Dr. Daifeng Wang won SBU-BNL Seed Grant on Large-Scale Comparative Regulatory Network Analysis in Photosynthetic Organisms
BMI faculty Dr. Daifeng Wang, together with Dr. Ian Blaby from Brookhaven National Laboratory, won the 2017 SBU-BNL SEED grant on "Large-Scale Comparative Regulatory Network Analysis in Photosynthetic Organisms".
BMI Grand Rounds: Shubham Jain, Ph.D.
Multi-Scale Motion-Derived Health Sensing
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Wang and Rosenthal Awarded $1.05M for Patient Risk Prediction Model Research
The Patient-Centered Outcomes Research Institute (PCORI) has announced a $1.05 million award to Fusheng Wang, professor in the departments of Biomedical Informatics and Computer Science, and his team, including Richard Rosenthal, MD, professor and addiction psychiatrist from the Depa
Improving Breast Cancer Diagnosis and Treatment with AI and Mathematical Models
Novel research supported by NCI could lead to more specific predictive disease models
A team of Stony Brook University researchers — led by two scientists in the Department of Biomedical Informatics in the Renaissance School of Medicine (RSOM) and College of Engineering and Applied Sciences (CEAS) — is developing a new way to analyze breast cancer imaging that incorporates mathematical modeling and deep learning. The approach will be much more interpretable and robust compared to previous methods.
Pathology Foundation Models & Open Source Pathology Tools - 2023 Wrap up
Stony Brook University has been at the forefront of developing innovative self supervised learning and diffusion methods to create Pathology foundation models for classification, segmentation and prediction tasks. In addition to our AI analysis pipelines and models, virtually all of which are publicly distributed, the group has created and distributed a variety of impactful tools.
IDEA Fellows Join Stony Brook Faculty
Alisa Yurovsky (Department of Biomedical Informatics, College of Engineering and Applied Sciences)
Challenging AI Conventions in Drug Discovery
Researchers from Stony Brook University’s Departments of Biomedical Informatics (BMI), Computer Science (CS), and Chemistry recently appeared in Nature Communications< for their work in molecular property prediction.
