Scholars@Duke

• Background
• 

  Education, Training, & Certifications

  • Ph.D., Technical University of Denmark (Denmark) 2011
• 

  Duke Appointment History

  • Assistant Research Professor in the Department of Electrical and Computer Engineering, Electrical and Computer Engineering, Pratt School of Engineering 2015 - 2017
• Recognition
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  In the News

  • MAR 16, 2016

    New Collaborative Seed Grant Program Gives Eight Awards
• Research
• 

  Selected Grants

  • Non-Invasive Diagnosis of Pediatric Pulmonary Invasive Mold Infections awarded by National Institutes of Health 2018 - 2023
  • Postdoctoral Training in Genomic Medicine Research awarded by National Institutes of Health 2017 - 2022
  • QuBBD: Deep Poisson Methods for Biomedical Time-to-Event and Longitudinal Data awarded by National Institutes of Health 2017 - 2020
  • Resilience Prediction to RSV Infection awarded by Sanofi US 2018 - 2019
  • Abbott Diagnostics Collaborative Sponsored Research Agreement awarded by Abbott Laboratories 2016 - 2019
  • Novel host-based diagnostics of febrile illness in the warfighter awarded by Department of Defense 2016 - 2019
  • Host-derived biomarker signatures to differentiate acute viral, bacterial, and fungal infection awarded by National Institutes of Health 2017 - 2019
  • PREdicting contagion using Systems And GEnomic analysis (PRESAGE) awarded by Defense Advanced Research Projects Agency 2017 - 2019
  • Role of the Stroma in Fibrolamellar Hepatocellular Carcinoma awarded by Fibrolamellar Cancer Foundation 2016 - 2019
  • Development and Application of Mathematical Methods for Tracking Biochronicity and Baseline Variation awarded by Defense Advanced Research Projects Agency 2016 - 2019
  • Deep learning driven angiographic analysis to enhance evaluation of coronary artery stenosis awarded by Vigilant Medical 2018 - 2019
  • CTOT Ancillary Studies Fund Carry Forward BAL awarded by Mount Sinai School of Medicine 2016 - 2017
  • Hyaluronan in Acute Rejection and Chronic Lung Allograft Dysfunction after Human Lung Transplantation awarded by Mount Sinai School of Medicine 2016 - 2017
  • HARDAC+:Reproducible HPC for next-generation genomics awarded by North Carolina Biotechnology Center 2016 - 2017
  • Feasibility for Predicting Warfighter Health Using Transcriptional Markers on the MAP Platform awarded by Ibis Biosciences, Inc. 2016
• Publications & Artistic Works
• 

