machine learning and computational neuroscience research group

We study machine learning and its application to science and industry, including in particular how neurons give rise to the remarkable computational sophistication of our brains. I am an Assistant Professor in the Department of Statistics at Columbia University. I was a postdoc in the Machine Learning Group at the University of Cambridge, a graduate student in electrical engineering at Stanford University, and an undergraduate in computer science at Dartmouth College. Learn more about our research and our people.

We are part of the world-class machine learning community at Columbia, which includes investigators like Dave Blei, Lauren Hannah, Daniel Hsu, Tony Jebara, Peter Orbanz, John Paisley, Liam Paninski, and more. We are also a part of the world-class neuroscience community at Columbia, including the Grossman Center for the Statistics of Mind, the Zuckerman Mind Brain Behavior Institute, and the Center for Theoretical Neuroscience.

  • "Structure in neural population data: interesting or epiphenomenal?" Simons Foundation, New York, NY, Sep. 12, 2016.
  • "Structure in neural population data: interesting or epiphenomenal?" Stanford University, Stanford, CA, Jun. 16, 2016.
  • "Finding and statistically validating hypothesized structure in high-dimensional data." Cubist Systemic Strategies, New York, NY, May 23, 2016.
  • "Your brain and high-dimensional data." Columbia University MA Student Seminar Series, New York, NY, Mar. 09, 2016.
  • "Statistical testing for neural population data, or, are population analyses all a bunch of nonsense?" Computational and Systems Neuroscience (COSYNE) Workshop, Snowbird, UT, USA, Feb. 29, 2016.
  • "Statistical testing for neural population data." University of California Berkeley, Berkeley, CA, USA, Feb. 17, 2016.
  • "Statistical testing for neural population recordings." University of Washington, Seattle, WA, USA, Jan. 29, 2016.
  • "How the brain controls movement: a journey of neural and data science." Zuckerman Institute Brain Trust, New York, NY, USA, Oct. 01, 2015.
  • "Generalized count linear dynamical systems for single-trial analysis of neural populations." Columbia University Center for Theoretical Neuroscience, New York, NY, USA, Jul. 27, 2015.
  • "Correlation structure of movement preparation and execution." Gatsby Tri-Center meeting, New York, NY, USA, Jun. 04, 2015.
  • "Expectation propagation: factorization and entropy approximation." Gaussian Process workshop, Copenhagen, Denmark, May 22, 2015.
  • "Neuroscience in the data era, data in the neuroscience era." Zuckerman Institute Brain Series, New York, NY, USA, Apr. 22, 2015.
  • "Correlation structure of movement preparation and execution." Banbury Center Worskhop, Cold Spring Harbor, NY, USA, Apr. 21, 2015.
  • "Hypothesis-guided dimensionality reduction and its application to large-scale neuroscience" Brown University Division of Applied Mathematics, Providence, RI, USA, Dec. 03, 2014.
  • "Hypothesis-guided dimensionality reduction and its application to large-scale neuroscience" Columbia University Center for Theoretical Neuroscience, New York, NY, USA, Nov. 24, 2014.
  • "Your brain and high-dimensional statistics" Columbia University Undergraduate Seminar, New York, NY, USA, Oct. 10, 2014.
  • "Statistical research and training under the BRAIN initiative," Working Group Letter to American Statistical Association (ASA), Apr. 2014. Working group with R. Kass (chair) and others. URL ; PDF.
  • "Generic linear dimensionality reduction for high-dimensional neural data," Computational and Systems Neuroscience (COSYNE) Workshop, Snowbird, UT, USA, Mar. 03, 2014.
  • "The computational structure of neural population responses," Center for Neural Engineering and Computation, Columbia University, New York, NY, USA, Nov. 20, 2013.
  • "Fast multidimensional pattern extrapolation with Gaussian processes," Department of Statistics Student Seminar, Columbia University, New York, NY, USA, Nov. 13, 2013.
  • "Model testing with neural populations," Grossman Center workshop on 'Quantifying structure in large neural datasets', Columbia University, New York, NY, USA, Oct. 17, 2013.
  • "Computation in populations of neurons," Neurosurgery Grand Rounds, Washington University, St. Louis, MO, USA, Apr. 24, 2013.
  • "The wonderland of higher space," Math Club, Washington University, St. Louis, MO, USA, Mar. 25, 2013.
  • "Computation in populations of neurons," EE Department Seminar, Stanford University, Stanford, CA, USA, Mar. 05, 2013.
  • "From single neuron statistics to neural population analyses," Neuroscience Seminar, Washington University, St. Louis, MO, USA, Jan. 08, 2013.
  • "Probabilistic Numerics," at NIPS 2012, Lake Tahoe, CA, USA, Dec. 08, 2012. Workshop, organized with P. Hennig and M. Osborne. [awarded PASCAL network of excellence support grant]
  • "Statistical analyses of populations of neurons," Statistics Department Seminar, Columbia University, NY, NY, USA, Nov. 26, 2012.
