Skip to main content

Search

Show all results for

Home

Person

Jing Zhang

This person is no longer with EPFL

About
Privacy
Disclaimer

Copyright © 2026 EPFL, all rights reserved

Graph Chatbot

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related publications (5)

Please note that this is not a complete list of this person’s publications. It includes only semantically relevant works. For a full list, please refer to Infoscience.

Wafer-scale MoS2 with water-vapor assisted showerhead MOCVD

Andras Kis, Aleksandra Radenovic, Yanfei Zhao, Michal Daniel Macha, Mukeshchand Thakur, Jing Zhang, Mukesh Kumar Tripathi, Hyungoo Ji

Among numerous thin film synthesis methods, metalorganic chemical vapor deposition performed in a showerhead reactor is the most promising one for broad use in scalable and commercially adaptable two-dimensional material synthesis processes. Adapting the m ...

ROYAL SOC CHEMISTRY2022

Super-resolved Optical Mapping of Reactive Sulfur-Vacancies in Two-Dimensional Transition Metal Dichalcogenides

Andras Kis, Aleksandra Radenovic, Magalí Alejandra Lingenfelder, Jean Camille Benjamin Comtet, Martina Lihter, Yanfei Zhao, Michal Daniel Macha, Karla Banjac, Jing Zhang, Zhenyu Wang, Miao Zhang, Tzu-Heng Chen

Transition metal dichalcogenides (TMDs) represent a class of semiconducting two-dimensional (2D) materials with exciting properties. In particular, defects in 2D-TMDs and their molecular interactions with the environment can crucially affect their physical ...

AMER CHEMICAL SOC2021

Learning Saliency From Single Noisy Labelling: A Robust Model Fitting Perspective

Jing Zhang, Tong Zhang

The advances made in predicting visual saliency using deep neural networks come at the expense of collecting large-scale annotated data. However, pixel-wise annotation is labor-intensive and overwhelming. In this paper, we propose to learn saliency predict ...

2021