Machine Learning

Research Area Faculty and Interests

  • cattaneo's picture
    Research Interests:
    Econometrics, statistics, machine learning, data science, causal inference, program evaluation, quantitative methods in the social, behavioral and biomedical sciences.
  • jqfan's picture
    Research Interests:
    High-dimensional statistics, Machine Learning, financial econometrics, computational biology, biostatistics, graphical and network modeling, portfolio theory, high-frequency finance, time series.
  • bhanin's picture
    Research Interests:
    Machine learning - theory of neural networks: approximation power, statistical physics of initialization, guarantees for optimization, and generalization Probability - mathematical physics, random matrix theory, Gaussian processes arising in spectral theory/quantum mechanics, and random polynomial
  • jk53's picture
    Research Interests:
    Data science, statistical learning, deep learning, decision tree learning; high-dimensional statistics, information theory, statistical physics, network modeling
  • bs37's picture
    Research Interests:
    Data-driven computational tools for mathematical optimization, machine learning and optimal control. Real-time and embedded optimization. Dynamical systems and optimization-based control. Differentiable optimization. First-order methods for large scale optimization. Machine learning for optimization and data-driven algorithms. Applications include control of fast dynamical systems, finance, robotics and autonomous systems.

Machine learning emerges from the need to design algorithms that are capable of learning from data how to make accurate predictions and decisions. Such problems arise in a variety of "big data" domains such as finance, genomics, information technologies and neuroscience. Research at ORFE ranges from the design of large-scale machine learning algorithms to their mathematical analysis.