First-generation graduate Brittany Rodriguez advances manufacturing scie...
Joe Tuccillo, a human geography research scientist, leads the UrbanPop project that uses census data to create synthetic populations. Using a Python software suite called Likeness on ORNL’s high-performance computers, Tuccillo’s team generates a population with individual ‘agents’ designed to represent people that interact with other agents, facilities and services in a simulated neighborhood.
Two ORNL teams recently completed Cohort 18 of Energy I-Corps, an immersive two-month training program where the scientists define their technology’s value propositions, conduct stakeholder discovery interviews and develop viable market pathways.
The contract will be awarded to develop the newest high-performance computing system at the Oak Ridge Leadership Computing Facility.
Brittany Rodriguez never imagined she would pursue a science career at a Department of Energy national laboratory. However, after some encouraging words from her mother, input from key mentors at the University of Texas Rio Grande Valley, or UTRGV, and a lot of hard work, Rodriguez landed at DOE’s Manufacturing Demonstration Facility, or MDF, at Oak Ridge National Laboratory.
ORNL hosted the Mid-South Regional Chapter of the American Society for Photogrammetry and Remote Sensing, or ASPRS. Participants spanning government, academia and industry engaged in talks, poster sessions, events and workshops to further scientific discovery in a field devoted to using pictures to understand changes to the earth’s inhabitants and landscape.
A newly established internship between ORNL and Maryville College is bringing cybersecurity careers to a local liberal arts college. The internship was established by a Maryville College alumni who recently joined ORNL.
As a data scientist, Daniel Adams uses storytelling to parse through a large amount of information to determine which elements are most important, paring down the data to result in the most efficient and accurate data set possible.
Oak Ridge National Laboratory scientists have developed a method leveraging artificial intelligence to accelerate the identification of environmentally friendly solvents for industrial carbon capture, biomass processing, rechargeable batteries and other applications.
Despite strong regulations and robust international safeguards, authorities routinely interdict nuclear materials outside of regulatory control. Researchers at ORNL are exploring a new method that would give authorities the ability to analyze intercepted nuclear material and determine where it originated.
Researchers used quantum simulations to obtain new insights into the nature of neutrinos — the mysterious subatomic particles that abound throughout the universe — and their role in the deaths of massive stars.