  Selected Publications

  • Academic Articles

    • Fourati, Slim, et al. “A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection..” Nature Communications, vol. 9, no. 1, Oct. 2018. Epmc, doi:10.1038/s41467-018-06735-8.
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    • Bradley, Todd, et al. “RAB11FIP5 Expression and Altered Natural Killer Cell Function Are Associated with Induction of HIV Broadly Neutralizing Antibody Responses..” Cell, vol. 175, no. 2, Oct. 2018, pp. 387-399.e17. Epmc, doi:10.1016/j.cell.2018.08.064.
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    • Sweeney, Timothy E., et al. “Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters..” Critical Care Medicine, vol. 46, no. 6, June 2018, pp. 915–25. Epmc, doi:10.1097/ccm.0000000000003084.
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    • Sweeney, Timothy E., et al. “A community approach to mortality prediction in sepsis via gene expression analysis..” Nat Commun, vol. 9, no. 1, Feb. 2018. Pubmed, doi:10.1038/s41467-018-03078-2.
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    • Pu, Y., et al. “JointGAN: Multi-domain joint distribution learning with generative adversarial nets.” 35th International Conference on Machine Learning, Icml 2018, vol. 9, Jan. 2018, pp. 6626–35.
    • Shen, D., et al. “Deconvolutional latent-variable model for text sequence matching.” 32nd Aaai Conference on Artificial Intelligence, Aaai 2018, Jan. 2018, pp. 5438–45.
    • Shen, D., et al. “NasH: Toward end-to-end neural architecture for generative semantic hashing.” Acl 2018  56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers), vol. 1, Jan. 2018, pp. 2041–50.
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    • Wegermann, Kara, et al. “Branched chain amino acid transaminase 1 (BCAT1) is overexpressed and hypomethylated in patients with non-alcoholic fatty liver disease who experience adverse clinical events: A pilot study..” Plos One, vol. 13, no. 9, Jan. 2018. Epmc, doi:10.1371/journal.pone.0204308.
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    • Zhang, Xinyuan, et al. “Multi-Label Learning from Medical Plain Text with Convolutional Residual Models..” Corr, vol. abs/1801.05062, 2018.
    • Hald, Ditte Høvenhoff, et al. “Gaussian process based independent analysis for temporal source separation in fMRI..” Neuroimage, vol. 152, May 2017, pp. 563–74. Epmc, doi:10.1016/j.neuroimage.2017.02.070.
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    • Patel, Yuval A., et al. “Reply to Kim et al..” The American Journal of Gastroenterology, vol. 112, no. 5, May 2017, pp. 807–08. Epmc, doi:10.1038/ajg.2017.45.
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    • Burke, Thomas W., et al. “Nasopharyngeal Protein Biomarkers of Acute Respiratory Virus Infection..” Ebiomedicine, vol. 17, Mar. 2017, pp. 172–81. Epmc, doi:10.1016/j.ebiom.2017.02.015.
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    • Li, Chunyuan, et al. “Towards Understanding Adversarial Learning for Joint Distribution Matching..” Corr, vol. abs/1709.01215, 2017.
    • Pu, Y., et al. “Adversarial symmetric variational autoencoder.” Advances in Neural Information Processing Systems, vol. 2017-December, Jan. 2017, pp. 4331–40.
    • Pu, Yunchen, et al. “Stein Variational Autoencoder..” Corr, vol. abs/1704.05155, 2017.
    • Zhang, Y., et al. “Adversarial feature matching for text generation.” 34th International Conference on Machine Learning, Icml 2017, vol. 8, Jan. 2017, pp. 6093–102.
    • Zhang, Y., et al. “Deconvolutional paragraph representation learning.” Advances in Neural Information Processing Systems, vol. 2017-December, Jan. 2017, pp. 4170–80.
    • Zhang, Y., et al. “Stochastic gradient monomial gamma sampler.” 34th International Conference on Machine Learning, Icml 2017, vol. 8, Jan. 2017, pp. 6083–92.
    • Patel, Yuval A., et al. “Vitamin D is Not Associated With Severity in NAFLD: Results of a Paired Clinical and Gene Expression Profile Analysis..” The American Journal of Gastroenterology, vol. 111, no. 11, Nov. 2016, pp. 1591–98. Epmc, doi:10.1038/ajg.2016.406.
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    • Henao, R., et al. “Electronic health record analysis via deep poisson factor models.” Journal of Machine Learning Research, vol. 17, Apr. 2016.
    • McClain, M. T., et al. “Differential evolution of peripheral cytokine levels in symptomatic and asymptomatic responses to experimental influenza virus challenge..” Clinical and Experimental Immunology, vol. 183, no. 3, Mar. 2016, pp. 441–51. Epmc, doi:10.1111/cei.12736.
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    • Gan, Zhe, et al. “Unsupervised Learning of Sentence Representations using Convolutional Neural Networks..” Corr, vol. abs/1611.07897, 2016.
    • Tsalik, Ephraim L., et al. “Host gene expression classifiers diagnose acute respiratory illness etiology..” Science Translational Medicine, vol. 8, no. 322, Jan. 2016. Epmc, doi:10.1126/scitranslmed.aad6873.
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    • Zhang, Y., et al. “Learning a hybrid architecture for sequence regression and annotation.” 30th Aaai Conference on Artificial Intelligence, Aaai 2016, Jan. 2016, pp. 1415–21.
