Professor Patrick Wolfe
Professor of Statistics
Honorary Professor of Computer Science
Royal Society Research Fellow
EPSRC Mathematical Sciences Research Fellow
Executive Director, UCL Big Data Institute
|Phone (external)||(+44 or 0) 207 679 1872|
|Themes||Multivariate and High Dimensional Data, Stochastic Modelling and Time Series|
Patrick J. Wolfe is Professor of Statistics and Honorary Professor of Computer Science at University College London, where he is a member of the Department's Senior Management Team and a Royal Society and EPSRC Established Career Research Fellow in the Mathematical Sciences.
From 2001-2004 he held a Fellowship and College Lectureship in Engineering and Computer Science at Cambridge University, where he completed his PhD in 2003 following a National Science Foundation Graduate Fellowship. Prior to joining UCL he was Assistant (2004-2008) and Associate (2008-2011) Professor at Harvard University, where he received the Presidential Early Career Award for Scientists and Engineers from the White House.
Professor Wolfe currently serves as Executive Director of the UCL Big Data Institute. Externally to UCL, he serves on the editorial board of the Proceedings of the Royal Society A (Mathematical, Physical & Engineering Sciences), the Research Section Committee of the Royal Statistical Society, the Program Committee of the 2015 Joint Statistical Meetings, and as an organizer of the 2016 Newton Institute program on Theoretical Foundations for Statistical Network Analysis.
The mathematics of Big Data. Modeling and inference for graphs and networks; statistical imaging and image processing;
time series and time-frequency analysis; audio signal processing and acoustic modeling.
- P. J. Wolfe and S. C. Olhede, "Nonparametric graphon estimation" (arXiv:1309.5936).
- S. C. Olhede and P. J. Wolfe, "Degree-based network models" (arXiv:1211.6537, revised June 2013).
- S. C. Olhede and P. J. Wolfe, "Order statistics of observed network degrees" (arXiv:1210.4377).
- P. O. Perry and P. J. Wolfe, "Null models for network data" (arXiv:1201.5871).
- S. C. Olhede and P. J. Wolfe, "Network histograms and universality of blockmodel approximation," Proceedings of the National Academy of Sciences of the USA, vol. 111, pp. 14722-14727, 2014 (arXiv:1312.5306). Code to compute the network histogram is available at https://github.com/p-wolfe/network-histogram-code.
- D. S. Choi and P. J. Wolfe, "Co-clustering separately exchangeable network data," Annals of Statistics, vol. 42, pp. 29-63, 2014 (arXiv:1212.4093).
- P. J. Wolfe, "Making sense of big data (commentary)," Proceedings of the National Academy of Sciences of the USA, vol. 110, pp. 18031-18032, 2013 (10.1073/PNAS.1317797110).
- P. O. Perry and P. J. Wolfe, "Point process modelling for directed interaction networks," Journal of the Royal Statistical Society, Series B, vol. 75, pp. 821-849, 2013 (arXiv:1011.1703).
- D. S. Choi, P. J. Wolfe, and E. O. Airoldi, "Stochastic blockmodels with growing number of classes," Biometrika, vol. 99, pp. 273-284, 2012 (arXiv:1011.4644).
- K. Hirakawa and P. J. Wolfe, "Skellam shrinkage: Wavelet-based intensity estimation for inhomogeneous Poisson data," IEEE Transactions on Information Theory, vol. 58, pp. 1080-1093, 2012 (arXiv:0905.3217).
- F. Luisier, T. Blu, and P. J. Wolfe, "A CURE for noisy magnetic resonance images: Chi-square unbiased risk estimation," IEEE Transactions on Image Processing, vol. 21, pp. 3454-3466, 2012 (arXiv:1106.2848).
- D. Mehta, D. Rudoy, and P. J. Wolfe, "Kalman-based autoregressive moving average modeling and inference for formant and antiformant tracking," Journal of the Acoustical Society of America, vol. 32, pp. 1732-1746, 2012 (arXiv:1107.0076).
- D. Rudoy, T. F. Quatieri, and P. J. Wolfe, "Time-varying autoregressions in speech: Detection theory and applications," IEEE Transactions on Audio, Speech, and Language Processing, vol. 19, pp. 977-989, 2011 (arXiv:0911.1697).
- D. Rudoy, S. G. Yuen, R. D. Howe, and P. J. Wolfe, "Bayesian changepoint analysis for atomic force microscopy and soft material indentation," Journal of the Royal Statistical Society, Series C, vol. 59, pp. 573-593, 2010 (arXiv:0909.5438).
- D. Rudoy, P. Basu, and P. J. Wolfe, "Superposition frames for adaptive time-frequency analysis and fast reconstruction," IEEE Transactions on Signal Processing, vol. 58, pp. 2581-2596, 2010 (arXiv:0906.5202).
- M.-A. Belabbas and P. J. Wolfe, "On landmark selection and sampling in high-dimensional data analysis," Philosophical Transactions of the Royal Society, Series A, vol. 367, pp. 4295-4312, 2009 (10.1098/RSTA.2009.0161).
- M.-A. Belabbas and P. J. Wolfe, "Spectral methods in machine learning and new strategies for very large datasets," Proceedings of the National Academy of Sciences of the USA, vol. 106, pp. 369-374, 2009 (10.1073/PNAS.0810600105).
- K. Hirakawa and P. J. Wolfe, "Spatio-spectral color filter array design for optimal image recovery," IEEE Transactions on Image Processing, vol. 17, pp. 1876-1890, 2008 (10.1109/TIP.2008.2002164).
Page last modified on 13 jan 15 11:08