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Dr Daniel Stamate

Staff details

PositionLecturer
Department Computing
Email d.stamate (@gold.ac.uk)
Phone+44 (0)20 7919 7864
Dr Daniel Stamate

Dr Daniel Stamate roles include:

Data Science MSc Programme Convener, Examinations Officer for Computing Department, Goldsmiths Information Management and Systems Committee member.

Areas of supervision

Soft computing and uncertainty modelling, data science, big data management and analytics, data mining and machine learning, computational statistics

 

Research Interests

I am interested in the following research areas where I tackle various themes strongly related to both Soft Computing and Data Science, in particular to: Uncertain Knowledge Bases and Databases with Imperfect Information (Imperfect Information Integration; Rule based Reasoning under Uncertainty, Incompleteness and Inconsistency in the context of Multivalued Logics; Query Optimisation for Efficient Imperfect Information Retrieval), Knowledge Discovery in Databases, Data Mining and Statistical Computing (Clustering/ Segmentation, Feature Selection, Classification Techniques, Statistical Techniques in Data Mining: Mixture Models and Probability Distribution Forecasting, and formerly in Statistical Databases). I am also interested in Algorithms and Complexity.

My interdisciplinary research interests concern various problems and applications particularly involving Data Science and related technologies. This work intertwines an academic expertise in Data Mining & Machine Learning, Statistical Modeling & Computational Statistics, Databases and Big Data Management and Analytics, and a practical and technical expertise in the major analytics technologies based on IBM SPSS Modeler & Statistics, SAS Enterprise Miner, R, RapidMiner, Weka, Hadoop and Big Data. Currently I have particular interests in bioinformatics and statistical data mining applications regarding knowledge and pattern discovery in classification, clustering and prediction problems involving genetic and phenotype data. Current interests concern also Digital and Statistical Research Methods in Social Sciences, Text and Web Mining in Sentiment Analysis, and Business Intelligence applications.

Current research

Publications

Book Section

Particle Swarm Optimization Algorithms for Autonomous Robots with Leaders Using Hilbert Curves
Logofatu, Doina; Sobol, Gil and Stamate, Daniel. 2017. Particle Swarm Optimization Algorithms for Autonomous Robots with Leaders Using Hilbert Curves. In: G. Boracchi; L. Iliadis; C. Jayne and A. Likas, eds. Engineering Applications of Neural Networks 18th International Conference, EANN 2017, Athens, Greece, August 25–27, 2017, Proceedings. 744 Cham: Springer International Publishing, pp. 535-543. ISBN 978-3-319-65172-9

A Prediction Modelling and Pattern Detection Approach for the First-Episode Psychosis Associated to Cannabis Use
Alghamdi, Wajdi; Stamate, Daniel; Vang, Katherine; Stahl, Daniel; Colizzi, Marco; Tripoli, Giada; Quattrone, Diego; Ajnakina, Olesya; Murray, Robin M. and Forti, Marta Di. 2016. A Prediction Modelling and Pattern Detection Approach for the First-Episode Psychosis Associated to Cannabis Use. In: , ed. 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA). Anaheim, CA, USA: IEEE, pp. 825-830. ISBN 978-1-5090-6167-9

Sentiment and stock market volatility predictive modelling - A hybrid approach
Olaniyan, Rapheal; Stamate, Daniel; Ouarbya, Lahcen and Logofatu, Doina. 2015. Sentiment and stock market volatility predictive modelling - A hybrid approach. In: Eric Gaussier; Longbing Cao; Patrick Gallinari; James Kwok; Gabriela Pasi and Osmar Zaiane, eds. Data Science and Advanced Analytics (DSAA), 2015. 36678 2015. IEEE International Conference on. Paris: IEEE, pp. 1-10. ISBN 978-1-4673-8272-4

Social Web-based Anxiety Index's Predictive Information on S&P 500 Revisited
Olaniyan, Rapheal; Stamate, Daniel and Logofatu, Doina. 2015. Social Web-based Anxiety Index's Predictive Information on S&P 500 Revisited. In: Alexander Gammerman; Vladimir Vovk and Harris Papadopoulos, eds. Statistical Learning and Data Sciences. 9047 Egham UK: Springer, pp. 203-213. ISBN 978-3-319-17090-9

