Monte Carlo Method Dispenses With Troublesome Meshes   Carnegie Mellon University researchers have shown complex shapes need not be divided into intricate meshes, left, to perform geometric analysis. Instead of spending 14 hours creating a mesh, they use Monte Carlo methods to get initial[...]

RoadBotics selected for its contribution to the field of asset management! The World Economic Forum announced its selection of 100 of the most promising Technology Pioneers of 2020, who are shaping industries from agriculture to healthcare while also working on sustainability issues and much more.[...]

              Nominated by: Aaron Steinfeld and Students “She’s an organized and knowledgeable powerhouse...absolute pleasure to interact with...is not only appreciated, but adored...I honestly hope that I will be able to work with someone as amazing as her when I graduate[...]

Additional Data Boosts Accuracy of Tracking Other Cars, Pedestrians PITTSBURGH—For safety's sake, a self-driving car must accurately track the movement of pedestrians, bicycles and other vehicles around it. Training those tracking systems may now be more effective thanks to a new method developed at Carnegie[...]

What a Perception System Doesn't See Can Help It Understand What It Sees                   PITTSBURGH—It's important that self-driving cars quickly detect other cars or pedestrians sharing the road. Researchers at Carnegie Mellon University have shown that they[...]

              Nominated by: Jessica Kaminsky“ ...has initiated several study groups focused on building empathy, understanding gender and race, and examining the role of a university in community and system-level change...values justice, compassion, and dreaming...extremely high work ethic and commitment[...]