Dr. Shams is recipient of a UCLA Undergrad Research Faculty Mentorship award.
Shams Lab research assistant Chenyang (Leo) Lin received a research fellowship award from Yale University with a start date in 2021.
Shams Lab graduate student Saul has received an NSF GRFP Award in the 2021 award cycle.
Shams Lab graduate student Sashel has received an NSF GRFP Honorable Mention in the 2021 award cycle.
Lab News | April 2020
Dr. Shams was recently featured in an article of Maddyness.
Lab News | December 2019
Dr. Shams was recently interviewed and quoted in an ESPN article.
Lab News | May 2019
Dr. Shams was quoted in one of the neuroscience articles in Medium.
UCLA MULTISENSORY PERCEPTION LAB IS PROUD TO PRESENT THE MULTISENSORY SCIENCE, ART AND TECHNOLOGY SYMPOSIUM
Prof. Shams will deliver a keynote speech at the 2018 International Multisensory Research Forum.
I would like to announce the beta release of Bayesian Causal Inference toolbox (BCIT), developed at the UCLA Multisensory Perception Lab:
BCIT is a MATLAB toolbox developed for learning and using the Bayesian Causal Inference Model of multisensory perception. This NSF-sponsored toolbox was developed for two aims: a) serving as a pedagogical tool for learning and understanding how the model works, and b) for adapting and using the model to explain experimental data in a variety of experimental paradigms. The toolbox is designed for use by researchers of any background, and does not require any computational training or skills.
This is a beta release and we welcome feedback on the existing functionality, as well as suggestions for additional functionality to be added in future releases. Please email the lead developer Dr. Majed Samad (email@example.com) or the assistant developer Kellienne Sita (firstname.lastname@example.org) with any questions. Please cc me (email@example.com) on your emails.
We look forward to your feedback.
Acknowledgement: The development of this toolbox was sponsored by NSF grant BCS-1057969.
Directions for downloading the toolbox:
- Go to: https://github.com/multisensoryperceptionlab/BCIT
- Click the green button labelled “Clone or Download”
- From the dropdown menu select “Download ZIP” to download a folder containing all of the files to the toolbox called “BCIT-Master”
- Read the brief introduction contained in the README file within the repository.
- For further explanations regarding the toolbox and its components please consult the documentation provided under the “Documentation” folder.