Harnessing Complexity

Advanced materials are increasingly embodying counterintuitive properties, such as extreme strength and super lightness, while additive manufacturing and other new technologies are vastly improving the ability to fashion these novel materials into shapes that would previously have been extremely costly or even impossible to create. Generating new designs that fully exploit these properties, however, has proven extremely challenging.

DARPA’s Information Innovation Office (I2O) is hosting a Proposers Day to provide information to potential proposers on the objectives of the upcoming Data-Driven Discovery of Models program. The program aims to develop semi-automated model discovery systems that enable non-expert users (i.e., users with subject matter expertise but no data science background) to create empirical models of real, complex processes. DARPA believes such a capability would increase the productivity of data scientists, and enable many more users to make predictions from data.

The Defense Advanced Research Projects Agency (DARPA) Defense Sciences Office (DSO) is sponsoring a Proposers Day to provide information to potential proposers on the objectives of an anticipated Broad Agency Announcement (BAA) for the TRAnsformative DESign (TRADES) program. The Proposers Day will be held on Friday, May 13, 2016 from 8:30 AM to 12:30 PM (EDT) at the Executive Conference Center (4075 Wilson Blvd. Suite 350 Arlington, VA 22203).

New manufacturing technologies such as additive manufacturing have vastly improved our ability to create shapes and material properties previously thought impossible. Generating new designs that fully exploit these properties, however, has proven extremely challenging. Conventional design technologies, representations, and algorithms are inherently constrained by outdated presumptions about material properties and manufacturing methods. As a result, today’s design technologies are simply not able to bring to fruition the enormous level of physical detail and complexity made possible with cutting-edge manufacturing capabilities and materials.

Dr. Reza Ghanadan joined DARPA in 2013 as a program manager in the Defense Sciences Office. He has interests in data analytics, autonomy, machine learning and artificial intelligence in information and cyber-physical systems. At DARPA, he has been investigating the mathematical foundations and applications of these technologies to complex science and engineering problems, ranging from precision genomics and neuroscience, to robotics and human-machine collaboration.