A virtual one day event! Basic introductory sessions to Machine Learning, two plenary lectures, oral presentations and round table.

Date: February 18, 2021
Time: 8:30 am – 4:30 pm
Location: Zoom conference (link will be shared upon registration)
Facilitators: Laura Ibañez and Victoria Fernandez (WashU Psychiatry)

Registration and Call for Abstracts

There is no fee for this event and anyone with an interest in Machine Learning applications in OMICS and Neuroscience is welcome to attend.

Registration is required for attendance, even if you are not submitting an abstract.

Abstract deadline (includes registration): January 15
Registration deadline (if not submitting an abstract): February 16

Registration/abstract submission    


Submit your Abstract on Machine Learning using OMIC data related to Neurosciences. We are accepting abstracts in two categories (i) ongoing projects, (ii) project proposals.

Abstracts should contain the following information:

  1. Title
  2. Authors
  3. Affiliations
  4. Abstract body (1500 characters max)
    a. Ongoing projects: introduction, methods, results, conclusions
    b. Project proposals: introduction, aims, proposed methods, expected results

Best proposals will have the opportunity to be presented as oral communications and be in the final round table with advice and tips from the panel of experts. In addition, there will be monetary awards for the best communication of each category.

Abstract Deadline: January 15
Communication of abstract acceptance: February 1st

February 18, 2021 – Schedule

8.30 – 9:00 am

9:00 – 10:00 am
Dr. Noah Simon (University of Washington)
“Introduction to Machine Learning”

10:00 – 11:00 am
Dr. Justin Miller (Brigham Young University)
“Types of ML: Supervised”

11:00 – 11.45 am
Dr. James Zou (Stanford University)
“Effective use of ML in Genetic Data”

11.45 am – 12.30 pm
Dr. Shuangge Ma (Yale University)
“Multi–omic Data Integration, Implications for the Medical Field”

12.30 – 1:00 pm
Lunch break

1:00 – 2:00 pm
Dr. Justin Miller (Brigham Young University)
“Types of ML: Unsupervised”

2:00 – 3:00 pm
Abstract Presentations

3:00 – 4:00 pm
Round Table

4:00 – 4.30 pm
Prizes and Final Remarks