Barbara Engelhardt, a computer scientist at Princeton University, explains why traditional machine-learning techniques have often fallen short for genomic analysis, and how researchers are overcoming that challenge.
The lauded astronomer Jim Gunn explains how a new spectrograph he is building will advance astronomy.
Jennifer Dunne of the Santa Fe Institute explains how reconstructions of food webs in past ecosystems help ecologists understand both the unusual niche of humans and new clues to a more sustainable civilization.
Jennifer Doudna, one of the coinventors of CRISPR technology, discusses how her work on bacterial defenses against viruses helped lead to a discovery with a revolutionary impact on biological research.
Priyamvada Natarajan explains the role of supermassive black holes in the structure and evolution of the universe.
Physicists use the Navier-Stokes equations to describe fluid flows, taking into account viscosity, velocity, pressure and density. But because of turbulence in fluids, proving that the equations always make sense is one of the hardest problems in physics and mathematics.
Carolina Araujo describes the effort to build a network of women mathematicians in Brazil.
Google Brain’s Been Kim is building ways to let us interrogate the decisions made by machine learning systems.
How do extraordinarily complex emergent phenomena — like ants assembling themselves into living bridges, or tiny water and air molecules forming into swirling hurricanes — spontaneously arise from systems of much simpler elements? The answer often depends on a transition in the interplay between the elements that resembles a phase change.
Meenakshi Wadhwa explains how meteorites illuminate the origins of Earth and the rest of the solar system.