Oliver Y. Chén bio photo

Oliver Y. Chén

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Reviews

  • Chén. The Roles of Statistics in Human Neuroscience. Brain Sci. 2019, 9, 194. Dedicated to Michael Jacroux in Honour of his Emeritus Retirement. [Paper]

  • Chén. The Rise of Big-data Statistical Science. Book review of Big Data in Omics and Imaging: Integrated Analysis and Causal Inference. The Journal of the American Statistical Association 2019.

  • Zeki and Chén. The Bayesian-Laplacian Brain. European Journal of Neuroscience 2019. [Paper]

Book chapters

  • Gou and 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]

  • Dasgupta, Chén, Basu, and Daoud. Unsupervised Learning Methods to Proteomic Data from Colon Cancer. In Contemporary Topics in Mathematics and Statistics with Applications. New Delhi, India, 2013. [Chapter]

Papers

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

  • Chén O. Y., Cao H., Phan H., Reinen J., Gou J., Di J., Qian T., Rrince J., Cannon T, and de Vos M. High-dimensional Whole Brain Mediation Analysis: methods and application in psychosis research.

  • Chén O. Y., Phan H., Qian T., and de Vos M. The Causal Effect of Priming.

  • Chén O. Y., Lipsmeier F., Phan H., Prince J., Taylor K. I., Lindemann M., Gossens C., and de Vos M. Building a Machine-learning Framework to Remotely Assess Parkinsons Disease Using Smartphones.

  • Cao H, Chén O. Y., Chung Y, McEwen SC, Bearden CE, Addington J, Goodyear B, Cadenhead KS, Mirzakhanian H, Cornblatt BA, Olvet DM, Mathalon DH, McGlashan TH, Perkins DO, Belger A, Seidman LJ, Thermenos H, Tsuang MT, van Erp TGM, Walker EF, Hamann S, Anticevic A, Woods SW, Cannon TD. Cerebello-thalamo-cortical hyperconnectivity: a state-independent functional neural signature for psychosis prediction and characterization. Nature Communications 2018, 9, 3836. [Paper] [Supp. Materials][News][Blog]

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

  • Chén and Jacroux. On the Use of Semi-folding in Regular Blocks Two-level Factorial Designs. Communications in Statistics - Theory and Methods 2015, 44, 2473-2506. [Paper]

  • Zeki, Chén, and Romaya. The Biological Basis of Mathematical Beauty. Frontiers in Human Neuroscience 2018, 12, 467. [Paper]

  • Chén O. Y., Ogburn E., Crainiceanu C., Caffo, B., Wager T., and Lindquist, M. High-dimensional Multivariate Mediation with Application to Neuroimaging Data. Biostatistics 2015, 19, 121–136 [Paper] [Asymptotic Theory]

  • Chén O. Y., Xiao L., Schrack J., Ferrucci L, and Crainiceanu C. A Longitudinal Functional Data Analysis for Underlying Daily Physical Activity Change. 2015. [Paper]

  • Phan, Chén, Koch, Lu, McLoughlin, Mertins, and de Vos. Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning. Under review.

  • Cao H., Chén O. Y., McEwen S., Forsyth J., Dylan G., Bearden C., Addington J., Goodyear B., Cadenhead K., Mirzakhanian H., Cornblatt B., Carrión R., Mathalon D., McGlashan T., Perkins D., Belger A., Thermenos H., Tsuang M., van Erp T., Walker E., Hamann S., Anticevic A., Wood S., Cannon T. Cross-paradigm connectivity: reliabiltiy, stability, and utility. Under review.

  • Phan, Andreotti, Cooray, Chén, and 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 2018, 27, 400-410. [Paper] [Journal Cover]

  • Phan, Andreotti, Cooray, Chén, and de Vos. Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification. IEEE Transactions on Biomedical Engineering 2018, 66, 1285-1296. [Paper]

  • Phan, Chén, Pham, Koch, de Vos, McLoughlin, and Mertins. Spatial-Temporal Attention Pooling for Audio Scene Classification. Interspeech 2019.

