Headshot Image

Dr. Ted Willke is an Adjunct Assistant Professor in the Department of Electrical and Computer Engineering at Portland State University. He received his doctorate in electrical engineering from Columbia University, master’s degrees from the University of Wisconsin-Madison and the University of Illinois, and bachelor’s degree from the University of Illinois.

Ted is currently the Director of the Brain-Inspired Computing Lab at Intel. The lab’s mission is to make Intel a leader in brain-inspired artificial intelligence by working closely with leaders in neuroscience to develop new algorithms and systems. Ted is also co-principal investigator of a multi-year grand challenge program on real-time brain decoding with the Princeton Neuroscience Institute. Previously, he founded an Intel venture focused on graph analytics for data science. In 2014, he won Intel’s highest award for this effort. In 2015, he was appointed to the Science & Technology Advisory Committee of the US Department of Homeland Security and served a 3-year term.

Ted’s research focuses on cognitive modeling, neuroscience-inspired artificial intelligence, medical imaging and neuroimaging analysis, graphical machine learning, and new computational technologies for these workloads. He has published over 50 peer-reviewed research papers and holds 13 patents. He applies his work to challenges in neuroscience, medicine, oceanography, and other important areas. For a list of Ted’s publications, see his CV or visit Google Scholar Profile.

You can reach Ted at willke@pdx.edu.

Selected Publications

Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-out Classifiers (Paper)
Published in European Conference on Computer Vision 2018
Vyas, A., Jammalamadaka, N., Zhu, X., Das, D., Kaul, B., Willke, T.L.

A Probabilistic Approach to Discovering Dynamic Full-Brain Functional Connectivity Patterns (Paper)
Published in NeuroImage
Manning, J.R., Zhu, X., Willke, T.L., Ranganath, R., Stachenfeld, K., Hasson, U., Blei, D.M., Norman, K.A.

Capturing Shared and Individual Information in fMRI Data (Paper)
Published in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2018
Turek, J.S., Ellis, C.T., Skalaban, L.J., Turk-Browne, N.B., Willke, T.L.

Anatomical DCE-MRI Phantoms Generated from Glioma Patient Data (Paper)
Published in Physics of Medical Imaging 2018, International Society for Optics and Photonics
Beers, A., Chang, K., Brown, J., Zhu, X., Sengupta, D., Willke, T.L., Gerstner, E., Rosen, B., Kalpathy-Cramer, J.

On Sampling from Massive Graph Streams (Paper)
Published in Proceedings of the VLDB Endowment 2017
Ahmed, N.K., Duffield, N., Willke, T.L., Rossi, R.A.

Bridging the Gap Between HPC and Big Data Frameworks (Paper)
Published in Proceedings of the VLDB Endowment 2017
Anderson, M., Smith, S., Sundaram, N., Capotă, M., Zhao, Z., Dulloor, S., Satish, N., Willke, T.L.

Computational Approaches to fMRI Analysis (Paper)
Published in Nature Neuroscience
Cohen, J.D., Daw, N., Engelhardt, B., Hasson, U., Li, K., Niv, Y., Norman, K.A., Pillow, J., Ramadge, P.J., Turk-Browne, N.B., Willke, T.L.