Photo of Zhongjun Ni

Zhongjun Ni

PhD student

Focus on digitalization of historic buildings to achieve energy optimization and smart maintenance through integrating advanced information and communication technologies, such as Internet of Things (IoT), Edge/Cloud Computing, and Machine Learning.

Presentation

Zhongjun Ni is currently a PhD student in Electrical Engineering with a specialization in Communication Electronics. His research interests include time series analysis, digital twins, and IoT solutions based on Edge-Cloud computing.

Zhongjun Ni received his licentiate degree from Linköping University, Sweden in 2023, as well as his M.Eng. and B.Eng. degrees from Zhejiang University, China, in 2017 and 2014, respectively. His master's program was to design a wireless measurement and control system specifically for agricultural use.

In 2017, Zhongjun joined Baidu as a software engineer, where he worked as a C++ programmer to develop a robust runtime framework, namely Apollo Cyber RT, for autonomous driving. Due to his outstanding performance, he was awarded the Best Newcomer in the entire business group. After the project was successfully delivered, he left Baidu and joined Microsoft to seek new challenges. At Microsoft, he worked to improve the automation rate of Azure datacenter network infrastructure buildout and ensure the reliability of Azure network infrastructure.

In 2020, Zhongjun joined the group of Professor Shaofang Gong at the Department of Science and Technology, Linköping University, for his PhD study, where he investigated digitalization solutions for energy optimization and smart maintenance of historic buildings. He also assisted in teaching undergraduate courses, such as Digital Electronics and Design (TNE094, HT 2022), Micro Computer Systems (TNE097, HT 2022, HT 2024), Signals and Systems (TNG015, VT 2024), and Microwave Engineering (TNE071, HT 2024).

Outside his research, Zhongjun has participated in several programming hackathons, mostly solving NP-hard combinatorial optimization problems. For example, he won first place at the Huawei Sweden Hackathon in 2023 and, together with his team, was granted a cash prize of 6,000 Euros.

Publications

2024

Chi Zhang, Zhongjun Ni, Christian Berger (2024) Spatial-Temporal-Spectral LSTM: A Transferable Model for Pedestrian Trajectory Prediction IEEE Transactions on Intelligent Vehicles, Vol. 9, p. 2836-2849 (Article in journal) Continue to DOI
Zhongjun Ni, Chi Zhang, Magnus Karlsson, Shaofang Gong (2024) Edge-based Parametric Digital Twins for Intelligent Building Indoor Climate Modeling 2024 IEEE 20th International Conference on Factory Communication Systems (WFCS) (Conference paper) Continue to DOI
Zhongjun Ni, Chi Zhang, Magnus Karlsson, Shaofang Gong (2024) A study of deep learning-based multi-horizon building energy forecasting Energy and Buildings, Vol. 303, Article 113810 (Article in journal) Continue to DOI

2023

Zhongjun Ni, Chi Zhang, Magnus Karlsson, Shaofang Gong (2023) Leveraging Deep Learning and Digital Twins to Improve Energy Performance of Buildings 2023 IEEE 3rd International Conference on Industrial Electronics for Sustainable Energy Systems (IESES) (Conference paper) Continue to DOI
Chi Zhang, Amir Hossein Kalantari, Yue Yang, Zhongjun Ni, Gustav Markkula, Natasha Merat, Christian Berger (2023) Cross or Wait? Predicting Pedestrian Interaction Outcomes at Unsignalized Crossings 2023 IEEE INTELLIGENT VEHICLES SYMPOSIUM, IV (Conference paper) Continue to DOI

Organisation