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Edited Volume

  1. Guide to mobile data analytics in refugee scenarios: The 'Data for Refugees Challenge' study [Link]
    A. A. Salah, A. Pentland, B. Lepri, E. Letouzé, Y.-A. de Montjoye, X. Dong and P. Vinck (Eds.), Springer, 2019.

Book Chapter

  1. Graph learning [Link]
    X. Dong, D. Thanou, M. Rabbat and P. Frossard
    Graph spectral image processing, G. Cheung and E. Magli (Eds.), ISTE, 2021, pp. 31-62.

  2. The rippling effect of social influence via phone communication network [Link]
    Y. Leng, X. Dong, E. Moro and A. Pentland
    Complex spreading phenomena in social systems, S. Lehmann and Y.-Y. Ahn (Eds.), Springer, 2018, pp. 323-333.

Journal Paper

  1. Maximum entropy approach to massive graph spectrum learning with applications [PDF]
    D. Granziol*, B. Ru*, X. Dong, S. Zohren, M. A. Osborne and S. Roberts (*equal contribution)
    Algorithms, Special Issue on Extreme Algorithmics: Analysis of Huge, Noisy, and Dynamic Networked Data, vol. 15, no. 6, article no. 209, June 2022.

  2. Interaction data are identifiable even across long periods of time [PDF]
    A.-M. Cretu, F. Monti, S. Marrone, X. Dong, M. M. Bronstein and Y.-A. de Montjoye
    Nature Communications, vol. 13, article no. 313, January 2022.

  3. Mobility patterns are associated with experienced income segregation in large US cities [PDF]
    E. Moro, D. Calacci, X. Dong and A. Pentland
    Nature Communications, vol. 12, article no. 4633, July 2021.

  4. Bayesian topology learning and noise removal from network data [PDF]
    M. R. Mayiami, M. Hajimirsadeghi, K. Skretting, X. Dong, R. S. Blum and H. V. Poor
    Discover Internet of Things, vol. 1, article no. 11, March 2021.

  5. Kernel-based graph learning from smooth signals: A functional viewpoint [PDF]
    X. Pu, S. L. Chau, X. Dong and D. Sejdinovic
    IEEE Transactions on Signal and Information Processing over Networks, vol. 7, pp. 192-207, February 2021.

  6. Sentiment correlation in financial news networks and associated market movements [PDF]
    X. Wan*, J. Yang*, S. Marinov, J.-P. Calliess, S. Zohren and X. Dong (*equal contribution)
    Scientific Reports, vol. 11, article no. 3062, February 2021.

  7. Graph signal processing for machine learning: A review and new perspectives [PDF] [Extended version]
    X. Dong*, D. Thanou*, L. Toni, M. Bronstein and P. Frossard (*equal contribution)
    IEEE Signal Processing Magazine, vol. 37, no. 6, pp. 117-127, November 2020.

  8. Segregated interactions in urban and online space [PDF]
    X. Dong, A. J. Morales, E. Jahani, E. Moro, B. Lepri, B. Bozkaya, C. Sarraute, Y. Bar-Yam and A. Pentland
    EPJ Data Science, vol. 9, article no. 20, July 2020.

  9. Purchase patterns, socioeconomic status, and political inclination [PDF]
    X. Dong, E. Jahani, A. J. Morales, B. Bozkaya, B. Lepri and A. Pentland
    The World Bank Economic Review, vol. 34, issue supplement_1, pp. S9-S13, February 2020.

  10. Segregation and polarization in urban areas [PDF]
    A. J. Morales, X Dong, Y. Bar-Yam and A. Pentland
    Royal Society Open Science, vol. 6, no. 10, article ID 190573, October 2019.

  11. MEMe: An accurate maximum entropy method for efficient approximations in large-scale machine learning [PDF]
    D. Granziol*, B. Ru*, S. Zohren, X. Dong, M. A. Osborne and S. Roberts (*equal contribution)
    Entropy, Special Issue on Entropy Based Inference and Optimization in Machine Learning, vol. 21, no. 6, article no. 551, May 2019.

  12. Learning graphs from data: A signal representation perspective [PDF] [Errata]
    X. Dong*, D. Thanou*, M. Rabbat and P. Frossard (*equal contribution)
    IEEE Signal Processing Magazine, vol. 36, no. 3, pp. 44-63, May 2019.

