Nikolay Y. Nikolaev

Dr Nikolay Y. Nikolaev is lecturer in Computing Science at Goldsmiths, University of London, where he has taught courses in software engineering, language design, neural networks, artificial intelligence and the technology of thought.

Prior to this he was Assistant Professor of Computer Science at the American University in Bulgaria. He took his PhD in Artificial Intelligence, MSc in Computer Science and BSc in Computer Science at Sofia Technical University.



Nikolaev, N., and Iba, H. (2006). Adaptive Learning of Polynomial Networks: Genetic
Programming, Backpropagation and Bayesian Methods, Springer, New York

Nikolaev, N., and Iba, H. (2002). Genetic Programming of Polynomial Models for Financial Forecasting. In: Shu-Heng Chen (Ed.), Genetic Agorithms and Genetic Programming in Computational Finance, Chapter 5, Kluwer Academic Publ., Boston, MA, pp.103-123.

Journal papers

Mirikitani,D. and Nikolaev, N. (2011). Nonlinear Maximum Likelihood Estimation of Electricity Spot Prices using Recurrent Neural Networks, Neural Computing and Applications, vol.20, N:1, pp.79-89.

Mirikitani,D. and Nikolaev, N. (2010). Recursive Bayesian Recurrent Neural Networks for Time Series Modeling, IEEE Transactions on Neural Networks, vol.21, N:2, pp.262-274.

Mirikitani,D. and Nikolaev, N. (2010). Efficient Online Recurrent Connectionist Learning with the Ensemble Kalman Filter, Neurocomputing, vol.73, N:4-6, pp.1024-1030.

Nikolaev,N. and de Menezes, L. (2008). Sequential Bayesian Kernel Modelling with Non-Gaussian Noise, Neural Networks, vol.21. N:1, pp.36-47.

Conference papers

Nikolaev, N., Tino,P. and Smirnov, E.N. (2011). Time-Dependent Series Variance Estimation via Recurrent Neural Networks, In: T. Honkela et al (Eds.) Proc. Int. Conf. on Artificial Neural Networks, ICANN-2011, Espoo, Finland, LNCS-6971, Springer, pp.176-184.

Nikolaev, N., Mirikitani,D. and Smirnov, E.N. (2010). Unscented Grid Filtering and Elman Recurrent Networks, In: Proc. Int. Joint Conf. on Neural Networks IJCNN-2010, Barcelona, Spain, pp.1-7.

Nikolaev, N. and Smirnov, E. (2007). A One-Step Unscented Particle Filter for Nonlinear Dynamical Systems, In: Proc. Int. Conf. on Artificial Neural Networks, LNCS 4668, Springer, Berlin, pp.747-756.

Tino, P., Nikolaev, N. and Yao, X. (2005). Volatility Forecasting with Sparse Bayesian Kernel Models, In: Proc. 4th International Conference on Computational Intelligence in Economics and Finance, Salt Lake City, UT, pp.1150-1153.