Research
Cardiovascular disease is the leading cause of death in New York State. Early detection is critical, yet diagnosis often depends on interpreting complex imaging data that can require significant time and expertise. The AI models Prof Yan and his team have developed analyze imaging and patient data together to deliver faster, more accurate diagnostics.
University at Buffalo researcher Thomas Grant has been awarded a $2.18 million federal grant to create a new artificial intelligence-powered tool that improves scientists’ understanding of how proteins move and change shape within the human body.
In today’s AI arms race, bigger often wins. Tech companies compete to build ever-larger models trained on massive datasets, pouring resources into compute infrastructure and experimentation. But Hongseok Namkoong, Assistant Professor in the Decision, Risk, and Operations Division at Columbia Business School and a member of the Data Science Institute, is taking a different approach—one that could reshape how AI systems are trained in the first place.
We need to learn our letters before we can learn to read and our numbers before we can learn how to add and subtract. The same principles are true with AI, a team of New York University scientists has shown through laboratory experiments and computational modeling.
