Nudges are interventions promoting healthy behavior without forbidding options or significant incentives. As an example of a nudge, the Apple Watch encourages users to stand by delivering a notification if […]
With the slowing of Moore's law, computer architects have turned to domain-specific hardware accelerators to improve the performance and efficiency of computing systems. However, programming these systems entails significant modifications […]
Ambitious targets on aggressive timelines have been heralded for the development of offshore wind energy in the United States, especially in New Jersey with a target of 11 GW (nearly […]
Quantum computers can solve important problems that are beyond the capability of conventional computers. Quantum computing is at an inflection point where small systems with a few tens qubits have […]
Can we accelerate convergence of gradient descent without changing the algorithm --- just by optimizing stepsizes? Surprisingly, we show that the answer is yes. Our proposed Silver Stepsize Schedule optimizes […]
Solid state spin qubits, in particular the nitrogen vacancy (NV) center in diamond, offer a path towards truly nanoscale imaging of condensed matter and biological systems with sensitivity to single […]
In this talk, I will present our recent efforts in probing the physical processes underlying self-assembly of colloidal gels and crystals. Nano-meter to micron sized particles in suspension can be […]
Climate change is a societal and political problem whose impact could be mitigated by technology. Underlying many of its technical challenges is a surprisingly simple yet challenging problem; modeling the […]
Many microorganisms and cells function in complex (non-Newtonian) fluids, which are mixtures of different materials that exhibit both viscous and elastic stresses. For example, mammalian sperm swim through cervical mucus […]
In this talk, we explain different roles that symmetries and approximate symmetries can play in machine learning models. We define approximately equivariant graph neural networks and we show a bias-variance […]
