Melanie Mitchell

What's New:

I will be on sabbatical during the 2017-2018 academic year. (I will not be adding any new students or interns to my research group.)

A video of my talk on "Artificial Intelligence and 'the Barrier of Meaning'".

Recent papers from my research group

Gaussian processes with context-supported priors for active object localization. To appear in IJCNN 2018.

Semantic image retrieval via active grounding of visual situations. In Proceedings of the 12th International Conference on Semantic Computing (IEEE), 2018.

Sparse coding on stereo video for object detection. In Proceedings of the NIPS Workshop on Learning with Limited Labeled Data: Weak Supervision and Beyond, 2017.

Fast on-line kernel density estimation for active object localization. In Proceedings of the International Joint Conference on Neural Networks, 2017

Current and upcoming free courses and tutorials from Complexity Explorer

Biographical Sketch:

Melanie Mitchell is Professor of Computer Science at Portland State University, and External Professor and Member of the Science Board at the Santa Fe Institute. She attended Brown University, where she majored in mathematics and did research in astronomy, and the University of Michigan, where she received a Ph.D. in computer science, Her dissertation, in collaboration with her advisor Douglas Hofstadter, was the development of Copycat, a computer program that makes analogies. She has held faculty or professional positions at the University of Michigan, the Santa Fe Institute, Los Alamos National Laboratory, the OGI School of Science and Engineering, and Portland State University. She is the author or editor of five books and over 80 scholarly papers in the fields of artificial intelligence, cognitive science, and complex systems. Her most recent book, Complexity: A Guided Tour (Oxford, 2009), won the 2010 Phi Beta Kappa Science Book Award. It was also named by Amazon.com as one of the ten best science books of 2009, and was longlisted for the Royal Society's 2010 book prize. Melanie originated the Santa Fe Institute's Complexity Explorer project, which offers online courses and other educational resources related to the field of complex systems.

Artificial intelligence, machine learning, computer vision, cognitive science, complex systems.

Teaching:

2018-2019 Academic Year

Fall, 2018:

CS 445/545: Machine Learning

CS 570: Machine Learning Seminar
Topic: Fairness and Transparency in Machine Learning

Winter, 2019:

CS 445/545: Machine Learning

CS 570: Machine Learning Seminar
Topic: TBA

Spring, 2019:

CS 570: Machine Learning Seminar
Topic: TBA