Scalable Distributed Genetic Algorithm for Data Ordering Problem with Inversion Using MapReduce
Logofatu, Doina and Stamate, Daniel. 2014. Scalable Distributed Genetic Algorithm for Data Ordering Problem with Inversion Using MapReduce. In: Lazaros Iliadis; Ilias Maglogiannis and Harris Papadopoulos, eds. Artificial Intelligence Applications and Innovations. (436) Berlin Heidelberg: Springer, pp. 325-334. ISBN 978-3-662-44653-9

Imperfect Information Representation through Extended Logic Programs in Bilattices
Stamate, Daniel. 2008. Imperfect Information Representation through Extended Logic Programs in Bilattices. In: Bernadette Bouchon-Meunier; Christophe Marsala; Maria Rifqi and Ronald R Yager, eds. UNCERTAINTY AND INTELLIGENT INFORMATION SYSTEMS. London: World Scientific, pp. 419-432. ISBN 978-981-279-234-1

Article

Utilising symptom dimensions with diagnostic categories improves prediction of time to first remission in first-episode psychosis
Ajnakina, Olesya; Lally, John; Di Forti, Marta; Stilo, Simona; Kolliakou, Anna; Gardner-Sood, Poonam; Dazzan, Paola; Pariante, Carmine; Marques, Tiago Reiss; Mondelli, Valeria; MacCabe, James; Gaughran, Fiona; David, Anthony S; Stamate, Daniel; Murray, Robin and Fisher, Helen L.. 2017. Utilising symptom dimensions with diagnostic categories improves prediction of time to first remission in first-episode psychosis. Schizophrenia Research, ISSN 0920-9964

Improving time-efficiency in blocking expanding ring search for mobile ad hoc networks
Pu, Ida; Stamate, Daniel and Shen, Yuji. 2014. Improving time-efficiency in blocking expanding ring search for mobile ad hoc networks. Journal of Discrete Algorithms, 24, pp. 59-67. ISSN 1570-8667

Default Reasoning with Imperfect Information in Multivalued Logics
Stamate, Daniel. 2008. Default Reasoning with Imperfect Information in Multivalued Logics. 38th International Symposium on Multiple Valued Logic, n/a, pp. 163-168. ISSN 0195-623X

Hypothesis-based semantics of logic programs in multivalued logics
Stamate, Daniel; Loyer, Y. and Spyratos, N.. 2004. Hypothesis-based semantics of logic programs in multivalued logics. ACM Transactions on Computational Logic, 5(3), pp. 508-527. ISSN 15293785

Parametrized semantics of logic programs: a unifying framework
Stamate, Daniel; Loyer, Y. and Spyratos, N.. 2003. Parametrized semantics of logic programs: a unifying framework. Theoretical Computer Science, 308(1-3), pp. 429-447. ISSN 03043975

Conference or Workshop Item

A novel statistical and machine learning hybrid approach to predicting S&P500 using sentiment analysis
Murtagh, Fionn; Olaniyan, Rapheal and Stamate, Daniel. 2015. 'A novel statistical and machine learning hybrid approach to predicting S&P500 using sentiment analysis'. In: 8th International Conference of the ERCIM Working Group on Computational and Methodological Statistics. Senate House, University of London, United Kingdom.

Imperfect Information Fusion Using Rules with Bilattice Based Fixpoint Semantics
Stamate, Daniel and Pu, Ida. 2012. 'Imperfect Information Fusion Using Rules with Bilattice Based Fixpoint Semantics'. In: 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2012. Catania, Italy.

Queries with Multivalued Logic-Based Semantics for Imperfect Information Fusion
Stamate, Daniel. 2010. 'Queries with Multivalued Logic-Based Semantics for Imperfect Information Fusion'. In: 40th IEEE International Symposium on Multiple-Valued Logic (ISMVL '10). Barcelona, Spain 26-28 May 2010.

Reduction in Dimensions and Clustering using Risk and Return Model
Stamate, Daniel and Qaiyumi, S.. 2007. 'Reduction in Dimensions and Clustering using Risk and Return Model'. In: IEEE International Symposium on Data Mining and Information Retrieval (IEEE DMIR-07) in conjunction with the IEEE 21 International Conference on Advanced Information Networking and Applications (IEEE AINA-07), Niagara Falls, Canada. UNDEFINED 5/1/2007.

Assumption based Multi-Valued Semantics for Extended Logic Programs
Stamate, Daniel. 2006. 'Assumption based Multi-Valued Semantics for Extended Logic Programs'. In: 36th IEEE International Symposium on Multiple-Valued Logics (IEEE ISMVL 2006). UNDEFINED 5/1/2006.