Chow, A.H.F., Santacreu, A., Tsapakis, I., Tanasaranond, G., Cheng, T. (2014). Empirical assessment of urban traffic congestion. Journal of Advanced Transportation, 48 (8), 1000-1016. doi:10.1002/atr.1241
Chow, A.H.F., Santacreu, A., Tsapakis, I., Tanasaranond, G., Cheng, T. (2014). Empirical assessment of urban traffic congestion. Journal of Advanced Transportation, 48 (8), 1000-1016. doi:10.1002/atr.1241
Cheng, T., Wicks, T. (2014). Event detection using Twitter: a spatio-temporal approach.. PLoS One, 9 (6), doi:10.1371/journal.pone.0097807
James, H., John, S.T., Tao, C., Jiaqiu, W. (2014). Local online kernel ridge regression for forecasting of urban travel times. Transportation Research Part C: Emerging Technologies, 46 151-178. doi:10.1016/j.trc.2014.05.015
James, H., John, S.T., Tao, C., Jiaqiu, W. (2014). Local online kernel ridge regression for forecasting of urban travel times. Transportation Research Part C: Emerging Technologies, 46 151-178. doi:10.1016/j.trc.2014.05.015
Cheng, T., Adepeju, M. (2014). Modifiable temporal unit problem (MTUP) and its effect on space-time cluster detection.. PLoS One, 9 (6), doi:10.1371/journal.pone.0100465
Zhang, W., Cheng, T., Mei, Z., Wang, J. (2014). Spatial distribution and autocorrelation pattern of Shenzhen service industries. Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering, 31 (6), 638-646. doi:10.3724/SP.J.1249.2014.06638
Anbaroglu, B., Heydecker, B., Cheng, T. (2014). Spatio-temporal clustering for non-recurrent traffic congestion detection on urban road networks. Transportation Research Part C: Emerging Technologies, 48 47-65. doi:10.1016/j.trc.2014.08.002
Cheng, T., Wang, J., Haworth, J., Heydecker, B.G., Chow, A.H.F. (2013). A dynamic spatial weight matrix and localized space-time autoregressive integrated moving average for network modeling. Geographical Analysis: an international journal of theoretical geography,
Cheng, T., Wang, J., Haworth, J., Heydecker, B.H., Chow, A.H.F. (2013). Dynamic spatial weight matrix and localised STARIMA for network modelling. Geographical Analysis: an international journal of theoretical geography,
Cheng, T., Tanaksaranond, G., Brunsdon, C., Haworth, J. (2013). Exploratory visualisation of congestion evolutions on urban transport networks. Transportation Research Part C: Emerging Technologies, 36 296-306. doi:10.1016/j.trc.2013.09.001
Cheng, T., Tanaksaranond, G., Brunsdon, C., Haworth, J. (2013). Exploratory visualisation of congestion evolutions on urban transport networks. Transportation Research Part C: Emerging Technologies, 36 296-306. doi:10.1016/j.trc.2013.09.001
Cheng, T., Tanaksaranond, G., Brunsdon, C., Haworth, J. (2013). Exploratory visualisation of congestion evolutions on urban transport networks. Transportation Research Part C: Emerging Technologies, 36 296-306. doi:10.1016/j.trc.2013.09.001
Cheng, T., Tanaksaranond, G., Brunsdon, C., Haworth, J. (2013). Exploratory visualisation of congestion evolutions on urban transport networks. Transportation Research Part C: Emerging Technologies, 36 296-306. doi:10.1016/j.trc.2013.09.001
Skarlatidou, A., Cheng, T., Haklay, M. (2013). Guidelines for trust interface design for public engagement Web GIS. International Journal of Geographical Information Science, doi:10.1080/13658816.2013.766336
Tsapakis, I., Heydecker, B.G., Cheng, T., Anbaroglu, B. (2013). How metro strikes affect macroscopic and microscopic travel times in London. Transportation Planning and Technology, 36 (1), doi:10.1080/03081060.2012.745766
Tsapakis, I., CHENG, T. (2013). Impact of weather conditions on macroscopic urban travel times. Journal of Transport Geography, 28 204-211. doi:10.1016/j.jtrangeo.2012.11.003
Dong, J.X., Cheng, T., Xu, J., Wu, J. (2013). Quantitative assessment of urban road network hierarchy planning. Town Planning Review, 84 (4), 445-472. doi:10.3828/tpr.2013.24
Cheng, T., Haworth, J., Manley, E. (2012). Advances in Geocomputation (1996-2011). Computers, Environment and Urban Systems, doi:10.1016/j.compenvurbsys.2012.10.002
Cheng, T., Haworth, J., Manley, E. (2012). Advances in geocomputation (1996-2011). Computers, Environment and Urban Systems, 36 (6), 481-487. doi:10.1016/j.compenvurbsys.2012.10.002
Cheng, T., Haworth, J., Manley, E. (2012). Advances in Geocomputation (1996-2011). Computers, Environment and Urban Systems, doi:10.1016/j.compenvurbsys.2012.10.002
