Oliver Y. Chén, M.S., Sc.M., Ph.D. bio photo

Oliver Y. Chén, M.S., Sc.M., Ph.D.

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Papers

  • OY Chén, H. Cao, H. Phan, J. Reinen, J. Gou, J. Di, T. Qian, J. Prince, T. Cannon, and M. de Vos. Identifying neural signatures mediating behavioral symptoms and psychosis onset: High-dimensional whole brain functional mediation analysis. NeuroImage (2021) [Paper][Supp. Materials].

  • OY Chén and B. Roberts. Personalized healthcare and public health in the digital age. Frontiers in Digital Health (2021) [Paper] [Longer version].

  • OY Chén, H. Phan, G. Nagel, and M. de Vos. On Statistical Analysis of Brain Variability. Preprints 202008.0428.v1 (2020) [Paper].

  • OY Chén, R. Saraiva, G. Nagels, H. Phan, T. Schwantje, H. Cao, J. Gou, J. Reinen, B. Xiong, and M. de Vos. Thou shalt not reject the P-value. arXiv 2002.07270 (2020) [Paper].

  • OY Chén. The roles of statistics in human neuroscience. Brain Sci. 9, 194 (2019). I dedicate this paper to Michael Jacroux, who showed me the excitement of statistics, in honour of his emeritus retirement. [Paper] [Erratum].

  • OY Chén. Big data in omics and imaging: Integrated analysis and causal inference. The Journal of the American Statistical Association 115, 487-488 (2020) [Paper].

  • OY Chén, F. Lipsmeier, H. Phan, J. Prince, K.I. Taylor, M. Lindemann, C. Gossens, and M. de Vos. Building a machine-learning framework to remotely assess Parkinson’s disease using smartphones. IEEE Transactions on Biomedical Engineering (2020) [Paper].

  • OY Chén, H. Cao, J. Reinen, T. Qian, J. Gou, H. Phan, M. de Vos, and T. Cannon. Resting-state brain information flow predicts cognitive flexibility in humans. Scientific Reports 9, 3879 (2019) [Paper].

  • S. Zeki and OY Chén. The Bayesian-Laplacian brain. European Journal of Neuroscience 51, 1441-1462 (2019) [Paper].

  • OY Chén, E. Ogburn, C. Crainiceanu, B. Caffo, T. Wager, and M. Lindquist. High-dimensional multivariate mediation with application to neuroimaging data. Biostatistics 19, 121–136 (2015) [Paper] [Asymptotic Theory].

  • OY Chén, L. Xiao, B. Caffo, M. Lindquist, J. Schrack, L. Ferrucci, and C. Crainiceanu. A longitudinal functional data analysis for underlying daily physical activity change. (2015) [Paper].

  • OY Chén and M.A. Jacroux. On the use of semi-folding in regular blocks two-level factorial designs. Communications in Statistics - Theory and Methods 44, 2473-2506 (2015) [Paper].

  • OY Chén and J. Di. Penalised iterative sparse partial correlation estimation (Π-SPaCE) - with an application to whole-brain graph estimation. (2021+)

  • OY Chén, H. Phan, T. Qian, and M. de Vos. The causal effect of priming. (2021).

  • OY Chén. The generative representational similarity analysis. (2021+)

  • H. Cao, OY Chén, Y. Chung, S.C. McEwen, C.E. Bearden, J. Addington, B. Goodyear, K.S. Cadenhead, H. Mirzakhanian, B.A. Cornblatt, D.M. Olvet, D.H. Mathalon, T.H. McGlashan, D.O. Perkins, A. Belger, L.J. Seidman, H. Thermenos, M.T. Tsuang, T.G.M. van Erp, E.F. Walker, S. Hamann, A. Anticevic, S.W. Woods, and T.D. Cannon. Cerebello-thalamo-cortical hyperconnectivity: A state-independent functional neural signature for psychosis prediction and characterization. Nature Communications 9, 3836 (2018) [Paper][Supp. Materials].

  • J. Reinen, OY Chén, J. Baker, T. Yeo, K. Anderson, R. Hutchison, M. Sabuncu, D. Öngür, J. Roffman, J. Smoller, and A. Holmes. The human cerebral cortex possesses a reconfigurable dynamic network architecture that is disrupted in psychotic illness. Nature Communications 9, 1157 (2018) [Paper] [Supp. Materials].

  • H. Phan, OY Chén, P. Koch, A. Mertins, and M. de Vos. XSleepNet: Multi-view sequential model for automatic sleep staging. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) (2021) [Paper]

  • J. Gou and OY Chén. Critical boundary refinement in a group sequential trial when the primary endpoint data accumulate faster than the secondary endpoint. In ICSA Book Series in Statistics. Springer, Berlin, Germany (2018) [Chapter] [Book].

