GONG Xiao 2017-09-06T00:17:47+00:00

Gong Xiao is an Assistant Professor at the National University of Singapore (NUS). He obtained his B. Eng. (Hon.) degree in Electrical Engineering from the Beijing Institute of Technology (BIT), and his Ph. D. degree in Electrical Engineering from NUS in June 2013. He was also a Visiting Scholar at the Massachusetts Institute of Technology (MIT), from May to August 2014. Dr. Gong has published more than 100 papers in top conferences and journals, including 18 in IEDM and VLSI Symposium. His research interests include:

  • Metal-oxide-semiconductor field-effect-transistors (MOSFETs) with high mobility channels: exploitation of new materials and processing technology.
  • Advanced transistor structures: multiple-gate transistors such as FinFETs, nanowire (NW) FETs, and vertical FETs.
  • Heterogeneous integration of group IV and III-V metal-oxide-semiconductor high electron mobility transistors (MOS-HEMTs) for mixed signal applications and flexible electronic and photonic systems.
  • Opto-electro integrated devices and circuits
  • World’s first vertically stacked III-V nanowire CMOS on silicon platform
  • For sub-5 nm ‘technology node’ in year 2020 or beyond
  • Enabling Low Power and High Speed OEICs: First Monolithic Integration of InGaAs n-FETs and GaAs/AlGaAs Lasers on Si Substrate
  • World’s First Monolithic Integration of Ge P-FETs and InAs N-FETs on Si Substrate Using Ultra Thin Buffer Layer
  • The First GeSn FinFET on a Novel GeSnOI Substrate AchievingLowest S of 79 mV/decade and Record High Gm,int of 807 μS/μm for GeSn P-FETs (To be presented in VLSI Symposium 2017)
  • Record Low Specific Contact Resistivity (1.2×10-9 Ω-cm2) for P-type Semiconductors: Incorporation of Sn into Ge and In-Situ Ga Doping (To be presented in VLSI Symposium 2017)
  • World’s First GeSn Multiple Quantum Wells on Si Avalanche Photodiode
  • Germanium-Tin Heterojunction Phototransistor: Towards High-Efficiency Low-Power Photodetection in Short-Wave Infrared Range (VLSI 2016)
Click HERE for research information