Dr. Daniel Stamate has a PhD in Computer Science (University of Paris-Sud) and an MSc degree in Computer Science & Mathematics (University of Iasi). He currently leads the Data Science & Soft Computing Lab, and is the Director of the MSc Data Science programme at Goldsmiths, University of London.
Having previously worked in Statistical Databases, his present research focuses on Data Uncertainty Management, Sentiment Analysis & Stock Market Prediction, Scalable Machine Learning Approaches in Psychiatric Research – ongoing work in collaboration with Institute of Psychiatry at King’s College London, and Mobility Big Data Analytics – in particular analysing smart card data from Transport for London.
Publications
Sentiment and Stock Market Volatility Predictive Modelling – a Hybrid Approach.
Proceedings 2015 IEEE/ACM International Conference on Data Science and Advanced Analytics (DSAA’2015), with R. Olaniyan, D. Logofatu and L. Ouarbya
A Novel Statistical and Machine Learning Hybrid Approach to Predicting S&P 500 using Sentiment Analysis.
Proceedings of 8th International Conference of the ERCIM WG on Computational and Methodological Statistics, 2015, with Fionn Murtagh and Rapheal Olaniyan
Social Web-Based Anxiety Index’s Predictive Information on S&P 500, Revisited.
Proceedings of the 3rd International Symposium on Statistical Learning and Data Sciences (SLDS 2015), Springer LNAI, with R. Olaniyan and D. Logofatu
Scalable Distributed Genetic Algorithm for Data Ordering Problem with Inversion Using MapReduce.
Proceedings of the 10th International Conference on Artificial Intelligence Applications and Innovations (AIAI 2014),
Springer 2014 IFIP Advances in Information and Communication Technology, with D. Logofatu
Improving Time-Efficiency in Blocking Expanding Ring Search for Mobile Ad Hoc Networks.
Journal of Discrete Algorithms, Volume 24, 2014, with I. Pu and Y. Shen
Data Mining in Interdisciplinary Research.
Invited talk, International Conference on Interdisciplinary Approaches to the Study of Individual Differences in Learning, London, 2013
Quantitative Semantics for Uncertain Knowledge Bases.
Proceedings of the 14th International Conference on Information Processing and Management
of Uncertainty in Knowledge-Based Systems (IPMU 2012), Springer-Verlag (LNAI/CCIS series), 2012
Imperfect Information Fusion using Rules with Bilattice based Fixpoint Semantics.
Proceedings of the 14th International Conference on Information Processing and Management
of Uncertainty in Knowledge-Based Systems (IPMU 2012), Springer-Verlag (LNAI/CCIS series), 2012, with I. Pu
Fixpoint Semantics for Extended Logic Programs on Bilattice based Multivalued Logics, and Applications.
Proceedings of ManyVal 2012 Conference, 2012, with I. Pu
Queries with Multivalued Logic based Semantics for Imperfect Information Fusion.
Proceedings of the 40th IEEE International Symposium on Multiple-Valued Logics (IEEE ISMVL 10), 2010
A Bilattice based Fixed Point Semantics for Integrating Imperfect Information.
Proceedings of the 6th Workshop on Fixed Points in Computer Science (FICS 09), 2009
Default Reasoning with Imperfect Information in Multivalued Logics.
Proceedings of the 38th IEEE International Symposium on Multiple-Valued Logics (IEEE ISMVL 08), 2008
Imperfect Information Representation through Extended Logic Programs in Bilattices.
Book chapter. In Uncertainty and Intelligent Information Systems, B.Bouchon-Meunier, R.R. Yager, C. Marsala, and M. Rifqi (Eds.), World Scientific, ISBN 978-981-279-234-1, 2008
Reduction in Dimensions and Clustering using Risk and Return Model
Proceedings of the IEEE International Symposium on Data Mining and Information Retrieval
(IEEE DMIR07), 2007, with S.W. Qaiyumi
Representing Imperfect Information through Extended Logic Programs in Multivalued Logics.
Proceedings of the 11th biennial Conference on Information Processing and Management of Uncertainty in
Knowledge-Based Systems (IPMU 06), 2006
Assumption based Multiple-Valued Semantics for Extended Logic Programs.
Proceedings of the 36th IEEE International Symposium on Multiple-Valued Logics (IEEE ISMVL 06), 2006
Extended Deductive Databases with Uncertain Information.
Proceedings of the 7th International Conference on Enformatika Systems Sciences and Engineering, 2005
Hypothesis-based Semantics of Logic Programs in Multivalued Logics.
Journal – ACM Transactions on Computational Logic 15(3), pp. 508-527, 2004, with Y. Loyer and N. Spyratos
Parameterized Semantics for Logic Programs – a Unifying Framework.
Journal – Theoretical Computer Science 308(1-3), pp. 429-447, 2003, with Y. Loyer and N. Spyratos
Hypothesis Support for Information Integration in Four-Valued Logics.
Proceedings of IFIP International Conference on Theoretical Computer Science,
LNCS No. 1872 (Springer Verlag), pp. 536-548, 2000, with Y. Loyer and N. Spyratos
Interfacing Decision Support Systems under Incomplete Information.
International Journal Information Theories and Applications 7(1), pp. 38-48, 2000, with Y. Loyer and N.Spyratos
Integration of Information in Four-Valued Logics under Non-Uniform Assumptions.
Proceedings of the 30th IEEE International Symposium on Multiple-Valued Logics, pp. 185-191, 2000, with Y. Loyer and N. Spyratos
Hypotheses Based Semantics for Information Integration in Four-valued Logics.
