Travis E. Gibson

Travis E. Gibson Research Fellow Harvard Medical School & Brigham and Women's Hospital Email: tgibson@mit.edu CV

Education

PhD, Massachusetts Institute of Technology (advisor Anuradha Annaswamy)
MS, Massachusetts Institute of Technology
BS, Georgia Institute of Technology

Research and Current Projects

My work is at the intersection of control theory and machine learning. My application area is in biology where I work on naturally occurring and engineered microbial consortia. My theoretical work remains in the area of adaptive control with more recent work focused on statistical inference (with Georg Gerber). I have ongoing projects in the following areas

• Statistical learning applied to microbial dynamics (Bayesian nonparametrics, layered latent state-space models)
  

• Genetically engineering and controlling a microbial consortia
  

• Theoretical foundations at the intersection of machine learning and control
  

• Microbiome remodeling via phage therapy

Selected Publications: (Google Scholar)

• Robust and Scalable Models of Microbiome Dynamics
  T.E. Gibson and G.K. Gerber
  International Conference on Machine Learning, 2018 slides poster

• Convergence Properties of Adaptive Systems and the Definition of Exponential Stability
  B.M. Jenkins, A.M. Annaswamy, E. Lavretsky, and T.E. Gibson
  SIAM Journal on Control and Optimization, in-press 2018

• Universality of human microbial dynamics
  A. Bashan, T.E. Gibson, J. Friedman, V.J. Carey, S.T. Weiss, E.L. Hohmann and Y.-Y. Liu
  Nature, 534, 259–262, 2016
  Nature News and Views Nature Physics Highlight

• Adaptation and Synchronization over a Network: Asymptotic Error Convergence and Pinning
  T.E. Gibson
  Conference on Decision and Control, 2016 slides

• Adaptive Output Feedback based on Separation Principle and Closed-loop Reference Models
  T.E. Gibson, Z. Qu, A.M. Annaswamy, E. Lavretsky
  IEEE Transactions on Automatic Control, 2015