Tsapakis, I., Turner, J., Cheng, T., Heydecker, B., Emmonds, A., Bolbol, A. (2012). Effects of Tube Strikes on Journey Times in the Transport Network of London. Transportation Research Record 2274: Journal of the Transportation Research Board (TRB), 84-92. doi:10.3141/2274-09
Cheng, T. (2012). Guest editorial: Integrated spatio-temporal analysis and data mining. GEOINFORMATICA, 16 (4), 623-624. doi:10.1007/s10707-012-0167-6
Tsapakis, I., Heydecker, B.G., Cheng, T., Anbaroglu, B. (2012). How tube strikes affect macroscopic and link travel times in London. Transportation Planning and Technology,
Bolbol, A., CHENG, T., Tsapakis, I., Haworth, J. (2012). Inferring hybrid transportation modes from sparse GPS data using a moving window SVM classification. Computers, Environment and Urban Systems, doi:10.1016/j.compenvurbsys.2012.06.001
Bolbol, A., CHENG, T., Tsapakis, I., Haworth, J. (2012). Inferring hybrid transportation modes from sparse GPS data using a moving window SVM classification. Computers, Environment and Urban Systems, doi:10.1016/j.compenvurbsys.2012.06.001
Samarasundera, E., CHENG, T., Walsh, T., Koenig, A., Jattansingh, K., Dawe, A., Soljak, M. (2012). Methods and tools for geographical mapping and analysis in primary health care. Primary Health Care Research and Development, 13 (1), 10-21. doi:10.1017/S1463423611000417
Haworth, J., Cheng, T. (2012). Non-parametric regression for space-time forecasting under missing data. Computers, Environment and Urban Systems, 36 (6), 538-550. doi:10.1016/j.compenvurbsys.2012.08.005
Haworth, J., Cheng, T. (2012). Non-parametric regression for space-time forecasting under missing data. Computers, Environment and Urban Systems, 36 (6), 538-550. doi:10.1016/j.compenvurbsys.2012.08.005
Haworth, J., CHENG, T. (2012). Non-parametric regression for space–time forecasting under missing data. Computers, Environment and Urban Systems, doi:10.1016/j.compenvurbsys.2012.08.005
CHENG, T., Haworth, J., Wang, J. (2012). Spatio-temporal autocorrelation of road network data. Journal of Geographical Systems, 14 (4), 389-413. doi:10.1007/s10109-011-0149-5
CHENG, T., Haworth, J., Wang, J. (2012). Spatio-temporal autocorrelation of road network data. Journal of Geographical Systems, 14 (4), 389-413. doi:10.1007/s10109-011-0149-5
Skarlatidou, A., Cheng, T., Haklay, M. (2012). What do lay people want to know about the disposal of nuclear waste? - A mental model approach to the design and development of an online risk communication. Risk Analysis, 32 (9), 1496-1511. doi:10.1111/j.1539-6924.2011.01773.x
Cheng, T., Wang, J.Q., Li, X. (2011). A hybrid framework for space-time modeling of environmental data. GEOGR ANAL, 43 (2), 188-210. doi:10.1111/j.1538-4632.2011.00813.x
Deng, M., Liu, Q., Cheng, T., Shi, Y. (2011). An adaptive spatial clustering algorithm based on delaunay triangulation. Computers, Environment and Urban Systems, 35 (4), 320-332. doi:10.1016/j.compenvurbsys.2011.02.003
Koenig, A., Samarasundera, E., Cheng, T. (2011). Interactive map communication: Pilot study of the visual perceptions and preferences of public health practitioners. Public Health, 125 (8), 554-560. doi:10.1016/j.puhe.2011.02.011
Cheng, T., Haworth, J., Wang, J. (2011). Spatio-temporal Autocorrelation of Road Network Data. Journal of Geographical Systems, doi:10.1007/s10109-011-0149-5
Cheng, T., Haworth, J., Wang, J. (2011). Spatio-temporal Autocorrelation of Road Network Data. Journal of Geographical Systems, doi:10.1007/s10109-011-0149-5
Skarlatidou, A., Haklay, M., CHENG, T. (2011). Trust in Web GIS: The role of the trustee attributes in the design of trustworthy Web GIS applications. International Journal of Geographical Information Science, doi:10.1080/13658816.2011.557379
Skarlatidou, A., CHENG, T., Haklay, M. (2011). What do laypeople want to know about the disposal of nuclear waste? A mental model approach for risk communication via online information.. Risk Analysis,
Cheng, T., Tanaksaranond, G., Emmonds, A., Sonoiki, D. (2010). Multi-scale visualisation of inbound and outbound traffic delays in London. CARTOGR J, 47 (4), 323-329. doi:10.1179/000870410X12911311788152
Li, G., Deng, M., Liu, Q., CHENG, T. (2009). A spatial clustering method adaptive to local density change. Acta Geodaetica et Cartographica Sinica, 38 (3), 255-263.