  13. Behavioral attributes and financial churn prediction [PDF]
    E. Kaya, X. Dong, Y. Suhara, S. Balcisoy, B. Bozkaya and A. Pentland
    EPJ Data Science, vol. 7, article no. 41, October 2018.

  14. Methods for quantifying effects of social unrest using credit card transaction data [PDF]
    X. Dong, J. Meyer, E. Shmueli, B. Bozkaya and A. Pentland
    EPJ Data Science, vol. 7, article no. 8, April 2018.

  15. Social bridges in urban purchase behavior [PDF]
    X. Dong*, Y. Suhara*, B. Bozkaya, V. K. Singh, B. Lepri and A. Pentland (*equal contribution)
    ACM Transactions on Intelligent Systems and Technology, Special Issue on Urban Intelligence, vol. 9, no. 3, article no. 33, February 2018.

  16. Learning heat diffusion graphs [PDF]
    D. Thanou, X. Dong, D. Kressner and P. Frossard
    IEEE Transactions on Signal and Information Processing over Networks, Special Issue on Graph Signal Processing, vol. 3, no. 3, pp. 484-499, September 2017.

  17. Learning Laplacian matrix in smooth graph signal representations [PDF] [Code]
    X. Dong, D. Thanou, P. Frossard and P. Vandergheynst
    IEEE Transactions on Signal Processing, vol. 64, no. 23, pp. 6160-6173, December 2016.

  18. Multiscale event detection in social media [PDF] [Code]
    X. Dong, D. Mavroeidis, F. Calabrese and P. Frossard
    Data Mining and Knowledge Discovery, Special Issue of the ECMLPKDD 2015 Journal Track, vol. 29, no. 5, pp. 1374-1405, September 2015.

  19. Clustering on multi-layer graphs via subspace analysis on Grassmann manifolds [PDF] [Code] [TSP cover]
    X. Dong, P. Frossard, P. Vandergheynst and N. Nefedov
    IEEE Transactions on Signal Processing, vol. 62, no. 4, pp. 905-918, February 2014.

  20. Clustering with multi-layer graphs: A spectral perspective [PDF] [Code]
    X. Dong, P. Frossard, P. Vandergheynst and N. Nefedov
    IEEE Transactions on Signal Processing, vol. 60, no. 11, pp. 5820-5831, November 2012.

  21. Structural analysis of network traffic matrix via relaxed principal component pursuit [PDF]
    Z. Wang, K. Hu, K. Xu, B. Yin and X. Dong
    Computer Networks, vol. 56, no. 7, pp. 2049-2067, May 2012.

Conference Paper (with proceedings)

  1. Learning to infer structures of network games [PDF]
    E. Rossi, F. Monti, Y. Leng, M. M. Bronstein and X. Dong
    International Conference on Machine Learning (ICML), July 2022.

  2. Modeling ideological salience and framing in polarized online groups with graph neural networks and structured sparsity [PDF]
    V. Hofmann, X. Dong, J. B. Pierrehumbert and H. Schuetze
    Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), July 2022.

  3. Understanding over-squashing and bottlenecks on graphs via curvature [PDF]
    J. Topping*, F. Di Giovanni*, B. P. Chamberlain, X. Dong and M. M. Bronstein (*equal contribution)
    International Conference on Learning Representations (ICLR), April 2022.

  4. Adaptive Gaussian processes on graphs via spectral graph wavelets [PDF]
    F. L. Opolka*, Y.-C. Zhi*, P. Liò and X. Dong (*equal contribution)
    International Conference on Artificial Intelligence and Statistics (AISTATS), March 2022.

  5. Beltrami flow and neural diffusion on graphs [PDF]
    B. P. Chamberlain, J. Rowbottom, D. Eynard, F. Di Giovanni, X. Dong and M. M. Bronstein
    Conference on Neural Information Processing Systems (NeurIPS), December 2021.

  6. Learning to learn graph topologies [PDF]
    X Pu, T Cao, X Zhang, X Dong and S Chen
    Conference on Neural Information Processing Systems (NeurIPS), December 2021.

  7. Adversarial attacks on graph classifiers via Bayesian optimisation [PDF]
    X. Wan, H. Kenlay, B. Ru, A. Blaas, M. A. Osborne and X. Dong
    Conference on Neural Information Processing Systems (NeurIPS), December 2021.

  8. Interpretable stability bounds for spectral graph filters [PDF]
    H. Kenlay, D. Thanou and X. Dong
    International Conference on Machine Learning (ICML), July 2021.