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    • Gan, Z., et al. “Deep temporal sigmoid belief networks for sequence modeling.” Advances in Neural Information Processing Systems, vol. 2015-January, Jan. 2015, pp. 2467–75.
    • Vikeså, Jonas, et al. “Cancers of unknown primary origin (CUP) are characterized by chromosomal instability (CIN) compared to metastasis of know origin..” Bmc Cancer, vol. 15, Jan. 2015. Epmc, doi:10.1186/s12885-015-1128-x.
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    • Yuan, X., et al. “Non-Gaussian discriminative factor models via the max-margin rank-likelihood.” 32nd International Conference on Machine Learning, Icml 2015, vol. 2, Jan. 2015, pp. 1254–63.
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    • Tsalik, Ephraim L., et al. “An integrated transcriptome and expressed variant analysis of sepsis survival and death..” Genome Medicine, vol. 6, no. 11, Jan. 2014. Epmc, doi:10.1186/s13073-014-0111-5.
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    • Benjamin, Ashlee M., et al. “A flexible statistical model for alignment of label-free proteomics data--incorporating ion mobility and product ion information..” Bmc Bioinformatics, vol. 14, Dec. 2013. Epmc, doi:10.1186/1471-2105-14-364.
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    • Henao, R., et al. “Latent protein trees.” Annals of Applied Statistics, vol. 7, no. 2, June 2013, pp. 691–713. Scopus, doi:10.1214/13-AOAS639.
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    • Kurokawa, Manabu, et al. “A network of substrates of the E3 ubiquitin ligases MDM2 and HUWE1 control apoptosis independently of p53..” Sci Signal, vol. 6, no. 274, May 2013. Pubmed, doi:10.1126/scisignal.2003741.
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    • Henao, Ricardo, et al. “Patient clustering with uncoded text in electronic medical records..” Amia ... Annual Symposium Proceedings. Amia Symposium, vol. 2013, Jan. 2013, pp. 592–99.
    • Henao, R., et al. “Hierarchical factor modeling of proteomics data.” 2012 Ieee 2nd International Conference on Computational Advances in Bio and Medical Sciences, Iccabs 2012, May 2012. Scopus, doi:10.1109/ICCABS.2012.6182638.
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    • Henao, R., and O. Winther. “Predictive active set selection methods for Gaussian processes.” Neurocomputing, vol. 80, Mar. 2012, pp. 10–18. Scopus, doi:10.1016/j.neucom.2011.09.017.
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    • Rossing, Maria, et al. “Down-regulation of microRNAs controlling tumourigenic factors in follicular thyroid carcinoma..” Journal of Molecular Endocrinology, vol. 48, no. 1, Feb. 2012, pp. 11–23. Epmc, doi:10.1530/jme-11-0039.
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    • Carin, Lawrence, et al. “High-Dimensional Longitudinal Genomic Data: An analysis used for monitoring viral infections..” Ieee Signal Processing Magazine, vol. 29, no. 1, Jan. 2012, pp. 108–23. Epmc, doi:10.1109/MSP.2011.943009.
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    • Friis, Morten, et al. “Gene expression of the endolymphatic sac..” Acta Oto Laryngologica, vol. 131, no. 12, Dec. 2011, pp. 1257–63. Epmc, doi:10.3109/00016489.2011.616910.
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    • Henao, R., and O. Winther. “Sparse linear identifiable multivariate modeling.” Journal of Machine Learning Research, vol. 12, Mar. 2011, pp. 863–905.
    • Henao, R., and O. Winther. “PASS-GP: Predictive active set selection for Gaussian processes.” Proceedings of the 2010 Ieee International Workshop on Machine Learning for Signal Processing, Mlsp 2010, Nov. 2010, pp. 148–53. Scopus, doi:10.1109/MLSP.2010.5589264.
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    • Borup, Rehannah, et al. “Molecular signatures of thyroid follicular neoplasia..” Endocrine Related Cancer, vol. 17, no. 3, Sept. 2010, pp. 691–708. Epmc, doi:10.1677/erc-09-0288.
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    • Walder, Christian, et al. “Semi-Supervised Kernel PCA.” Corr, vol. abs/1008.1398, 2010.
    • Alvarez López, M. A., et al. “Myocardial ischemia detection using Hidden Markov principal component analysis.” Ifmbe Proceedings, vol. 18, Jan. 2008, pp. 99–103. Scopus, doi:10.1007/978-3-540-74471-9_24.
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    • Alvarez, M., et al. “Kernel Principal Component analysis through time for voice disorder classification..” Conference Proceedings : ... Annual International Conference of the Ieee Engineering in Medicine and Biology Society. Ieee Engineering in Medicine and Biology Society. Conference, 2006, pp. 5511–14.
    • Alvarez, Mauricio, et al. “Kernel Principal Component analysis through time for voice disorder classification..” Conference Proceedings : ... Annual International Conference of the Ieee Engineering in Medicine and Biology Society. Ieee Engineering in Medicine and Biology Society. Annual Conference, vol. 1, Jan. 2006, pp. 5511–14. Epmc, doi:10.1109/iembs.2006.260357.
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    • Henao, Ricardo, and Joseph E. Lucas. Efficient hierarchical clustering for continuous data.
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  • Book Sections