Proceedings of the FICS2000 Workshop (Fixed Points in Computer Science), 2000, with Y. Loyer and N. Spyratos
Interfacing Decision Support Systems under Incomplete Information.
Proceedings of the 25th International Conference on Information and Communication Technologies
and Programming, 2000, pp. 21-31, with Y. Loyer and N. Spyratos
Computing and Comparing Semantics of Programs in Four-valued Logics.
Proceedings of the the 24th International Symposium on Mathematical Foundations of Comp. Science,
LNCS No. 1672 (Springer Verlag), pp. 59-69, 1999, with Y. Loyer and N. Spyratos
Deterministic Enforcement of Constraints.
Journal – Programming and Computer Software 24, pp. 71-83, 1998, with D. Laurent and N. Spyratos
Semantics and Containment of Queries with Internal and External conjunctions.
Proceedings of the 6th International Conference on Database Theory, LNCS No. 1186
(Springer Verlag), pp. 71-82, 1997, with G. Grahne and N. Spyratos
Multivalued Stable Semantics for Updating Databases with Uncertain Information.
Information Modelling and Knowledge Bases, VIII, IOS Press, pp. 129-144, 1997, with N. Spyratos
Semantics and Containment of Queries in Multimedia Information Systems.
Proceedings of the 2nd International Workshop on Multimedia Information Systems,
West Point, USA, pp. 82-87, 1997, with G. Grahne and N. Spyratos
A Class of Active Database Constraints.
Proceedings of the International Conference on Information Technology ’96, 1996,
with M. Halfeld Ferrari Alves, D. Laurent and N. Spyratos
Answer-Perturbation Techniques for the Protection of Statistical Databases.
Journal – Statistics and Computing 5, Springer, pp. 203-213, 1995, with H. Luchian
A General Model for the Answer-Perturbation Techniques.
Proceedings of the 7th International Working Conference on Scientific and Statistical Database
Management, pp. 90-96, 1994, with H. Luchian and B. Paechter
Statistical Protection for Statistical Databases.
Proceedings of the 6th International Working Conference on Scientific and Statistical Database
Management, Ascona, Switzerland, pp. 160-177, 1992, with H. Luchian
User-Oriented Approach for the Protection of Statistical Databases.
Scientific Annals of “Alexandru Ioan Cuza” University of Iasi, vol. 1 (Computer Science), pp. 41-55, 1992, with H. Luchian
Test d’Hypothèses pour l’Intégration d’Informations en Logique à Quatre Valeurs (In French)
Proceedings of JFPLC’2000 (Journées Francophones de Programmation Logique et Programmation
par Contraintes), Hermes, pp. 265-278, 2000, with Y. Loyer and N. Spyratos
Unification des Semantiques Usuelles de Programmes Logiques (In French)
Proceedings of JFPLC’98 (Journées Francophones de Programmation Logique et Programmation
par Contraintes), Hermes, pp. 135-150, 1998, with Y. Loyer and N. Spyratos
Bases de Données avec Informations Incertaines. Sémantique et Mises à Jour (In French)
Proceedings of JFPLC’96 (Journées Francophones de Programmation Logique et Programmation
par Contraintes), Hermes, pp. 49-63, 1996, with N. Spyratos
Theses
Applications of Multivalued Logics to Databases with Uncertain Information [In French: Applications des Logiques Multivaluées aux Bases de Données avec Informations Incertaines].
PhD Thesis in Computer Science, University of Paris-Sud, LRI (Laboratoire de Recherche en Informatique), 1999
A Branching Process Approach to Optimal Betting Strategies – Statistical Modeling and Computer Simulation Applications.
MSc Thesis in Computational Statistics, University of Iasi, Faculty of Mathematics, Computer Science Section
Data Science & Soft Computing Lab
– Our Lab organises the Data Science Talk Series at Goldsmiths, University of London
– The DSSC’s team designed the Data Science MSc Programme at Goldsmiths, University of London, launched 2014
– Summer school 23rd – 24th July 2015 : Prediction modelling and personalized medicine in psychiatric research using modern statistical methods, King’s College London
– The EVOLVE Conference, Iasi 2015:: Track: Evolving from Natural Computing and Data Mining
– The Congress of Romanian Mathematicians, 8th edition, Iasi 2015
Regular members
- Dr Daniel Stamate, DSSC Lab Leader, Goldsmiths
- Dr Ida Pu, Goldsmiths
- Prof Doina Logofatu, Frankfurt University of Applied Sciences
- Dr Mihaela Breaban, University of Iasi
- Dr Marc Atlan
- Dr Lahcen Ouarbya, Goldsmiths
Research and Masters students
- Wajdi Alghamdi, PhD candidate, Goldsmiths
- Rapheal Olaniyan, PhD candidate, Goldsmiths
- Michael Ng, Data Science MSc student, Goldsmiths
- Caroline Butler, Data Science MSc student, Goldsmiths
Undergraduate students
- James Dewar, Computer Science BSc, Goldsmiths
Research Themes
- Sentiment Analysis and Stock Market Trends Prediction
- Data Analytics and Applications
- Probability Distribution Forecasting and Applications in Wind Energy Forecasting and Risk Management
- Soft Computing and Algorithms
- Fuzzy Approaches to Imperfect Data Integration and Optimal Querying
- Scalable Machine Learning Applications in Mining Treated Depression Patients Data
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