Merge pull request #124 from eltonpan/patch-3

Update project-27-bayes-warmup.md

_projects/project-27-bayes-warmup.md

@@ -3,23 +3,24 @@ number: 27 # leave as-is, maintainers will adjust
 title: How does initial warm-up data influence Bayesian optimization in low-data experimental settings?
 topic: general
 team_leads:
-  - Elton Pan (MIT)
-  - Pengfei Cai (MIT)
-  - Jurgis Ruza (MIT)
+  - Elton Pan (MIT) @eltonpan
+  - Pengfei Cai (MIT) @cpfpengfei
+  - Jurgis Ruza (MIT) @JurgisR
 
 # Comment these lines by prepending the pound symbol (#) to each line to hide these elements
 # contributors:
 #  - Contributor 1 (Institution 1)
 #  - Contributor 2 (Institution 2)
 
 github: eltonpan/bayes-warmup
-# youtube_video: <your-video-id>
+youtube_video: 4gPTMaarQt0
 
 ---
 
 Real-world experiments in chemistry and materials science often involve very small initial datasets (10-100 data points). In this project, we propose to investigate how the 1) size and 2) distribution of the initial dataset influence the performance of bayesian optimization algorithms. We propose experiments on molecular property optimization tasks.
 
+Check out our [submission post on X](https://twitter.com/pengfeicsci/status/1776721505361248278)!
+
 References:
 - L. Ruddigkeit, R. van Deursen, L. C. Blum, J.-L. Reymond, Enumeration of 166 billion organic small molecules in the chemical universe database GDB-17, J. Chem. Inf. Model. 52, 2864–2875, 2012.
 - R. Ramakrishnan, P. O. Dral, M. Rupp, O. A. von Lilienfeld, Quantum chemistry structures and properties of 134 kilo molecules, Scientific Data 1, 140022, 2014.
-- S. Xu, J. Li, P. Cai, X. Liu, B. Liu, X. Wang, Self-improving photosensitizer discovery system via Bayesian search with first-principle simulations. Journal of the American Chemical Society, 143(47), 19769-19777, 2021.