Nathan Youngblood

Department of Electrical and Computer Engineering, University of Pittsburgh
PhD in Electrical and Electronics Engineering, University of Minnesota, 2016

Dr. Youngblood will join the Electrical and Computer Engineering Department at the University of Pittsburgh as a tenure-track assistant professor in September 2019. He received his PhD in electrical engineering from the University of Minnesota where his research focused on integrating 2D materials with silicon photonics for high-speed optoelectronic applications. From 2017 to 2019, he worked as a postdoctoral researcher at the University of Oxford developing phase-change photonic devices for integrated optical memory and computation. His research interests include bi-stable optical materials, 2D material optoelectronics, and photonic architectures for machine learning.

Most Cited Publications
  1. "Waveguide-integrated black phosphorus photodetector with high responsivity and low dark current."  Nathan Youngblood, Che Chen, Steven J Koester, and Mo Li.  Nature Photonics 9.4 (2015).
  2. "Multifunctional graphene optical modulator and photodetector integrated on silicon waveguides."  Nathan Youngblood, Yoska Anugrah, Rui Ma, Steven J Koester, and Mo Li.  Nano Letters 14.5 (2014).
  3. "Three-dimensional integration of black phosphorus photodetector with silicon photonics and nanoplasmonics."  Che Chen, Nathan Youngblood, Ruoming Peng, Daehan Yoo, Daniel A Mohr, Timothy W Johnson, Sang-Hyun Oh, and Mo Li.  Nano Letters 17.2 (2017).
  4. "Layer-tunable third-harmonic generation in multilayer black phosphorus."  Nathan Youngblood, Ruoming Peng, Andrei Nemilentsau, Tony Low, and Mo Li.  ACS Photonics 4.1 (2016).
  5. "Midinfrared electro-optic modulation in few-layer black phosphorus."  Ruoming Peng, Kaveh Khaliji, Nathan Youngblood, Roberto Grassi, Tony Low, and Mo Li.  Nano Letters 17.10 (2017).
Recent Publications
  1. "Phase change photonics for brain-inspired computing," N Youngblood, Z Cheng, N Farmakidis, X Li, J Tan, and H Bhaskaran.  Micro and Nanotechnology Sensorys, Systems, and Applications XI (2019)
  2. "All-photonic in-memory computing based on phase-change materials,"  C Rios, N Youngblood, Z Cheng, M Le Gallo, WHP Pernice, CD Wright, A Sebastian and H Bhaskaran.  CLEO: Science and Innovations (2019)
  3. "All-optical spiking neurosynaptic networks with self-learning capabilities," J Feldmann, N Youngblood, CD Wright, H Bhaskaran, and WHP Pernice.  Nature 569 (2019)
  4. "Non-volatile silicon photonic memory with more than 4-bit per cell capability," X Li, N Youngblood, CD Wright, WHP Pernice, and H Bhaskaran.  arXiv 1904.12740 (2019)
  5. "Integrated Phase-change Photonics: A Strategy for Mergin Communication and Computing,"  CD Wright, H Bhaskaran, WHP Pernice, SGC Carrillo, E Gemo, A Baldycheva, Z Cheng, X Li, C Rios, N Youngblood, J Feldmann, N Gruhler, and M Stegmaier.  Optical Fiber Communication Conference M1D.3 (2019)

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