Publications

Preprints

(·)* denotes equal author contribution.

  1. Spike Sorting by Convolutional Dictionary Learning
    Andrew H. Song, Francisco Flores, and Demba Ba
    Arxiv, 2018 [link]

Journal & Conference

(·)* denotes equal author contribution.

  1. Integrating Context for Superior Cancer Prognosis
    Guillaume Jaume*, Andrew H. Song*, and Faisal Mahmood
    Nature Biomedical Engineering, 2022 [link]

  2. Investigating Morphologic Correlates of Driver Gene Mutation Heterogeneity via Deep Learning
    Andrew H. Song, Drew F.K. Williamson, and Faisal Mahmood
    Cancer Research, 2022 [link]

  3. Covariance-Free Sparse Bayesian Learning
    Alexander Lin, Andrew H. Song, Berkin Bilgic, and Demba Ba
    IEEE Transactions on Signal Processing, 2022 [link][arxiv]

  4. Incorporating intratumoral heterogeneity into weakly-supervised deep learning models via variance pooling
    Iain Carmichael*, Andrew H. Song*, Richard Chen, Drew F.K. Williamson, Tiffany Chen, and Faisal Mahmood
    International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022 [link]

  5. High-dimensional Sparse Bayesian Learning without Covariance Matrices
    Alexander Lin, Andrew H. Song, Berkin Bilgic, and Demba Ba
    IEEE ICASSP, 2022

  6. Mixture Model Auto-encoders: Deep Clustering through Dictionary Learning
    Alexander Lin, Andrew H. Song, and Demba Ba
    IEEE ICASSP, 2022 [link]

  7. Adaptive State-space Multitaper Spectral Estimation
    Andrew H. Song*, Seong-Eun Kim*, and Emery N. Brown
    IEEE Signal Processing Letters, 2022 [link][arxiv]

  8. Gaussian Process Convolutional Dictionary Learning
    Andrew H. Song, Bahareh Tolooshams, and Demba Ba
    IEEE Signal Processing Letters, 2022 [link][arxiv]

  9. PLSO: A generative framework for decomposing nonstationary timeseries into piecewise stationary oscillatory components
    Andrew H. Song, Demba Ba, and Emery N. Brown
    Uncertainty in Artificial Intelligence (UAI), 2021 [link]

  10. Convolutional dictionary learning based auto-encoders for natural exponential-family distributions
    Bahareh Tolooshams*, Andrew H. Song*, Simona Temereanca, and Demba Ba
    International Conference on Machine Learning (ICML), 2020 [link][slides]

  11. Convolutional dictionary learning with grid refinement
    Andrew H. Song, Francisco Flores, and Demba Ba
    IEEE Transactions on Signal Processing, 2020 [link]

  12. Channel-attention dense u-net for multichannel speech enhancement
    Bahareh Tolooshams, Ritwik Giri, Andrew H. Song, Umut Isik, and Arvindh Krishnaswamy
    IEEE ICASSP, 2020 [link]

  13. Multitaper Infinite Hidden Markov Model for EEG
    Andrew H Song*, Leon Chlon*, Hugo Soulat, John Tauber, Sandya Subramanian, Demba Ba, and Michael J Prerau
    IEEE EMBC, 2019 [link]

  14. A smoother state space multitaper spectrogram
    Andrew H. Song*, Sourish Chakravarty*, and Emery N. Brown
    IEEE EMBC, 2018 [link]

  15. Pharmacological Modulation of Noradrenergic Arousal Circuitry Disrupts Functional Connectivity of Locus Ceruleus in Humans
    Andrew H. Song, Aaron Kucyi, Vitaly Napadow, Emery N. Brown, Marco L. Loggia, and Oluwaseun Akeju
    Journal of Neuroscience, 2017 [link]

  16. GABAA circuit mechanisms are associated with ether anesthesia-induced unconsciousness
    Oluwaseun Akeju, Allison E. Hamilos, Andrew H. Song, Kara J. Pavone, Patrick L. Purdon, and Emery N. Brown
    Clinical Neurophysiology, 2016 [link]

  17. Electroencephalogram signatures of ketamine anesthesia-induced unconsciousness
    Oluwaseun Akeju, Andrew H. Song, Allison E. Hamilos, Kara J. Pavone, Francisco J. Flores, Emery N. Brown, and Patrick L. Purdon
    Clinical Neurophysiology, 2016 [link]

  18. Optical flow-switched transport layer protocol simulation and analysis
    Andrew H. Song, Henna Huang, Vincent Chan
    IEEE ICC, 2016 [link]

  19. Bring your own learner: A cloud-based, data-parallel commons for machine learning
    Ignacio Arnaldo, Kalyan Veeramachaneni, Andrew H. Song, Una-May O'Reilly
    IEEE Computational Intelligence Magazine, 2015 [link]

Workshop & Abstracts

  1. An efficient Gaussian process framework for analysis of oscillations in nonstationary time series
    Andrew H. Song, Demba Ba, and Emery N. Brown
    International Conference on Machine Learning (ICML) Time Series Workshop, 2021 [link]

  2. A statistical framework for extracting time-varying oscillations from neural data
    Andrew H. Song, Francisco J. Flores, Demba Ba, and Emery N. Brown
    COSYNE, 2021 [link]

  3. Convolutional dictionary learning of stimulus from spiking data
    Andrew H. Song*, Bahareh Tolooshams*, Simona Temereanca, and Demba Ba
    COSYNE, 2020 [link]

  4. Efficient robust spectral analysis of spike data
    Andrew H. Song, Patrick L. Purdon, Emery N. Brown, and Demba Ba
    SFN, 2019 [link]

Talks

  1. Generative models for neural time series with structured priors
    SNU Data science seminar, 2021

  2. Generative models for neural time series with structured priors
    Harvard DtAK lab meeting, 2021

  3. Neural signal processing with domain constraints
    KAIST AI symposium, 2020

  4. Neural signal processing with domain constraints
    KAIST EE seminar, 2020

  5. Neural signal processing with domain constraints
    SKKU M.IN.D lab, 2020