• Stochastic first order methods for distributed composite optimization with differential privacy 

  Sutcher-Shepard, Colin (Rensselaer Polytechnic Institute, Troy, NY, 2023-08)

  ABSTRACTDistributed optimization has gained much attention over recent years as the world generates ever more data. At the same time machine learning methods are able to solve many new problems. As the desire to train ...

• Human-building collaboration: a case study on lighting enabled collaborative system design 

  Varsami, Constantina (Rensselaer Polytechnic Institute, Troy, NY, 2023-08)

  Building automation systems have gained increased attention by means of their ability to improve building performance. They increasingly rely on cutting-edge technologies, sensors, and the Internet of Things to autonomously ...

• Defect engineering for tuning electronic and optical properties of materials 

  Ward, Zachary, D (Rensselaer Polytechnic Institute, Troy, NY, 2023-08)

  All pristine nanostructured materials are susceptible to disruptions in their chemical composition and expected crystal structure, where these disruptions are commonly referred to as defects. At first glance, defects may ...

• Electrical resistivity size effect in compound conductors 

  Zhang, Minghua (Rensselaer Polytechnic Institute, Troy, NY, 2023-06)

  The downscaling of modern integrated circuits is facing a major challenge posed by the resistivity size effect in interconnect lines which is mainly due to electron scattering at surfaces and grain boundaries. The resistivity ...

• Spectral ct at ultra-high resolution via photon-counting and deep learning 

  Li, Mengzhou (Rensselaer Polytechnic Institute, Troy, NY, 2023-08)

  Computed tomography (CT) plays an indispensable role in the clinical diagnosis and treatment of diseases. Enabled by recent dual-energy CT (DECT) advances, spectral CT allows anatomical and functional imaging with material ...

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