ENG: Algorithms developed in Cornell’s Laboratory for Intelligent Systems and Controls can predict the in-game actions of volleyball players with more than 80% accuracy, and now the lab is collaborating with the Big Red hockey team to expand the research project’s applications. The algorithms are unique in that they take a holistic approach to action anticipation, combining visual data – for example, where an athlete is located on the court – with information that is more implicit, like an athlete’s specific role on the team.
Category: Engineering
When making a detour is faster
ENG: Autonomous optimal navigation of microswimmers is in fact possible, as researchers from the Max Planck Institute for Dynamics and Self-Organization showed. In contrast to the targeted navigation of boats, the motion of swimmers at the microscale is strongly disturbed by fluctuations. The researchers now described a navigation strategy for microswimmers that does not need an external interpreter. Their findings may contribute to the understanding of transport mechanisms in the microcosm as well as to applications such as targeted drug delivery.
Upgrading your Computer to Quantum
ENG: The processes used to manufacture conventional silicon microprocessors have matured over decades and are constantly being refined and improved. In contrast, most quantum computing architectures must be designed mostly from scratch. However, finding a way to add quantum capabilities to existing fabrication lines, or even integrate quantum and conventional logic units in a single chip, might be able to vastly accelerate the adoption of these new systems.
Machine learning generates 3D model from 2D pictures
ENG: Researchers from the McKelvey School of Engineering at Washington University in St. Louis have developed a machine learning algorithm that can create a continuous 3D model of cells from a partial set of 2D images that were taken using the same standard microscopy tools found in many labs today. The key to this work was the use of a neural field network, a particular kind of machine learning system that learns a mapping from spatial coordinates to the corresponding physical quantities. When the training is complete, researchers can point to any coordinate and the model can provide the image value at that location.