    • Gan, Zhe, et al. “Inference of gene networks associated with the host response to infectious disease..” Big Data over Networks, edited by Shuguang Cui et al., Cambridge University Press, 2016, pp. 365–90.

  • Conference Papers

    • Fan, K., et al. “Triply stochastic variational inference for non-linear beta process factor analysis.” Proceedings  Ieee International Conference on Data Mining, Icdm, 2017, pp. 121–30. Scopus, doi:10.1109/ICDM.2016.36.
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    • Zhang, Y., et al. “Dynamic poisson factor analysis.” Proceedings  Ieee International Conference on Data Mining, Icdm, 2017, pp. 1359–64. Scopus, doi:10.1109/ICDM.2016.111.
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    • Gan, Zhe, et al. “Learning Generic Sentence Representations Using Convolutional Neural Networks..” Emnlp, edited by Martha Palmer et al., Association for Computational Linguistics, 2017, pp. 2390–400.
    • Komives, Eugenie, et al. “Guiding Principles for the Duke Connected Care Predictive Modeling Pilot..” Amia, AMIA, 2017.
    • Li, C., et al. “ALICE: Towards understanding adversarial learning for joint distribution matching.” Advances in Neural Information Processing Systems, vol. 2017-December, 2017, pp. 5496–504.
    • Li, Chunyuan, et al. “ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching..” Nips, edited by Isabelle Guyon et al., 2017, pp. 5501–09.
    • Pu, Y., et al. “VAE learning via Stein variational gradient descent.” Advances in Neural Information Processing Systems, vol. 2017-December, 2017, pp. 4237–46.
    • Pu, Yunchen, et al. “VAE Learning via Stein Variational Gradient Descent..” Nips, edited by Isabelle Guyon et al., 2017, pp. 4239–48.
    • Pu, Yunchen, et al. “Adversarial Symmetric Variational Autoencoder..” Nips, edited by Isabelle Guyon et al., 2017, pp. 4333–42.
    • Rusincovitch, Shelley A., et al. “Rationale and Design for the Duke Connected Care Predictive Modeling Pilot with a Medicare Shared Savings Program Population..” Amia, AMIA, 2017.
    • Zhang, Yizhe, et al. “Stochastic Gradient Monomial Gamma Sampler..” Icml, edited by Doina Precup and Yee Whye Teh, vol. 70, PMLR, 2017, pp. 3996–4005.
    • Zhang, Yizhe, et al. “Adversarial Feature Matching for Text Generation..” Icml, edited by Doina Precup and Yee Whye Teh, vol. 70, PMLR, 2017, pp. 4006–15.
    • Zhang, Yizhe, et al. “Deconvolutional Paragraph Representation Learning..” Nips, edited by Isabelle Guyon et al., 2017, pp. 4172–82.
    • Patel, Yuval A., et al. “Vitamin D is Not Associated with Histologic Severity in NAFLD: Results of a Paired Clinical and Hepatic Gene Expression Profile Analysis.” Hepatology, vol. 64, WILEY, 2016, pp. 577A-577A.
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    • Wegermann, Kara, et al. “BCAT1 is Associated with Clinical Decompensation in NAFLD: A Pilot Study.” Hepatology, vol. 64, WILEY, 2016, pp. 577A-577A.
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    • Pu, Y., et al. “Variational autoencoder for deep learning of images, labels and captions.” Advances in Neural Information Processing Systems, 2016, pp. 2360–68.
    • Pu, Yunchen, et al. “Variational Autoencoder for Deep Learning of Images, Labels and Captions..” Nips, edited by Daniel D. Lee et al., 2016, pp. 2352–60.
    • Song, Zhao, et al. “Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization..” Aistats, edited by Arthur Gretton and Christian C. Robert, vol. 51, JMLR.org, 2016, pp. 1347–55.
    • Yizhe, Z., et al. “Bayesian dictionary learning with Gaussian processes and sigmoid belief networks.” Ijcai International Joint Conference on Artificial Intelligence, vol. 2016-January, 2016, pp. 2364–70.