Cheng, T., Wang, J. (2009). Accommodating spatial associations in DRNN for space-time analysis. COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 33 (6), 409-418. doi:10.1016/j.compenvurbsys.2009.08.004
Li, G.Q., Deng, M., Cheng, T., Zhu, J.J. (2008). A dual distance based spatial clustering method. Acta Geodaetica et Cartographica Sinica, 37 (4), 482-488.
Li, G.Q., Deng, M., Zhu, J.J., Cheng, T. (2008). A new detection method of spatial outliers by considering the distances of spatial entities in their neighbors. Journal of Remote Sensing (in chinese), 12 (5), 197-202.
Deng, M., Liu, Y., CHENG, T., Chen, J. (2008). An approach for evaluation of semantic quality in map generalization. Geography and Geo-Information Science, 25 (5), 20-51.
Chen, J., Liu, W., Li, Z., Zhao, R., Cheng, T. (2008). Detection of spatial conflicts between rivers and contours in digital map updating. International Journal of Geographical Information Science,
Cheng, T., Wang, J. (2008). Integrated spatio-temporal data mining for forest fire prediction. Transactions in GIS, 12 (5), 591-611. doi:10.1111/j.1467-9671.2008.01117.x
Deng, M., Cheng, T., Chen, X. (2007). A General Approach for Topological Relations Between Spatial Regions. GeoInformatica, 11 (2), 239-267.
Zuo, X., Li, Q., Yang, B., Cheng, T. (2007). A view‐dependent method for the multi‐resolution representation of terrains with roads embedded. International Journal of Remote Sensing, 28 (2), 319-334. doi:10.1080/01431160600702657
Wang, J.Q., Cheng, T. (2007). Applications of spatio-temporal forecasting to forest fire prevention. Zhongshan Daxue Xuebao/Acta Scientiarum Natralium Universitatis Sunyatseni, 46 (2),
Chen, J., Liu, W., Li, Z., Zhao, R., Cheng, T. (2007). Detection of spatial conflicts between rivers and contours in digital map updating. INT J GEOGR INF SCI, 21 (10), 1093-1114. doi:10.1080/13658810701300071
Fisher, P., Wood, J., Cheng, T. (2007). Higher order vagueness in a dynamic landscape: multiresolution morphometric analysis of a coastal dunefield. Journal of Environmental Informatics, 9 (1), 56-70. doi:10.3808/jei.200700087
Fisher, P., Cheng, T., Wood, J. (2007). Higher Order Vagueness in Geographical Information: Empirical Geographical Population of Type n Fuzzy Sets. Geoinformatica, 11 (3), 311-330. doi:10.1007/s10707-006-0009-5
Deng, M., Cheng, T., Chen, X., Li, Z. (2007). Multi-level topological relations between spatial regions based upon topological invariants. Geoinformatica, 11 (2), 239-267. doi:10.1007/s10707-006-0004-x
Cheng, T., Deng, M., Li, Z. (2007). Representation methods of spatial objects with uncertainty and their application in GIS. Geomatics and Information Science of Wuhan University, 32 (5), 389-393.
Wang, J., Cheng, T. (2007). Using spatio-temporal data mining and knowledge discovery for forest fire prevention. Acta Scientiarum Naturalium Universitatis Sun Yat-sen I, 46 (2), 110-116.
Cheng, T., Li, Z. (2006). A multi-scale approach for spatial-temporal outlier detection. Transactions in GIS, 10 (2), 253-263. doi:10.1111/j.1467-9671.2006.00256.x
Cheng, T., Li, Z. (2006). Effect of generalisation on area features: a comparative study of two strategies. Cartographic Journal, 43 (2), 157-170. doi:10.1179/000870406X114649
Deng, M., Li, Z., Cheng, T. (2006). Rough-set representation of GIS data uncertainties with multiple granularities. Acta Geodaetica et Cartographica Sinica, 35 (1), 64-70.
Chen, J., Liu, W., Li, Z., Cheng T, Z.R. (2006). The refined calculation method of topological relationships between line objects. Acta Geodaetica et Cartographica Sinica, 35 (3), 255-260.
