Dr. Emily Mackevicius is a postdoctoral research scientist working with professor Dmitriy Aronov at Columbia University. She received her BS in mathematics at the University of Chicago, and her PhD in neuroscience in the lab of professor Michale Fee at MIT. Her research investigates how intelligent behaviors emerge, especially in distributed and recurrent systems. Her theoretical work is strongly grounded in experimental practice, including neural and behavioral recordings of birds with extreme memory abilities. Her doctoral work focused on motor memories which require practice, using birdsong as a model system. She extended previous computational models of song learning to include very early learning of the overall rhythm structure and timing of a tutor song, demonstrated how rhythmically patterned inputs could train a neural network to generate precisely timed sequences, and experimentally verified predictions of these models. Dr. Mackevicius also investigated how these neural circuits self-organize in birds that have never heard a tutor and developed a new computational method for unsupervised detection of precisely timed neural sequences (seqNMF). For her postdoctoral research, Dr. Mackevicius is investigating memories that do not require rehearsal, but instead stem from a single ‘episodic’ experience. This work involves developing new theoretical frameworks, as well as a new experimental model system—food-catching birds with extreme memory abilities. In addition to her postdoctoral position at Columbia, Dr. Mackevicius has co-founded a new research institute, Basis, which develops open-source AI code applied to real-world problems, including understanding collaborative multi-agent behaviors. Through her BRAIN Initiative project, she will assess the role of hippocampus-based memory in foraging decisions within the context of multi-agent, multi-species groups of birds