Imperial College London

Dr Ovidiu Șerban

Faculty of EngineeringDepartment of Computing

Research Fellow in Intelligent Data Processing and Curation
 
 
 
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Contact

 

o.serban Website

 
 
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Location

 

DSI Main OfficeWilliam Penney LaboratorySouth Kensington Campus

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Summary

 

Summary

Ovidiu Șerban (ʃerban) is a Research Fellow at the Data Science Institute (DSI), Imperial College London. His current work includes real-time Natural Language Processing, Data Curation and Large Scale Visualisation Systems.

Ovidiu’s research topics are Natural Language Processing, Machine Learning, Affective Computing and Interactive System Design. He holds a joint PhD from INSA de Rouen Normandy (France) and “Babeș-Bolyai” University (Romania), while working at LITIS Laboratory in France.

In his youth, Ovidiu worked at the Institute for Security Science and Technology (ISST), Imperial College London; Computer Lab, University of Cambridge, UK and ISR Laboratory, University of Reading, UK.

Publications

Journals

Hilman D, Serban O, 2022, A unified Link Prediction architecture applied on a novel heterogenous Knowledge Base, Knowledge-based Systems, Vol:241, ISSN:0950-7051, Pages:1-17

Vaghela U, Rabinowicz S, Bratsos P, et al., 2021, Using a secure, continually updating, web source processing pipeline to support the real-time data synthesis and analysis of scientific literature: development and validation study, Journal of Medical Internet Research, Vol:23, ISSN:1438-8871, Pages:1-14

Fernando S, Amador Díaz López J, Şerban O, et al., 2020, Towards a large-scale twitter observatory for political events, Future Generation Computer Systems, Vol:110, ISSN:0167-739X, Pages:976-983

Fernando S, Scott-Brown J, Şerban O, et al., 2020, Open Visualization Environment (OVE): A web framework for scalable rendering of data visualizations, Future Generation Computer Systems, Vol:112, ISSN:0167-739X, Pages:785-799

Hankin CL, Serban O, Thapen N, et al., 2019, Real-time processing of social media with SENTINEL: a syndromic surveillance system incorporating deep learning for health classification, Information Processing and Management, Vol:56, ISSN:0306-4573, Pages:1166-1184

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