  • S. Zeki, OY Chén, and J. Romaya. The biological basis of mathematical beauty. Frontiers in Human Neuroscience 12, 467 (2018) [Paper].

  • H. Phan, OY Chén, P. Koch, L. Pham, I. McLoughlin, A. Mertins, and M. de Vos. Revisiting convolutional neural networks for automated sleep staging. EMBC (2020).

  • H. Phan, OY Chén, L. Pham, P. Koch, M. de Vos, I. McLoughlin, and A. Mertins. Spatial-temporal attention pooling for audio scene classification. Interspeech (2019) [Paper].

  • H. Phan, OY Chén, P. Koch, A. Mertins, and M. de Vos. Deep transfer learning for single-channel automatic sleep staging with channel mismatch. EUSIPCO (IEEE European Association for Signal Processing (2019) [Paper].

  • H. Phan, OY Chén, P. Koch, A. Mertins, and M. de Vos. Fusion of end-to-end deep learning models for sequence-to-sequence sleep staging. IEEE Engineering in Medicine and Biology Society (2019) [Paper].

  • H. Phan, OY Chén, P. Koch, L. Pham, I. McLoughlinz, A. Mertins, and M. de Vos. Unifying isolated and overlapping audio event detection with multi-label multi-task convolutional recurrent neural networks. In ICASSP 51-55 (2018) [Paper].

  • H. Cao H, OY Chén, S.C. McEwen, Y. Chung, C.E. Bearden, J. Addington, B. Goodyear, K.S. Cadenhead, H. Mirzakhanian, B.A. Cornblatt, D.M. Olvet, D.H. Mathalon, T.H. McGlashan, D.O. Perkins, A. Belger, L.J. Seidman, H. Thermenos, M.T. Tsuang, T.G.M. van Erp, E.F. Walker, S. Hamann, A. Anticevic, S.W. Woods, and T.D. Cannon. Altered brain activation during memory retrieval precedes and predicts conversion to psychosis in individuals at clinical high risk. Schizophrenia Bulletin 45, 924-933 (2018) [Paper].

  • H. Phan, OY Chén, P. Koch, L. Pham, I. McLoughlin, A. Mertins, and M. de Vos. Beyond equal-length snippets: How long is sufficient to recognize an audio scene? (2018) [Paper].

  • H. Phan, OY Chén, P. Koch, Z. Lu, I. McLoughlin, A. Mertins, and M. de Vos. Towards more accurate automatic sleep staging via deep transfer learning. IEEE Transactions on Biomedical Engineering (2019) [Paper].

  • H. Cao, OY Chén, S. McEwen, J. Forsyth, G. Dylan, C. Bearden, J. Addington, B. Goodyear, K. Cadenhead, H. Mirzakhanian, B. Cornblatt, R. Carrión, D. Mathalon, T. McGlashan, D. Perkins, A. Belger, H. Thermenos, M. Tsuang, T. van Erp, E. Walker, S. Hamann, A. Anticevic, S. Wood, and T.D. Cannon. Cross-paradigm connectivity: Reliabiltiy, stability, and utility. Brain Imaging and Behavior (2020).

  • H. Phan, OY Chén, F. Andreotti, N. Cooray, and M. de Vos. Towards better practice of deep learning for automatic sleep staging. IEEE (2018) [Paper].

  • H. Phan, K. Mikkelsen, OY Chén, P. Koch, A. Mertins, and M. de Vos. SleepTransformer: Automatic Sleep Staging with Interpretability and Uncertainty Quantification. arXiv 2105.11043 (2021) [Paper]

  • H. Phan, F. Andreotti, N. Cooray, OY Chén, and M. de Vos. SeqSleepNet: End-to-end hierarchical recurrent neural network for sequence-to-sequence automatic sleep staging. IEEE Transactions on Neural Systems and Rehabilitation Engineering 27, 400-410 (2018) [Paper] [Journal Cover].

  • H. Phan, F. Andreotti, N. Cooray, OY Chén, and M. de Vos. Joint classification and prediction CNN framework for automatic sleep stage classification. IEEE Transactions on Biomedical Engineering 66, 1285-1296 (2018) [Paper].

  • H. Phan, H. Nguyen, OY Chén, P. Koch, N. Duong, I. McLoughlin, and A. Mertins. Self-attention generative adversarial network for speech enhancement. ICASSP, (2021) [Paper].

  • H. Phan, H. Nguyen, OY Chén, P. Koch, N. Duong, I. McLoughlin, and A. Mertins. Multi-view Audio and Music Classification. ICASSP, (2021) [Paper].

