Scrolling for the Truth: Banerjee Builds AI Tool to Verify Scientific Claims on Social Media
Stony Brook, NY, February 22, 2026 — Scroll through Instagram or X long enough, and you’ll see it — a reel insisting that “fruits are citrus, so you shouldn’t eat them with milk,” a thread warning “protein shakes wreck kidney function,” a carousel promising “this workout routine will fix your PCOS in 30 days.” Every third post seems to offer a health hack, often backed by a chart, a DOI link, and just enough scientific language to sound convincing.
But behind those posts is a tangle of dense scientific research that few people ever read.
How Much Does AI Really Understand: Stress-testing Neural Networks with 1,800 Language Patterns
Stony Brook, NY, February 13, 2026 — In his office lined with hand-drawn diagrams and alphabet-like symbols, Stony Brook researcher Jeffrey Heinz is trying to answer a deceptively simple question: How well, exactly, can today’s neural networks learn, and where do they fail?
Stony Brook Researchers Working to Make AI More Efficient at Complex Problems
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Researchers at Stony Brook University are working to improve how artificial intelligence systems think through multi-step problems, which can help AI perform better in real-world environments.