  9. On the stability of graph convolutional neural networks under edge rewiring [PDF]
    H. Kenlay, D. Thanou and X. Dong
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Toronto, ON, Canada, June 2021.

  10. Interpretable neural architecture search via Bayesian optimisation with Weisfeiler-Lehman kernels [PDF]
    B. Ru*, X Wan*, X. Dong and M. A. Osborne (*equal contribution)
    International Conference on Learning Representations (ICLR), May 2021.

  11. Mobility networks for predicting gentrification [PDF]
    O. Gardiner and X. Dong
    International Conference on Complex Networks and their Applications (Complex Networks), Madrid, Span, December 2020.

  12. Laplacian-regularized graph bandits: Algorithms and theoretical analysis [PDF]
    K. Yang, X. Dong and L. Toni
    International Conference on Artificial Intelligence and Statistics (AISTATS), Palermo, Italy, August 2020.

  13. Learning quadratic games on networks [PDF]
    Y. Leng, X. Dong, J. Wu and A. Pentland
    International Conference on Machine Learning (ICML), Vienna, Austria, July 2020.

  14. On the stability of polynomial spectral graph filters [PDF]
    H. Kenlay, D. Thanou and X. Dong
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, May 2020.

  15. Multi-modal image retrieval with random walk on multi-layer graphs [PDF]
    R. Khasanova, X. Dong and P. Frossard
    IEEE International Symposium on Multimedia (ISM), San Jose, CA, USA, December 2016.

  16. Laplacian matrix learning for smooth graph signal representation [PDF]
    X. Dong, D. Thanou, P. Frossard and P. Vandergheynst
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brisbane, Australia, April 2015.

  17. SaferCity: A system for detecting incidents from social media [PDF]
    M. Berlingerio, F. Calabrese, G. Di Lorenzo, X. Dong, Y. Gkoufas and D. Mavroeidis
    IEEE International Conference on Data Mining (ICDM), Dallas, TX, USA, December 2013.

  18. Clustering on multi-layer graphs via subspace analysis on Grassmann manifolds [PDF]
    X. Dong, P. Frossard, P. Vandergheynst and N. Nefedov
    IEEE Global Conference on Signal and Information Processing (GlobalSIP), Austin, TX, USA, December 2013.

  19. Inference of mobility patterns via spectral graph wavelets [PDF]
    X. Dong, A. Ortega, P. Frossard and P. Vandergheynst
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vancouver, Canada, May 2013.

  20. Learning of structured graph dictionaries [PDF]
    X. Zhang, X. Dong and P. Frossard
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, Japan, March 2012.

  21. A regularization framework for mobile social network analysis [PDF]
    X. Dong, P. Frossard, P. Vandergheynst and N. Nefedov
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Prague, Czech Republic, May 2011.

Conference Paper (without proceedings)

  1. On the unreasonable effectiveness of feature propagation in learning on graphs with missing node features
    E. Rossi, H. Kenlay, M. I. Gorinova, B. P. Chamberlain, X. Dong and M. M. Bronstein
    NeurIPS 2022 Workshop on New Frontiers in Graph Learning, New Orleans, LA, USA, December 2022.

  2. Understanding stock market instability via graph auto-encoders
    D. Gorduza, X. Dong and S. Zohren
    NeurIPS 2022 Workshop on Graph Learning for Industrial Applications, New Orleans, LA, USA, December 2022.

  3. Can social connections be protected when behavioral data is public?
    Y. Leng and Y. Chen and X. Dong and J. Wu and G. Shi
    Workshop on Information Technology and Systems (WITS), Copenhagen, Denmark, December 2022.

  4. Structure-aware robustness certificates for graph classification
    P. Osselin, H. Kenlay and X. Dong
    International Workshop on Mining and Learning with Graphs (MLG), Grenoble, France, September 2022.

  5. On the unreasonable effectiveness of feature propagation in learning on graphs with missing node features
    E. Rossi, H. Kenlay, M. I. Gorinova, B. P. Chamberlain, X. Dong and M. M. Bronstein
    ECML PKDD 2022 Workshop on Graph Quality, Grenoble, France, September 2022.

  6. Graph similarity learning for change-point detection in dynamic networks
    D. Sulem, H. Kenlay, M. Cucuringu and X. Dong
    Higher-Order Topology & Dynamics in Complex Networks, Satellite Symposium of NetSci'22, Shanghai, China, July 2022.