  • "From single neuron statistics to neural population analyses," Neurotheory Center Seminar, Columbia University, NY, NY, USA, Oct. 26, 2012.
  • "Characterizing neural population dynamics and predicting behavior," BME Department Seminar, Washington University, St. Louis, MO, USA, Oct. 12, 2012.
  • "Computation in Populations of Neurons," CBSE Center Seminar, Washington University, St. Louis, MO, USA, Sep. 07, 2012.
  • "R-100 is a big place," at Swartz/Gatsby/Janelia Dimensionality Reduction Meeting, HHMI/Janelia Farm, VA, USA, Jul. 26, 2012.
  • "Extracting Rotational Structure from Motor Cortical Data," at Swartz/Gatsby/Janelia Dimensionality Reduction Meeting, HHMI/Janelia Farm, VA, USA, Jul. 25, 2012.
  • "Extracting Rotational Structure from Motor Cortical Data," at Machine Learning and Neuroscience Meeting, HHMI/Janelia Farm, VA, May 07, 2012.
  • "Gaussian Processes for machine learning." invited lecture at the Machine Learning Summer School 2012, La Palma, Spain, Apr. 18, 2012.
    Video: Part 1 ; Part 2
  • "Gaussian Processes for machine learning." Machine Learning seminar, Washington University, St. Louis, MO, USA, Apr. 16, 2012.
  • "Single Neuron Thinking (and my hope that we end it by 2025)." at the New York Academy of Sciences, NY, NY, USA. Mar. 11, 2012.
  • "Approximate Inference." Machine Learning RCC, Cambridge, UK, Dec. 08, 2011. With David Knowles.
  • "Nothing that is can pause or stay; The moon will wax, the moon will wane, The mist and cloud will turn to rain, The rain to mist and cloud again, To-morrow be to-day." CBL Tea Talk, Cambridge, UK, Dec. 07, 2011.
  • "Extracting Rotational Structure from Motor Cortical Data," at Society for Neuroscience, Washington, DC, USA. Nov. 13, 2011.
  • "What is this that thou hast done? And the [developer] said, 'The serpent beguiled me, and I did eat.'" CBL Tea Talk, Cambridge, UK, Sep. 30, 2011.
  • "High performance neural prostheses: understanding and exploiting closed-loop feedback control" (invited talk) British Neuroscience Association Annual Meeting, Harrogate, UK, Apr. 19, 2011.
  • "Gaussian Probabilities and Expectation Propagation," CBL Research Talk, Cambridge, UK, Apr. 11, 2011.
  • "Cortical preparatory activity: representation of movement or first cog in a dynamical machine?" Computational Neuroscience Journal Club, Cambridge, UK, Feb. 01, 2011.
  • "A closed-loop human simulator for understanding feedback-control and its relevance for brain-machine interfaces," at Society for Neuroscience, San Diego, CA, USA. Nov. 13, 2010.
  • "The jewel has facets, and it is possible that many [histories] are moderately true... But we are only moderately certain," CBL Tea Talk, Cambridge, UK, Oct. 01, 2010.
  • "Analysing Time Marked Data," CBL Research Talk, Cambridge, UK, Jul. 19, 2010.
  • "Numerical Linear Algebra," Machine Learning RCC, Cambridge, UK, Apr. 29, 2010. With Peter Orbanz.
  • "Gravely the men turn [the matrix] - the wrong [matrix]. But no one knows [Heywood's] name, and no one cares." CBL Tea Talk, Cambridge, UK, Apr. 28, 2010.
  • "Neural Prosthetic Systems: Past, Present, and Future," CBL Research Talk, Cambridge, UK, Feb. 8, 2010.
  • "Neural Prosthetic Systems: Current Problems and Future Directions," at IEEE EMBC 2009, Minneapolis, MN, USA. Sep. 4, 2009.
  • "Numerical Mathematics in Machine Learning," at ICML 2009, Montreal, Quebec, Canada. Jun. 18, 2009. Organized with M. Seeger and S. Sra.
  • "Algorithms for Understanding Motor Cortical Processing and Neural Prosthetic Systems," Faculty job talk and Ph.D. oral defense talk, given several times throughout 2009.
  • "Dimensionality reduction for multi-channel neural recordings," at COSYNE 2009, Snowbird, UT, USA. Mar. 3, 2009. Organized with B.M. Yu.
  • "Toward an Improved Understanding of Motor Cortical Processing," at MIT/MGH, Charlestown, MA, USA. Dec. 15, 2008.
  • "Decoding arm movements: a framework and suite of approaches," at DARPA prosthetic signal analysis summit, Columbia, MD, USA. Nov. 14, 2008. with C.A. Chestek and V. Gilja.
  • "Fast Gaussian Process Methods for Point Process Intensity Estimation," at the 25th International Conference on Machine Learning, Helsinki, Finland. Jul. 7, 2008
  • "Practical Optimization Tricks and Tips," at the Gatsby Computational Neuroscience Unit, University College London, London, UK. Jun. 19, 2008
  • "Engineering Challenges in Neural Prosthetic Systems," at the Stanford Bioengineering Forum, Stanford, CA, USA. Feb. 26, 2008
  • "Neural Basis of Reach Preparation and Neural Communication Prostheses," at the Neukom Inst. for Comp. Sci., Dartmouth College, Hanover, NH, USA. Feb. 11, 2008
  • "Engineering Challenges in Neural Prosthetic Systems," at the Thayer School of Engineering, Dartmouth College, Hanover, NH, USA. Feb. 8, 2008
  • "Inferring Neural Firing Rates from Spike Trains using Gaussian Processes," Spotlight Presentation at Neural Information Processing Systems 20 (NIPS 20), Vancouver, BC, CA. Dec. 5, 2007
  • "Inferring Neural Firing Rates from Spike Trains using Gaussian Processes," Research Talk, Gatsby Computational Neuroscience Unit, University College London, London, UK. Nov. 27, 2007