  • Phan, Chén, Koch, Mertins, and de Vos. Deep Transfer Learning for Single-Channel Automatic Sleep Staging with Channel Mismatch. EUSIPCO (IEEE European Association for Signal Processing, 2019.

  • Phan, Chén, Koch, Mertins, and de Vos. Fusion of End-to-End Deep Learning Models for Sequence-to-Sequence Sleep Staging. IEEE Engineering in Medicine and Biology Society 2019

  • Phan, Chén, Koch, Phamz, McLoughlinz, Mertins, and de Vos. Unifying Isolated and Overlapping Audio Event Detection with Multi-Label Multi-Task Convolutional Recurrent Neural Networks. In ICASSP 2018, 51-55. [Paper]

  • Phan, Chén, Koch, Pham, McLoughlin, Mertins, and de Vos. Beyond equal-length snippets: how long is sufficient to recognize an audio scene? 2018. [Paper]

  • Cao H, McEwen SC, Chung Y, Chén O. Y., Bearden CE, Addington J, Goodyear B, Cadenhead KS, Mirzakhanian H, Cornblatt BA, Olvet DM, Mathalon DH, McGlashan TH, Perkins DO, Belger A, Seidman LJ, Thermenos H, Tsuang MT, van Erp TGM, Walker EF, Hamann S, Anticevic A, Woods SW, Cannon TD. Altered brain activation during memory retrieval precedes and predicts conversion to psychosis in individuals at clinical high risk. Schizophrenia Bulletin 2018, 45, 924-933. [Paper]

  • Phan, Andreotti, Cooray, Chén, and de Vos. Automatic Sleep Stage Classification Using Single-Channel EEG: Learning Sequential Features with Attention-Based Recurrent Neural Networks. In IEEE Engineering in Medicine and Biology Society (EMBC). 2018, 1452-1455.

  • Phan, Andreotti, Cooray, Chén, and de Vos. DNN Filter Bank Improves 1-Max Pooling CNN for Automatic Sleep Stage Classification. IEEE Engineering in Medicine and Biology Society (EMBC). 2018, 453-456.

  • Phan, Andreotti, Cooray, Chén, and de Vos. Towards Better Practice of Deep Learning for Automatic Sleep Staging. IEEE. 2018.

  • Chén and Di. Penalised Iterative Sparse Partial Correlation Estimation (Π-SPaCE) - with an application to whole-brain graph estimation.

  • 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.

  • The Generative Representational Similarity Analysis. Gershman S., Chén O. Y., Konkle T. In preparation.

  • Dasgupta, N., Chén O. Y., Basu, R., and Daoud S.S. Comparison of Clustering Algorithms: an Example with Proteomic Data. Advances and Applications in Statistics 33 (1), 63. 2013.

  • Dasgupta, N., Chén O. Y., Basu, R., and Daoud S.S. Comparison of Methods for Unsupervised Learning Methods – an Applied Study using Proteomic Data from Colon Cancer and Simulations. 2012 Conference on Contemporary Issues and Applications of Statistics (CIAS 2012), Indian Statistical Institute. 2012.

Lectures and talks

I have made many errors and mistakes in research and in ways of thinking; I am very grateful to scholars from various of fields who have pointed out my shortcomings and helped me learn and grow.

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

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

  • Mathematical Institute, University of Oxford. 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

  • Bernstein Center for Computational Neuroscience. Berlin, Germany. August, 2016.

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

  • Si-Shui Lecture. He University and He Eye Hospital. 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 and awards

  • 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.

Unpublished Reviews, Essays, Handbooks, and Notes

  • Chén O. Y. Comments on Triplets of Spikes in a Model of Spike Timing-Dependent Plasticity (Pfister and Gerstner, 2006). [Link]

  • Chén O. Y. A Handbook to Conquer Casella and Berger Book in Ten Days. [Link]

  • Chén O. Y. A Brief Study Guide for Full, Blocking, and Fractional Factorial Experimental Designs. [Link]

  • Chén O. Y. Notes for Time Series Data Analysis. [Link]