People

Dr Sefki Kolozali

Postdoctoral Fellow (Institute for Analytics and Data Science)
School of Computer Science and Electronic Engineering (CSEE)
Dr Sefki Kolozali

Profile

Biography

I am a Postdoctoral Research Fellow at the Institute of Analytics and Data Science, University of Essex. I am interested in the field of Internet of Things. Previously, I worked as a Research Associate in Applied Big Data Analysis at the MRC-PHE Centre for Environment and Health, King's College London. I worked on exploring links between the environment and human health through the analysis of very large time series datasets. I was part of the COPE study team, which aims to reduce the frequency of hospital and GP visits by patients with respiratory disease. I also worked as a Research Fellow in large-scale data analytics for the Internet of Things at the 5G innovation centre, University of Surrey, where I was a work package leader in large scale data analysis and seamless integration of data sources in the CityPulse project. I received a B.Sc. degree in Computer Engineering from Near East University, Nicosia, Turkish Republic of Northern Cyprus, in 2005. I received an M.Sc. degree from the University of Essex and a PhD degree from Queen Mary University of London. My thesis was titled Automatic Ontology Generation Based on Semantic Audio Analysis.

Qualifications

  • PhD on Automatic Ontology Generation Based on Semantic Audio Analysis Queen Mary University of London, (2013)

  • MSc in E-Commerce Technologies University of Essex, (2008)

  • BSc in Computer Engineering Near East University, (2005)

Appointments

University of Essex

  • Postdoctoral Research Fellow, Institute for Analytics and Data Science, University of Essex (2/7/2018 - present)

Other academic

  • Research Associate in Applied Big Data Analysis, MRC-PHE Centre for Environment and Health, Faculty of Life Sciences, King's College London (1/9/2016 - 30/4/2018)

  • Research Fellow in Large-scale data analytics for the Internet of Things, Institute for Communication Systems (ICS), University of Surrey (4/2/2014 - 31/8/2016)

Research and professional activities

Research interests

Internet of Things

Machine Learning

Semantic Web

Signal Processing

Teaching and supervision

Current teaching responsibilities

  • Team Project Challenge (CE101)

Publications

Journal articles (7)

van den Brink, L., Barnaghi, P., Tandy, J., Atemezing, GA., Atkinson, R., Cochrane, B., Fathy, Y., García-Castro, R., Haller, A., Harth, A., Janowicz, K., Kolozali, S., van Leeuwen, B., Lefrançois, M., Lieberman, J., Perego, A., Le Phuoc, D., Roberts, B., Taylor, K. and Troncy, R., (2019). Best Practices for Publishing, Retrieving, and Using Spatial Data on the Web. Semantic Web. 10 (1), 95-114

Kolozali, S., Bermudez-Edo, M., FarajiDavar, N., Barnaghi, P., Gao, F., Intizar Ali, M., Mileo, A., Fischer, M., Iggena, T., Kuemper, D. and Tonjes, R., (2019). Observing the Pulse of a City: A Smart City Framework for Real-time Discovery, Federation, and Aggregation of Data Streams. IEEE Internet of Things Journal. 6 (2), 2651-2668

Quint, JK., Moore, E., Lewis, A., Hashmi, M., Sultana, K., Wright, M., Smeeth, L., Chatzidiakou, L., Jones, R., Beevers, S., Kolozali, S., Kelly, F. and Barratt, B., (2018). Recruitment of patients with Chronic Obstructive Pulmonary Disease (COPD) from the Clinical Practice Research Datalink (CPRD) for research. npj Primary Care Respiratory Medicine. 28 (1), 21-

Hashmi, M., Wright, M., Sultana, K., Barratt, B., Chatzidiakou, L., Moore, E., Kolozali, Ş., Jones, RL., Beevers, S., Smeeth, L., Kelly, FJ. and Quint, JK., (2018). Preliminary results from the COPE study using primary-care electronic health records and environmental modelling to examine COPD exacerbations. British Journal of General Practice. 68 (suppl 1), bjgp18X696749-bjgp18X696749

Kolozali, S., Puschmann, D., Bermudez-Edo, M. and Barnaghi, P., (2016). On the Effect of Adaptive and Nonadaptive Analysis of Time-Series Sensory Data. IEEE Internet of Things Journal. 3 (6), 1084-1098

Puiu, D., Barnaghi, P., Tonjes, R., Kumper, D., Ali, MI., Mileo, A., Xavier Parreira, J., Fischer, M., Kolozali, S., Farajidavar, N., Gao, F., Iggena, T., Pham, T-L., Nechifor, C-S., Puschmann, D. and Fernandes, J., (2016). CityPulse: Large Scale Data Analytics Framework for Smart Cities. IEEE Access. 4, 1086-1108

Kolozali, S., Barthet, M., Fazekas, G. and Sandler, M., (2013). Automatic Ontology Generation for Musical Instruments Based on Audio Analysis. IEEE Transactions on Audio, Speech, and Language Processing. 21 (10), 2207-2220

Conferences (11)

Kolozali, S., Chatzidiakou, L., Jones, R., Quint, JK., Kelly, F. and Barratt, B., A probabilistic multi-aspect learning model for the early detection of COPD patients' symptoms

Ahrabian, A., Kolozali, S., Enshaeifar, S., Cheong-Took, C. and Barnaghi, P., (2017). Data analysis as a web service: A case study using IoT sensor data

Barratt, B., Chatzidiakou, L., Moore, E., Quint, J., Beevers, S., Kolozali, S., Kelly, F., Jones, R. and Smeeth, L., (2017). Characterisation of COPD exacerbations using personal environmental exposure monitoring

Farajidavar, N., Kolozali, S. and Barnaghi, P., (2016). Physical-cyber-social similarity analysis in smart cities

Kolozali, S., Bermudez-Edo, M., Puschmann, D., Ganz, F. and Barnaghi, P., (2014). A Knowledge-Based Approach for Real-Time IoT Data Stream Annotation and Processing

Kolozali, Ş., Elsaleh, T. and Barnaghi, P., (2014). A validation tool for the W3C SSN ontology based sensory semantic knowledge

Kolozali, S., Fazekas, G., Barthet, M. and Sandler, MB., (2014). A framework for automatic ontology generation based on semantic audio analysis

Barthet, M., Anglade, A., Fazekas, G., Kolozali, S. and Macrae, R., (2011). Music recommendation for music learning: Hotttabs, a multimedia guitar tutor

Kolozali, S., Barthet, M., Fazekas, G. and Sandler, M., (2011). Knowledge representation issues in musical instrument ontology design

Kolozali, S., Barthet, M., Fazekas, G. and Sandler, M., (2011). Towards the Automatic Generation of a Semantic Web Ontology for Musical Instruments

Tidhar, D., Fazekas, G., Kolozali, S. and Sandler, M., (2009). Publishing music similarity features on the semantic web

Reports and Papers (1)

Farajidavar, N., Kolozali, S. and Barnaghi, P., (2017). A Deep Multi-View Learning Framework for City Event Extraction from Twitter Data Streams

Grants and funding

2019

AI-Assisted Decision-Making System for Cancer Pathways of the Colchester Hospital

East Suffolk and North Essex NHS Foundation Trust

A Remote Monitoring System for the Early Detection of Gestational Diabetes

University of Essex (GCRF)

Contact

sefki.kolozali@essex.ac.uk
+44 (0) 1206 872791

Location:

PARKSIDE UNIT C2, Colchester Campus

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