**Wenlian Lu**

Professor,

Centre for Computational Systems Biology, Fudan University

School of Mathematical Sciences, Fudan University

**Email:** wenlian@fudan.edu.cn

**Office Phone: **86-21-55665140

**Homepage:** N/A

**Background**

2005-2007 Max Planck Institute for Mathematics in the Sciences, Germany, Postdoc

2000-2005 Institute of Mathematics, Fudan University Ph.D. in Applied Mathematics

1996-2000 Department of Mathematics, Fudan University Diploma in Mathematics

**Awards**

2011 Asia Pacific Neural Network Assembly, Young Researcher Award

2008, Award for Science and Technology Advancement of Shanghai (Second Class).

2007, Award for National Excellent Doctoral Dissertation of PR China.

**Research Interests**

Computational neuroscience, Dynamical Systems in Complex Networks, Statistical

Inference on Neuroimage, Dynamical Systems.

Let us mention briefly three parts of Dr. Lu’s major research accomplishments. (A). Dr. Lu regarded the periodicity of neural networks as the limiting orbit and present simple mathematical approaches to treat the periodicity of neural network systems and conducted mathematical analysis on dynamical behaviours of neural networks with discontinuous activations. (B). By proposing a novel skew projection from the state space to the synchronization manifold, Dr. Lu unified the analyses of diverse sorts of coordination dynamics in network systems in diverse models into a mathematical framework. By this framework, he was able to bridge the theoretical gap among the statistical analysis of complex networks, graph theory and dynamical theory. In particular, he analyzed synchronization in networks with directed and even reducible graph topology and investigated the consensus and synchronization in networks with the general time-varying graph topologies, modelled by adapted processes, by combining the theories of dynamical system and stochastic analysis.(C). Neural network is one most of exciting models in artificial intelligence. The classic neural network model is the Wilson-Cowan-Amari (WCA) model built up based on the mean-field approach to describe firing rates or membrane potentials of neural population. Dr. Lu built up a DYNAMIC random model with depicting the random features of the experimental data of neurosciences and the capability to approximate the stochastic behaviours of network systems.

**Selected Papers**

1. W. Lu, T. Chen. “New approach to synchronization analysis of linearly coupled ordinary differential systems”, Physica D-Nonlinear Phenomena, 213 (2006) 214-230.

2. W. Lu, F. M. Atay, J. Jost. “Synchronization of discrete-time dynamical networks with time-varying couplings”, SIAM Journal on Mathematical Analysis, 39 (2007) 1231-1259.

3. W. Lu, T. Chen. “Almost periodic dynamics of a class of delayed neural networks with discontinuous activations”, Neural Computation, 20 (2008) 1065-1090.

4. W. Lu, E. Rossini, J. Feng. “On a Gaussian Random Field”, NeuroImage, 52 (2010) 913-933.

5. W. Lu, L. Wang, T. Chen. “On attracting basins of multiple equilibria of a class of cellular neural networks”. IEEE Transactions on Neural Networks, 22:3 (2011) 381–394.