    • Zhang, Y., et al. “Laplacian Hamiltonian Monte Carlo.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9851 LNAI, 2016, pp. 98–114. Scopus, doi:10.1007/978-3-319-46128-1_7.
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    • Zhang, Y., et al. “Towards unifying hamiltonian Monte Carlo and Slice sampling.” Advances in Neural Information Processing Systems, 2016, pp. 1749–57.
    • Zhang, Yizhe, et al. “Towards Unifying Hamiltonian Monte Carlo and Slice Sampling..” Nips, edited by Daniel D. Lee et al., 2016, pp. 1741–49.
    • Henao, Ricardo, et al. “Plasma Metabolomic Profiles Predict Advanced Hepatic Fibrosis in Patients with Nonalcoholic Fatty Liver Disease.” Hepatology, vol. 62, WILEY-BLACKWELL, 2015, pp. 290A-291A.
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    • Gan, Z., et al. “Learning deep sigmoid belief networks with data augmentation.” Journal of Machine Learning Research, vol. 38, 2015, pp. 268–76.
    • Gan, Z., et al. “Scalable deep Poisson factor analysis for topic modeling.” 32nd International Conference on Machine Learning, Icml 2015, vol. 3, 2015, pp. 1823–32.
    • Gan, Zhe, et al. “Deep Temporal Sigmoid Belief Networks for Sequence Modeling..” Nips, edited by Corinna Cortes et al., 2015, pp. 2467–75.
    • Henao, R., et al. “Deep poisson factor modeling.” Advances in Neural Information Processing Systems, vol. 2015-January, 2015, pp. 2800–08.
    • Lian, W., et al. “A multitask point process predictive model.” 32nd International Conference on Machine Learning, Icml 2015, vol. 3, 2015, pp. 2030–38.
    • Raiy, P., et al. “Large-scale Bayesian multi-label learning via topic-based label embeddings.” Advances in Neural Information Processing Systems, vol. 2015-January, 2015, pp. 3222–30.
    • Henao, R., et al. “Bayesian nonlinear support vector machines and discriminative factor modeling.” Advances in Neural Information Processing Systems, vol. 2, no. January, 2014, pp. 1754–62.
    • Ouinones, Quintin J., et al. “Proteomnic and Metabolomic Profiling After Isehemia-Reperfusion Injury Reveals Bottlenecks That Underlie Cardioprotection in Hibernating Mammals.” Circulation, vol. 128, no. 22, LIPPINCOTT WILLIAMS & WILKINS, 2013.
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    • Henao, R., and O. Winther. “Bayesian sparse factor models and DAGs inference and comparison.” Advances in Neural Information Processing Systems 22  Proceedings of the 2009 Conference, 2009, pp. 736–44.
    • Alvarez, M., and R. Henao. “Probabilistic kernel principal component analysis through time.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4232 LNCS, 2006, pp. 747–54.
    • Alvarez, Mauricio, et al. “Kernel principal component analysis through time for voice disorder classification.” 2006 28th Annual International Conference of the Ieee Engineering in Medicine and Biology Society, Vols 1 15, IEEE, 2006, pp. 2620-+.
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    • Rengifo, Carlos Lino, et al. “Active learning on the classification of voice pathologies..” Odyssey, edited by Javier Ortega-Garcia et al., ISCA, 2004, pp. 271–74.
• Teaching & Mentoring
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  Recent Courses

  • COMPSCI 394: Research Independent Study 2019
  • ECE 899: Special Readings in Electrical Engineering 2017
• Scholarly, Clinical, & Service Activities
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  Outreach & Engaged Scholarship

  • Bass Connections Faculty Team Member. Data+. June 2016 - July 2016  2016

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