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Eva Dyer is currently an an adjunct assistant professor in the School of ECE and an assistant professor in the Wallace H. Coulter Department of Biomedical Engineering at the Georgia Institute of Technology and Emory University. She runs the Neural Data Science (NerDS) Lab, where she and her team develop new machine learning and data science approaches for making sense of large-scale neural datasets. Eva completed all of her degrees in Electrical & Computer Engineering, including a Ph.D. (2014) and M.S. (2011) from Rice University, and her B.S. (2007) from University of Miami.
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Computational neuroscience
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Machine learning
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Signal processing
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Low-dimensional models
- Next Generation Leader Award from the Allen Institute for Brain Science
- NSF Graduate Fellowship Recipient
- Eliahu Jury Award for Scholarship in Electrical Engineering
E.L. Dyer, M. Azar, H.L. Fernandes, M. Perich, L.E. Miller, and K.P. Körding, A cryptography-based approach to brain decoding, Nature Biomedical Engineering, 1(12), 967. 2017. (Paper, Code)
E.L. Dyer, W.G. Roncal, J.A. Prasad, H.L. Fernandes, D. Gürsoy, V. De Andrade, K. Fezzaa, X. Xiao, J.T. Vogelstein, C. Jacobsen, K.P. Körding & N. Kasthuri, Quantifying mesoscale neuroanatomy using X-ray microtomography, eNeuro, 25 September 2017, 4 (5) ENEURO.0195-17. 2017.
E.L. Dyer, A.C. Sankaranarayanan, and R.G. Baraniuk, Greedy feature selection for subspace clustering, The Journal of Machine Learning Research 14 (1), 2487-2517, September 2013. (Paper)
Last revised August 19, 2019