Cheng, T., Li, Z. (2006). Towards quantitive measures for semantic quality of polygon generalization. Cartographica, 41 (2), 135-148. doi:10.3138/0172-6733-227U-8155
Cheng, T., Fisher, P., Li, Z. (2004). Double Vagueness: uncertainty in multi-scale fuzzy assignment of duneness. Geo-Spatial Information Science, 7 (1), 58-66. doi:10.1007/BF02826677
Fisher, P., Wood, J., Cheng, T. (2004). Where is Helvellyn? Multiscale morphometry and the mountains of the English Lake District. Transactions of the Institute of British Geographers, 29 (1), 106-128. doi:10.1111/j.0020-2754.2004.00117.x
Cheng, T. (2002). Fuzzy objects: their change and uncertainties. Photogrammetric Engineering and Remote Sensing, 68 (1), 41-49.
Wang, D., Cheng, T. (2001). A spatio-temporal data model for activity-based transport demand modelling. International Journal of Geographical Information Science, 15 (6), 561-586. doi:10.1080/13658810110046934
Cheng, T., Lin, H. (2001). Concept, model and application of fuzzy objects. Journal of Remote Sensing, 5 248-253.
Cheng, T., Molenaar, M., Lin, H. (2001). Formalising fuzzy objects from uncertain classification results. International Journal of Geographical Information Science, 15 (1), 27-42. doi:10.1080/13658810010004689
Molenaar, M., Cheng, T. (2000). Fuzzy spatial objects and their dynamics. ISPRS Journal of Photogrammetry and Remote Sensing, 55 (3), 164-175. doi:10.1016/S0924-2716(00)00017-4
Cheng, T., Molenaar, M. (1999). Diachronic analysis of fuzzy objects. GeoInformatica, 3 (4), 337-356. doi:10.1023/A:1009884730822
Cheng, T., Molenaar, M. (1999). Objects with fuzzy spatial extent. Photogrammetric Engineering and Remote Sensing, 65 (7), 797-801.
Blok, C., Kobben, B., Cheng, T., Kuterema, A. (1999). The visualizations of relationships between spatial patterns in time by cartographic animation. Cartography and Geographic Information Science, 26 (2), 139-151. doi:10.1559/152304099782330716
Van Zuidam, R., Farifteh, J., Eleveld, M., Cheng, T. (1998). Developments in remote sensing, dynamic modelling and GIS applications for integrated coastal zone management. Journal of Coastal Conservation, 4 (2), 191-202. doi:10.1007/BF02806511
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Cheng, T., Li, D., Shu, N. (1992). An expert system prototype for remote sensing image interpretation. Journal of Wuhan Technical University of Surveying and Mapping, 17 155-166.
Cheng, T. (1991). Geographic information system and expert system. Journal of Postgraduates in Wuhan Technical University of Surveying and Mapping, (1),
Tsapakis, I., Schneider, W.H., Nichols, A., Haworth, J. (1900). Alternatives in Assigning Coverage Counts to Factor Groupings for a Precise Estimation of Annual Average Daily Traffic. Journal of Advanced Transportation, doi:10.1002/atr.1186

Report

Skarlatidou, A., Cheng, T., Haylay, M., Nicholson, D., Atherton, E. (2007). Public response to Defra (Department for Environment, Food and Rural Affairs) Consultation on public participation in nuclear disposal site selection. .

Thesis / Dissertation

Cheng, T. (1900). A Process-oriented Data Model for Fuzzy Spatial Objects. (Doctoral Dissertation).
Sari Aslam, N. (1900). Analysis of Demand Dynamics and Inter-modal Connectivity in London Bicycle Sharing System. (). UCL.
Cheng, T. (1900). Developing an Expert System for Grass Resource Investigation in North-West China,. ().
Zhang, Y. (1900). Graph Deep Learning Models for Network-based Spatio-Temporal Data Forecasting: From Dense to Sparse. (Doctoral Dissertation). UCL (University College London).
Cheng, T. (1900). Multiscale Spatio-Temporal Data Modeling, Analyzing and Reasoning. (Doctoral Dissertation).
Lipani, A. (1900). On Biases in Information Retrieval Models and Evaluation. (Doctoral Dissertation). TU Wien.
Sari Aslam, N. (1900). Online support vector regression for network travel time prediction. (). UCL.
Sari Aslam, N. (1900). Online support vector regression for network travel time prediction. (). UCL.
Haworth, J. (1900). Spatio-temporal forecasting of network data. (Doctoral Dissertation). UCL.

Working/Discussion Paper

Hayward, A., Fragaszy, E., Kovar, J., Nguyen, V., Beale, S., Byrne, T., ...Erica Fong, W.L. (2020). Risk factors, symptom reporting, healthcare-seeking behaviour and adherence to public health guidance: protocol for Virus Watch, a prospective community cohort study. .