December 1, 2020

12:00 pm / 1:15 pm

Venue

https://wse.zoom.us/j/95490607662?pwd=Zzh4OVNQZWpnaFpjekxlaWhQTnk4Zz09

Recorded Seminar:   
https://wse.zoom.us/rec/share/OVqxOYDSECLaEO-ribZB_t_U6PA2Dg9D7sLUcS2t9hfjpZIRMvhL1KD7RAYSv6kR.SQV7uErjDaH_sopU?startTime=1606841134000    

Join Zoom Meeting
https://wse.zoom.us/j/95490607662?pwd=Zzh4OVNQZWpnaFpjekxlaWhQTnk4Zz09

Meeting ID: 954 9060 7662
Passcode: clark_hall

Eva Dyer, PhD 

Assistant Professor 
in the Coulter Department ofBiomedical Engineering 
at the Georgia Institute of Technology 
and Emory University   

  ?Representation learning and alignment in biological andartificial neural networks?   

Abstract: In both biological and artificial neural networks,we are faced withsimilar challenges in interpreting how the representations of many neurons (orunits) change across different domains, across perturbations, or across differentindividuals (or networks) performing the same task. The question, however, ofhow we should go about comparing the activities of populations of neurons overall these differing conditions is stilla major challenge. A critical observation isthat when the activity of manyneurons can be modeled as being driven by asmaller number of latent factors, then distinct measurements acquired fromneurons that share the similar underlying latent space can be compared byfinding and aligning their latentfactors. In this talk, I will highlight newapproaches that my lab is developing for representation learning and alignment,and demonstrate their applications in the analysis and interpretation of neuralnetworks. Being able to align neural representations promises meaningful waysof comparing high-dimensional neural activities across times, subsets ofneurons, or individuals. 

Bio: Eva Dyer is an Assistant Professor in the Coulter Department ofBiomedical Engineering at the Georgia Institute of Technology and EmoryUniversity. Dr. Dyer works at the intersection of neuroscience and machinelearning, developing machine learning approaches to interpret complexneuroscience datasets, and designing new machine intelligence architecturesinspired by the organization and function of biological brains. Dr. Dyer completedall of her degrees in Electrical & Computer Engineering, obtaining a Ph.D. andM.S. from Rice University, and a B.S. from the University of Miami. She is therecipient of a Sloan Fellowship in Neuroscience, an NSF CISE ResearchInitiation Initiative Award, was a previous AllenInstitute for Brain Science NextGeneration Leader, and was recently awarded a McKnight Award forTechnological Innovations in Neuroscience.