Analyzing perturbed cell morphologies using deep learning
Presented by Matteo Di Bernardo, Cheeseman Lab, Whitehead Institute
Interpretable neural networks for single cell RNA sequencing analysis
Presented by Hunter King, Reddien Lab, Whitehead Institute
Whitehead Institute
McGovern Auditorium
455 Main Street
Cambridge, MA 02142
Wednesday, November 20, 2024
3:30 pm - 4:15 pm
Social mixer to follow. Free and open to the scientific community.
Matteo Di Bernardo Bio
Matteo Di Bernardo is a graduate student in the Cheeseman Lab, developing computational approaches for microscopy-based functional genomics screens. He combines scalable data processing methods with machine learning to analyze cellular mechanisms through high-throughput microscopy. His work currently focuses on morphological screens that probe fundamental cell biology processes, and he aims to apply these computational tools to more complex cellular states in development and cancer.
Hunter King Bio
Hunter joined the Reddien Lab as a graduate student in MIT’s Brain and Cognitive Sciences department, primarily studying the origin of cellular diversity in planarians. Since his graduation, he has continued his work by developing and applying machine learning methods to uncover signatures of cellular diversity in single cell transcriptomics data.
About the Whitehead Innovation Initiative
The Whitehead Innovation Initiative (WII) is a bold program advancing cutting-edge bio-AI leadership, which sponsors community-building and educational programs, funding opportunities, and computational resources at Whitehead Institute. The goal of the initiative is to spark innovation at the intersection of biomedical research and AI, foster partnerships between biomedical and computational researchers, facilitate collaboration, and support individual projects through expanded, state of the art computational infrastructure, educational resources, funding opportunities and social events.
