Zhongjun Ni

Zhongjun Ni

PhD Student

Linköping University

Biography

Zhongjun Ni is currently a Ph.D. student under the supervision of Prof. Shaofang Gong and Sr. Assoc. Prof. Magnus Karlsson with the Department of Science and Technology, Linköping University. His research interests include digital twin, edge computing, Internet of Things, time series analysis, and optimization. He received his B.Eng. and M.Eng. degrees from Zhejiang University, Hangzhou, China, in 2014 and 2017, respectively. Between April 2017 and July 2020, he worked as a software engineer in the industry and applied for three U.S. patents for his work in distributed systems.

Interests
  • Digital Twin
  • Edge Computing
  • Internet of Things
  • Time Series Analysis
  • Optimization
Education

  • PhD Student, 2020 - Present

    Linköping University, Sweden

  • Master of Engineering, 2017

    Zhejiang University, China

  • Bachelor of Engineering, 2014

    Zhejiang University, China

Experience

 
 
 
 
 
Linköping University
PhD Student
Linköping University
Aug 2020 – Present Norrköping, Sweden

Responsibilities include:

  • Work within research projects.
  • Assist in teaching courses Digital Electronics and Design (TNE094) and Microcomputer Systems (TNE097).
 
 
 
 
 
Microsoft
Software Engineer II
Microsoft
Apr 2019 – Jul 2020 Beijing, China

Responsibilities include:

  • Manage Azure network infrastructure metadata.
  • Design and implement new network infrastructure metadata buildout scenarios.
  • Ensure Azure network infrastructure availability and business continuity.
 
 
 
 
 
Baidu
Senior Software R&D Engineer
Baidu
Nov 2017 – Apr 2019 Beijing, China

Responsibilities include:

  • Design and implement adaptive message-oriented middleware in distributed systems.
  • Implement a message recording tool, which supports the recording, extraction and playback of messages.
  • Expand influence for Apollo and Cyber RT.

Projects

Digitalization framework for energy optimization and smart maintenance of historic buildings
This project aims to develop a cloud-based digitalization framework for energy optimization and smart maintenance of historic buildings. Within the project, digital twins corresponding to three selected historic buildings in Norrköping will be created and artificial intelligence will be developed. The project is expected to provide a deeper understanding of the operating and use conditions for historic buildings and make it possible to automatically control the building’s heating depending on internal heat loads and other specific operating conditions.
Minerva

Recent Publications

Zhongjun Ni, Chi Zhang, Magnus Karlsson, Shaofang Gong (2023). A study of deep learning-based multi-horizon building energy forecasting. In Energy and Buildings.

PDF DOI

Zhongjun Ni, Chi Zhang, Magnus Karlsson, Shaofang Gong (2023). Leveraging Deep Learning and Digital Twins to Improve Energy Performance of Buildings. In the 3rd IEEE International Conference on Industrial Electronics for Sustainable Energy Systems.

PDF DOI

Zhongjun Ni, Yu Liu, Magnus Karlsson, Shaofang Gong (2022). Enabling Preventive Conservation of Historic Buildings Through Cloud-based Digital Twins: A Case Study in the City Theatre, Norrköping. In IEEE Access.

PDF Cite DOI

Zhongjun Ni, Yu Liu, Magnus Karlsson, Shaofang Gong (2022). Link Historic Buildings to Cloud with Internet of Things and Digital Twins. In EEHB 2022.

PDF Cite Slides

Zhongjun Ni, Yu Liu, Magnus Karlsson, Shaofang Gong (2021). A Sensing System Based on Public Cloud to Monitor Indoor Environment of Historic Buildings. In Sensors.

PDF Cite DOI

Zhongjun Ni, Petra Eriksson, Yu Liu, Magnus Karlsson, Shaofang Gong (2021). Improving energy efficiency while preserving historic buildings with digital twins and artificial intelligence. In SBE21 Sustainable Built Heritage.

PDF Cite DOI

Achievements

  • Huawei Sweden Hackathon 2023, 1st place out of 170+ registrants with 6,000 Euro prize, 2023.
  • Huawei Sweden Hackathon 2022, 3rd place out of 160+ registrants with 10,000 SEK prize, 2022.
  • Huawei Sweden Hackathon 2021, 3rd place out of 200+ registrants with 10,000 SEK prize, 2021.
  • Best Newcomer, Baidu, 2018.
  • Excellent Postgraduate Students’ Award, Zhejiang University, 2017.

Contact