Borui Kang

Research Intern (RA)

Peking University (PKU)

Biography

I am a gap-year student applying for PhD position in artificial intelligence. Now I am working as a research intern (RA) supervised by Associate Prof. Jiaying Liu in Wangxuan Institute of Computer Technology, Peking University. My research interests mainly include stereo vision, general computer vision and other deep learning techniques. I received the B.Eng. degree in Civil Engineering from School of Civil Engineering, awarded excellent (优良) graduate of Tsinghua University, Beijing, China in June 2023, supervised by Assistant Prof. Chen GU. After that, I continued to pursue a PhD degree mainly in AI for seismology supervised by Chen in Institute of Disaster Prevention and Mitigation Engineering (IDPME), and quited in January 2024. Due to my unusual experiences mentioned above, I also have a certain interest in disaster prevention and mitigation, as well as AI for science.

Interests

Stereo Vision
Computer Vision
AI for Science
Deep Learning
Artificial Intelligence
Disaster Prevention and Mitigation

Education

Research Intern (RA), 03/2024 -
STRUCT, Wangxuan Institute of Computer Technology, Peking University (PKU)
PhD in Civil Engineering (Quit), 09/2023 - 01/2024
Institute of Disaster Prevention and Mitigation Engineering (IDPME), Department of Civil Engineering, Tsinghua University (THU)
BEng in Civil Engineering, 08/2019 - 06/2023
Department of Civil Engineering, Tsinghua University (THU)

Featured Publications

Zhe Zheng, Borui Kang, Qitian Yuan, Yucheng Zhou, Xinzheng Lu, Jiarui Lin

December, 2022 In ICCCBE

Text Mining-Based Patent Analysis for Automated Rule Checking in AEC

An article utilizes LDA and correlation analysis to study the themes in Chinese and English patents related to automated rule checking.

Recent & Upcoming Talks

WaveformMAE: Self-Supervised Learning for Fault-Inversion-Free Reconstruction of Ground Motion Waveforms Across the Entire Area

A study attempting to reconstruct seismic waveforms of various locations across an entire region using the self-supervised learning approach of MAE, without the need for inversion in geophysics.

Dec 13, 2023 8:30 AM — 12:50 PM Moscone Center, South, Poster Hall A-C, S31F-0409

Borui Kang, Peng Wu, Chen Gu, Yichen Zhong

WaveformMAE: Self-Supervised Learning for Fault-Inversion-Free Reconstruction of Ground Motion Waveforms Across the Entire Area

Projects

Exploring the Impact of Music on Driving Focus and Emergency Handling Ability Based on Driving Simulation: A Case Study of Novice Drivers

A study investigated the impact of music with different volumes and languages on driver behavior. Specifically, it examined factors such as reaction time to encountering vehicles running red lights or pedestrians suddenly crossing the road, as well as the ability to maintain a constant vehicle speed. A somewhat counterintuitive finding was that the study discovered that appropriate music might enhance drivers’ reaction speed rather than impede them.