About
Over the past few years, behavior quantification and modeling has experienced an explosion of innovation and discovery largely enabled by application of new machine learning methods. These methods have enabled the quantification of behavior at high temporal and spatial resolution, and in concordance with simultaneous measurement and manipulation of neural and genetic function. However, access to this revolutionary technology is limited primarily due to a lack of adequate resources and training. Democratization of this technology through training of the next generation of scientists is necessary to elevate the field of quantitative behavior.
The Short Course on the Application of Machine Learning for Automated Quantification of Behavior will disseminate the theoretical and technical knowledge of this field, and train researchers to apply machine learning methods to behavior quantitation and modeling. Our goal is to build an educational program that fosters productive and interactive dialogue, teaches proper methodology, and provides support structure to nurture and lower the barrier of entry into this nascent field. The course will:
- teach the theoretical basis of machine learning and its applications to quantitative animal behavior analyses
- offer hands-on training in experimental workflow, analysis tools and algorithms
- showcase key biological applications
- foster organic collaborations across disparate fields
This course is appropriate for early career researchers from the fields of neuroscience, genetics, and biomedical research and will prioritize diverse learners and those who are educators and mentors. The short course will also include scientific lectures and promote collaborative networking between researchers and technology developers to drive innovation in animal behavior modeling.
In-Person Option
The in-person course includes morning lectures from 8:00 AM - 12:00 PM, lunch, activities led by instructors (such as walking or hiking) between 1:00 - 3:00 PM, hands-on workshops from 3:00 - 6:00 PM and informal evening discussions after dinner. In addition, participants will have additional opportunities to interact with faculty on special outings and during a poster session.
Virtual Option
The virtual audience will have access the live-stream of morning lectures from (approximately) 8:00 AM - 12:00 PM EDT and will have the ability to ask questions at the end of each lecture through a virtual Q+A function. In addition, all lectures will be recorded and posted within 72 hours of airing on a centralized Canvas course that participants will have access to for six months following the course.
The virtual audience will not have access to live or recorded versions of workshops or evening discussions.
In-Person Requirements: Participants must bring a laptop with a Mac or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. You will also need a reasonably up-to-date browser, such as a current version of the Chrome, Safari or Firefox browsers (some older browsers, including Internet Explorer version 9 and below, are not supported). Basic scripting or programming knowledge is suggested but not required.
This program is supported by the National Institutes of Health and the Howard Hughes Medical Institute. The content is solely the responsibility of the organizers and does not necessarily represent the official views of the National Institutes of Health or the Howard Hughes Medical Institute.
