Abstract In this talk I will present my current and future work towards enabling safe real-world autonomy. My core focus is to enable efficient and safe decision-making in complex autonomous […]
Abstract Today’s computer systems and their owners fail to protect data. Exacerbating this are new threats stemming from the rise of cloud computing. The consequences are dire: sensitive information like […]
Abstract Millimeter-wave and terahertz bands are emerging as the most promising spectrum to meet the data-rate and latency demands of future wireless applications, including virtual reality and autonomous cars. Moreover, […]
Synthetic biology has transformed how cells can be reprogrammed, providing a means to reliably and predictably control cell behavior with the assembly of genetic parts into more complex gene circuits. […]
Abstract: A wide range of application domains are emerging as computing platforms of all types become more ubiquitous in society. Many of these applications are data centric, and spend a […]
Abstract By enabling optical microsystems with new functionalities, improved system performance, and reduced size, weight, and power, integrated photonics is positioned to enable next-generation optical technologies that facilitate revolutionary advances […]
The computational modeling of complex multi-physics problems often requires specialized approaches in the formulation, implementation, and deployment of algorithms that lie outside the scope of conventional practice in physics-based modeling […]
The study of wind farms within realistic atmospheric boundary layer conditions is critical to understand the governing physics of the system and to design optimal operational protocols. Historically, control protocols […]
Abstract: Abstract: Much of our success in artificial intelligence stems from the adoption of a simple paradigm: specify an objective or goal, and then use optimization algorithms to identify a […]
Abstract: Deep learning (DL) is a powerful approach to modeling complex and large scale data. However, DL models lack interpretable quantities and calibrated uncertainty. In contrast, probabilistic graphical modeling (PGM) […]