  7. Graph similarity learning for change-point detection in dynamic networks
    D. Sulem, H. Kenlay, M. Cucuringu and X. Dong
    International School and Conference on Network Science (NetSci), Shanghai, China, July 2022.

  8. Long-term behavioral changes during COVID-19 have increased urban segregation
    T. Yabe, B. G. B. Bueno, X. Dong, A. Pentland and E. Moro
    International School and Conference on Network Science (NetSci), Shanghai, China, July 2022.

  9. Long-term impacts of COVID-19 on urban income segregation
    T. Yabe, B. G. B. Bueno, X. Dong, A. Pentland and E. Moro
    International Conference on Computational Social Science (IC2S2), Chicago, IL, USA, July 2022.

  10. Interaction data are identifiable even across long periods of time
    A.-M. Cretu, F. Monti, S. Marrone, X. Dong, M. M. Bronstein and Y.-A. de Montjoye
    NeurIPS 2021 Workshop on Privacy in Machine Learning, December 2021.

  11. Interaction data are identifiable even across long periods of time
    A.-M. Cretu, F. Monti, S. Marrone, X. Dong, M. M. Bronstein and Y.-A. de Montjoye
    ACM CCS 2021 Workshop on Privacy Preserving Machine Learning, November 2021.

  12. Local2Global: Scaling global representation learning on graphs via local training
    L. G. S. Jeub, G. Colavizza, X. Dong, M. Bazzi and M. Cucuringu
    KDD 2021 Workshop on Deep Learning on Graphs: Methods and Applications, August 2021.

  13. Attacking graph classification via Bayesian optimisation
    X. Wan, H. Kenlay, B. Ru, A. Blaas, M. A. Osborne and X. Dong
    ICML 2021 Workshop on Adversarial Machine Learning, July 2021.

  14. On the stability of graph convolutional neural networks under edge rewiring
    H. Kenlay, D. Thanou and X. Dong
    ICLR 2021 Workshop on Geometrical and Topological Representation Learning, May 2021.

  15. On the stability of graph convolutional neural networks under edge rewiring
    H. Kenlay, D. Thanou and X. Dong
    AAAI 2021 Workshop on Deep Learning on Graphs, February 2021.

  16. Gaussian processes on graphs via spectral kernel learning
    Y.-C. Zhi, Y. C. Ng and X. Dong
    AAAI 2021 Workshop on Graphs and more Complex Structures for Learning and Reasoning, February 2021.

  17. Geometric deep learning for music genre classification
    M. Sathyamurthy, X. Dong and M. Pawan Kumar
    International Workshop on Machine Learning and Music (MML), Ghent, Belgium, September 2020.

  18. Segregated behaviors in American cities
    E. Moro, D. Calacci, X. Dong and A. Pentland
    International Conference on Computational Social Science (IC2S2), Cambridge, MA, USA, July 2020.

  19. Beyond exposure: The complex pattern of social influence
    Y. Leng, X. Dong, M. Travizano, E. Moro and A. Pentland
    International Conference on Computational Social Science (IC2S2), Cambridge, MA, USA, July 2020.

  20. Entropic graph spectrum
    D. Granziol, B. Ru, S. Zohren, X. Dong, M. A. Osborne and S. Roberts
    NeurIPS 2019 Workshop on Information Theory and Machine Learning, Vancouver, Canada, December 2019.

  21. Mapping segregation in urban areas
    A. J. Morales, X. Dong, Y. Bar-Yam and A. Pentland
    International Conference on Computational Social Science (IC2S2), Amsterdam, Netherlands, July 2019.

  22. Learning network structure in linear quadratic games
    Y. Leng, X. Dong and A. Pentland
    International Conference on Computational Social Science (IC2S2), Amsterdam, Netherlands, July 2019.

  23. Economical segregation of encounter networks in cities
    E. Moro, D. Calacci, X. Dong and A. Pentland
    NetMob, Oxford, UK, July 2019.

  24. Mapping segregation in urban areas
    A. J. Morales, X. Dong, Y. Bar-Yam and A. Pentland
    International School and Conference on Network Science (NetSci), Burlington, VT, USA, May 2019.

  25. Beyond exposure: The complex pattern of social influence
    Y. Leng, X. Dong, E. Moro and A. Pentland
    International School and Conference on Network Science (NetSci), Burlington, VT, USA, May 2019.

  26. Learning quadratic games on networks
    Y. Leng, X. Dong and A. Pentland
    International Conference on Complex Networks and Their Applications (Complex Networks), Cambridge, UK, December 2018.