  • H. Phan, K. Mikkelsen, OY Chén, P. Koch, A. Mertins, P. Kidmose, and M. de Vos. Personalized automatic sleep staging with single-night data: a pilot study with Kullback–Leibler divergence regularization. Physiological Measurements (2020).

  • H. Phan, F. Andreotti, N. Cooray, OY Chén, and M. de Vos. Automatic sleep stage classification using single-channel EEG: Learning sequential features with attention-based recurrent reural networks. In IEEE Engineering in Medicine and Biology Society (EMBC), 1452-1455 (2018). [Paper].

  • H. Phan, I. McLoughlin, L. Pham, OY Chén, P. Koch, M. de Vos, and A. Mertins. Improving GANs for speech enhancement. IEEE Signal Processing Letters (2020) [Paper]

  • H. Phan, F. Andreotti, N. Cooray, OY Chén, and M. de Vos. DNN filter bank improves 1-max pooling CNN for automatic sleep stage classification. IEEE Engineering in Medicine and Biology Society (EMBC), 453-456 (2018) [Paper].

  • OY Chén. A generalized and drifting time corrected approach using Wiener-Granger causality and VAR(p) process for detecting high-dimensional directed functional communication between brain regions and predicting behavior.

  • N. Dasgupta, OY Chén, R. Basu, and S.S. Daoud. Unsupervised learning methods to proteomic data from colon cancer. In Contemporary Topics in Mathematics and Statistics with Applications. New Delhi, India (2013) [Chapter].

  • N. Dasgupta, OY Chén, R. Basu, and S.S. Daoud. Comparison of clustering algorithms: An example with proteomic data. Advances and Applications in Statistics 33, 63 (2013) [Paper].

  • N. Dasgupta, OY Chén, R. Basu, and S.S. Daoud. Comparison of methods for unsupervised learning methods – an applied study using proteomic data from colon cancer and simulations. In CIAS, Indian Statistical Institute (2012).

Lectures

  • University of Warwick. Department of Statistics. March, 2021.

  • The Lausanne University Hospital. December, 2020.

  • University of Oxford. Big Data Institute. November, 2020.

  • ETH Zürich. Department of Health Sciences and Technology. November, 2020.

  • Queen Mary University of London. School of Electronic Engineering and Computer Science. November, 2020.

  • University College London. Department of Statistics. Nov 2020.

  • Imperial College London. Department of Epidemiology and Biostatistics. February, 2020.

  • University of Arkansas. Department Seminar. Department of Mathematical Sciences. October, 2020.

  • Vietnam National University. John von Neumann Institute. Ho Chi Minh City, Vietnam. December, 2018.

  • Roche Innovation Center. Basel, Switzerland. September, 2018.

  • University of Oxford. Mathematical Institute. Oxford, UK. February, 2018.

  • University of Oxford. Institute of Biomedical Engineering. Oxford, UK. February, 2018.

  • Yale University. Cognitive Neuroscience Laboratory. New Haven. CT. June, 2017.

  • Humboldt-Universität zu Berlin. Bernstein Center for Computational Neuroscience. Berlin, Germany. August, 2016.

  • Yale University. Department of Psychology. New Haven, CT. July, 2016.

  • He University and He Eye Hospital. Si-Shui Lecture. Shen-Yang, China. September, 2016.

  • Stanford University. Department of Psychology. Serra Mall, Stanford, CA. January, 2016.

  • University of Oxford. MRC Brain Network Dynamics Unit. Oxford, United Kingdom. December, 2015.

  • University of Cambridge. Engineering Department. Cambridge, United Kingdom. December, 2015.

  • The 8th International Conference of the ERCIM WG on Computational and Methodological Statistics, London, United Kingdom. December, 2015.

  • Spiegelman Student Finalist Speaker. The 142nd Annual Meeting and Exposition of the American Public Health Association, Chicago, IL. October, 2015.

  • ETH Zürich and University of Zürich. Institut für Neuroinformatik, Zürich, Switzerland, August, 2015.

  • Washington State University. Mathematics Colloquium. Department of Mathematics and Statistics. Pullman, WA. August, 2015.

Honors

  • Si-Shui Lecture.

  • Joseph Zeger Award.

  • Louis I. and Thomas D. Dublin Award for the Advancement of Epidemiology and Biostatistics.

  • Univeristy College London Visiting Lectureship.

  • Fritz Hoffmann-La Roche Award.

  • Statistical and Applied Mathematical Sciences Institute Award.

  • Award of Excellence for Outstanding Performance and Lasting Contributions as a Teaching Assistant.

  • First Place. Student Research Competition, the Applied Public Health Statistics Section, the American Public Health Association.