February 2022 CIC Webinar: Featured Q&A
Our monthly CIC webinars inspire some really fantastic audience Q&A sessions! In each monthly newsletter, we highlight one of the insightful questions raised from the webinar attendees.
A Featured Question from our February 2022 Webinar
This question was for two of our February speakers: Ho-Joon Lee (Yale University), who presented on his NSF grant, A landscape of virus-host protein-protein interactions in SARS-CoV-2 infection in humans by machine learning, and Xingzhi Guo (Stony Brook University, SUNY), who presented findings from the Knowledge Graph Embedding Evolution for COVID-19 project, which receives NSF funding through the NEBD Hub's Seed Fund Program.
You can watch Ho-Joon Lee and Xingzhi Guo's presentations on our YouTube channel.
How could Machine Learning support your research? Are some Machine Learning tools or techniques particularly helpful for research on COVID-19?
Answer from Ho-Joon Lee:
Machine Learning is a very exciting field and you can always find something to work with and apply to your research. Ironically, though, some tools are wrong and some are useful, depending on your specific project. I think, practically, there are lots of tools out there that can be useful. The best thing to do is jump in and try new tools!
Answer from Xingzhi Guo:
I agree. There are many ways Deep Learning can be useful. Actually, if the network goes deeper, it can become harder to understand what has happened. But it's definitely very useful in terms of performance.
Thank you to all of our February 2022 speakers and our CIC Community audience members for keeping the conversation going!
Read a Summary of the February 2022 CIC Webinar