SfN Virtual Conference: Machine Learning in Neuroscience — Fundamentals and Possibilities

Registration Details

Wednesday, June 26, 11 a.m. to 5 p.m. EDT

Machine learning methods enable researchers to discover statistical patterns in large datasets to solve a wide variety of tasks, including in neuroscience. Recent advances have led to an explosion in the scope and complexity of problems to which machine learning can be applied, with an accuracy rivaling or surpassing that of humans in some domains.

This virtual conference will illuminate the many ways machine learning and neuroscience intersect in the context of data analysis and modeling brain function, and how neuroscience can benefit from the machine learning revolution.

SfN Member Registration Nonmember Registration

Topics include:

  • Basic machine learning concepts and resources.
  • Machine learning methods to automate analyses of large neuroscience datasets.
  • Using deep network learning to gain insight into how the brain learns.
  • Combining machine learning concepts with neuroscience theory to predict nervous system function and uncover general principles.

The conference will end with speakers sharing their views on promising future directions for both machine learning and neuroscience.


View the Full Agenda


SfN members, including Institutional Program members, are able to register for the virtual conference at the special member rate of $50, saving $100.

Not an SfN member? Nonmembers can register for the virtual conference at the registration rate of $150. Join SfN or renew your membership to register for the virtual conference at the special member rate of $50 (saving $100) and receive access to other SfN member benefits.

Receipt information is included in your registration confirmation email.

Contact us if you have questions. Email digitallearning@sfn.org or call (202) 962-4000.


Why Should You Attend?

This conference is intended to be applicable to individuals new to machine learning as well as those working at the intersection of machine learning and neuroscience.

  • Hear from leaders in the field and gain new insight for your research.
  • Ask questions and get answers from experts — each session will be accompanied by a Q&A opportunity.
  • Network with other attendees from around the world in the interactive networking lounge.
  • Avoid travel costs and learn about cutting-edge research from the comfort of your home, classroom, or lab.
  • Host watch parties with students and colleagues — only one registration is required. Please find information about watching in a group and using second screen participation links for individuals who are not registered here.
  • Enjoy six months of on-demand access. Can’t make it for the live day or want to watch the talks again? All sessions and data blitz videos are immediately available on demand.



Kristin Branson
Kristin Branson, PhD
Kristin Branson is a group leader and the head of computation and theory at the Howard Hughes Medical Institute's Janelia Research Campus. Her lab develops new machine vision and learning technologies to extract scientific understanding from large image data sets. Using these systems, Janelia Research Campus aims to gain insight into behavior and how it is generated by the nervous system. She earned her BA in computer science from Harvard University and her PhD in computer science from the University of California, San Diego, and completed postdoctoral training at the California Institute of Technology.
Edda (Floh) Thiels
Edda (Floh) Thiels, PhD
Edda (Floh) Thiels is an adjunct associate professor of neurobiology at the University of Pittsburgh School of Medicine and a program director in the Directorate for Biological Sciences at the National Science Foundation. Thiels’ main research interests lie in how animals acquire information from the environment and use that information to guide their behavior. She received her undergraduate degree in psychology from the University of Toronto and her PhD in psychology from Indiana University.

Sparking Global Conversations Around Neuroscience