Dr Suparna De

Lecturer in Computer Science
Ph.D, MSc (distinction), B.Sc. (honours), FHEA
+44 (0)1483 682261
Thursdays 10:00-12:00


Areas of specialism

Natural language understanding for longitudinal data; Semantic search and modelling; Machine learning applications; Big Data analysis ; Computational Social Science

University roles and responsibilities

  • Computer Science Admissions Tutor (UG)

    Affiliations and memberships

    IEEE Standards Association: P3800 WG
    Working Group member of the IEEE P3800 - Standard for a Data-Trading System

    Academic networks


      In the media


      Research interests

      Research projects

      Indicators of esteem

      • Scholarships:
        • Overseas Research Student Sponsorship for PhD research: University of Surrey and MobileVCE Core 4 programme
        • DFIDSSS Scholarship: jointly funded by the University of Surrey and the British Commonwealth Scholarship Commission for MSc programme.
      • Awards:
        • Cable and Wireless Award: University of Surrey, for the best overall performance from a student graduating with an MSc in Satellite Communication Engineering or Communications Networks and Software
        • IET Certificate in recognition of significant contribution to IET On Campus at the University of Surrey

        Research Themes

        Data analytics for Cyber-Physical and Social Streams

        This research theme focusses on deriving latent patterns in CPSS data streams by developing novel ML algorithms; as well as fusion of social network data with sensor data streams. Our work looks at analysing social network data to extract real-world event information and human movements, in conjunction with sensor data and open datasets, to achieve outcomes related to quantifying their influence on smart city dynamics, such as traffic flows, measured pollution levels, redefining inner-city boundaries etc.

        Related publications:

        • Exploring the Effectiveness of Service Decomposition in Fog Computing Architecture for the Internet of Things, IEEE Transactions on Sustainable Computing, March 2019
        • A Survey on an Emerging Area: Deep Learning for Smart City Data, IEEE Transactions on Emerging Topics in Computational Intelligence, May 2019
        • Data-driven Air Quality Characterisation for Urban Environments: a Case Study, IEEE Access, December 2018
        • Missing Data Estimation in Mobile Sensing Environments, IEEE Access 6(1), October 2018 
        • Cyber–Physical–Social Frameworks for Urban Big Data Systems: A Survey. MDPI Applied Sciences, 2017, 7 (10) (slideshare)
        • Real world city event extraction from Twitter data streams, Procedia Computer Science, 2016, 98, pp. 443-448 (dataset)

        Large scale sensor and data discovery and ranking

        This research theme focuses on scalable, distributed discovery mechanisms supporting the sensor-as-a-service paradigm. Based on the particular localization characteristics of IoT deployments, our work has developed novel methods using geospatial indexing techniques and semantic service technologies for both sensor and sensor data discovery.

        Related publications:

        • Designing the Sensing as a Service Ecosystem for the Internet of Things, IEEE Internet of Things Magazine,1(2), December 2018
        • Spatial Indexing for Data Searching in Mobile Sensing Environments. Sensors 2017, 17(6), 1427
        • Search Techniques for the Web of Things: A Taxonomy and Survey, Sensors 2016, 16(5), 600
        • An Experimental Study on Geospatial Indexing for Sensor Service Discovery, Expert Systems with Applications, Elsevier, May 2015 (ontologydataset)
        • A Ranking Method for Sensor Services based on Estimation of Service Access Cost, Information Sciences, Elsevier, October 2015 (code and dataset)
        • Enabling Query of Frequently Updated Data from Mobile Sensing Sources, The 13th IEEE International Conferences on Ubiquitous Computing and Communications (IUCC2014), December 2014.

        Semantic Models for the Internet of Things

        This research theme focusses on semantic models for the main abstractions and concepts that underlie the IoT domain. The developed ontologies enable fine-grained semantic annotations, and to create Linked sensor data for service and data discovery.

        Related publications:

        • SmartTags: IoT Product Passport for Circular Economy Based on Printed Sensors and Unique Item-Level Identifiers, Sensors 2019, 19(3), 586.
        • Knowledge Representation in the Internet of Things: Semantic Modelling and its Applications. Automatika – Journal for Control, Measurement, Electronics, Computing and Communications, December 2013. 
        • An Internet of Things Platform for Real-World and Digital Objects'. Scalable Computing: Practice and Experience, May 2012. (platform demo)
        • Service modelling for the Internet of Things, IEEE Federated Conference on Computer Science and Information Systems (FEDCSIS), September 2011 (ontology)


        Completed postgraduate research projects I have supervised

        Postgraduate research supervision