  27. Inferring mobile app preference via multi-view geometric information fusion
    Y. Leng, X. Dong, D. Adjodah and A. Pentland
    Conference on Information Systems and Technology (CIST), Phoenix, AZ, USA, November 2018.

  28. Quantifying heterogeneous social influence via ego network structures
    Y. Leng, X. Dong, E. Moro and A. Pentland
    Conference on Digital Experimentation (CODE), Cambridge, MA, USA, October 2018.

  29. Mapping segregation in urban areas
    A. J. Morales, Y. Bar-Yam, X. Dong and A. Pentland
    Conference on Complex Systems (CCS), Thessaloniki, Greece, September 2018.

  30. Economical segregation of encounter networks in cities
    E. Moro, D. Calacci, X. Dong, M. Cebrian and A. Pentland
    International Conference on Computational Social Science (IC2S2), Evanston, IL, USA, July 2018.

  31. Economical segregation of encounter networks in cities
    E. Moro, D. Calacci, X. Dong, M. Cebrian and A. Pentland
    International School and Conference on Network Science (NetSci), Paris, France, June 2018.

  32. A Bayesian learning model for decision-making in social networks
    Y. Leng, X. Dong, E. Moro and A. Pentland
    International School and Conference on Network Science (NetSci), Paris, France, June 2018.

  33. Inferring mobile app preference via multi-view geometric information fusion
    Y. Leng, X. Dong, D. Adjodah and A. Pentland
    Graph Signal Processing Workshop (GSP), Lausanne, Switzerland, June 2018.

  34. A large-scale experiment and model of social influence in phone communication networks
    Y. Leng, X. Dong, E. Moro and A. Pentland
    Annual Conference on Network Science and Economics (NetSciEcon), Nashville, TN, USA, April 2018.

  35. Coupling patterns of virtual and physical behavior
    A. J. Morales, X. Dong, Y. Bar-Yam and A. Pentland
    Conference on Complex Systems (CCS), Cancún, Mexico, September 2017.

  36. Coupling patterns of virtual and physical behavior
    A. J. Morales, X. Dong, Y. Bar-Yam, B. Bozkaya and A. Pentland
    International Conference on Computational Social Science (IC2S2), Cologne, Germany, July 2017.

  37. The ripple effect: You are more influential than you think
    Y. Leng, X. Dong, E. Moro and A. Pentland
    International School and Conference on Network Science (NetSci), Indianapolis, IN, USA, June 2017.

  38. The ripple effect of social influence in phone communication network
    Y. Leng, X. Dong, E. Moro and A. Pentland
    NetMob, Milan, Italy, April 2017.

  39. Spatial structure of cities: How neighborhoods' activity patterns shape inequality and polycentricity
    M. De Nadai, X. Dong, R. Larcher, A. Pentland and B. Lepri
    International Conference on Computational Social Science (IC2S2), Evanston, IL, USA, June 2016.

  40. DeepShop: Understanding purchase patterns via deep learning
    Y. Suhara, X. Dong, B. Bozkaya and A. Pentland
    International Conference on Computational Social Science (IC2S2), Evanston, IL, USA, June 2016.

  41. Purchase patterns, socioeconomic status, and political inclination
    X. Dong*, E. Jahani*, A. J. Morales, B. Bozkaya, B. Lepri and A. Pentland (*equal contribution)
    International Conference on Computational Social Science (IC2S2), Evanston, IL, USA, June 2016.

  42. Learning graph Laplacians: A signal representation perspective
    D. Thanou, X. Dong and P. Frossard
    Graph Signal Processing Workshop (GSP), Philadelphia, PA, USA, May 2016.

  43. Social bridges in community purchase behavior
    X. Dong*, Y. Suhara*, B. Bozkaya, V. K. Singh and A. Pentland (*equal contribution)
    Workshop on Information in Networks (WIN), New York, NY, USA, October 2015.

  44. Methods for clustering multi-layer graphs in mobile networks
    X. Dong, P. Frossard, P. Vandergheynst and N. Nefedov
    Interdisciplinary Workshop on Information and Decision in Social Networks (WIDS), Cambridge, MA, USA, May-June 2011.

Patent

  1. System for identifying, monitoring and ranking incidents from social media [Link]
    M. Berlingerio, X. Dong, A. Gkoulalas-Divanis and D. Mavroeidis
    US Patent: US9397904 B2, July 2016.