Junru Lin

I’m a final-year undergraduate studying Computer Science and Mathematics at the University of Toronto. I’m broadly interested in computer vision and graphics, with a particular focus on 3D reconstruction, probabilistic modeling, and deep learning. Currently, I’m working with Prof. Leonidas J. Guibas and Prof. Ke Li on exciting projects in 3D vision.

Previously, I had the opportunity to collaborate with Prof. Luc Van Gool and Dr. Danda Pani Paudel on NeRF-SLAM. My research journey in 3D vision began under the guidance of Prof. David B. Lindell and Prof. Igor Gilitschenski. I also had the pleasure of working with Prof. Kyros Kutulakos on computational imaging.

I gained industry experience through a year-long internship as a machine learning researcher at Deep Genomics/. Earlier in my undergrad studies, I conducted research with Lisa Jeffrey and Prof. Carolyn Sealfon, and worked as a web developer with Prof. David Liu.

I am passionate about mentoring junior students and helping them explore research opportunities at UofT and beyond. If you ever want to chat about research (or anything else!), feel free to reach out: junru.lin@mail.utoronto.ca.

news

Jun 30, 2024	One paper accepted to IROS!
May 1, 2022	I start my internship at the Dynamic Graphics Project Lab!
Sep 1, 2020	I start my undergrad at the University of Toronto! 🎓

selected publication

SIURO
Rapid Testing in COVID and Modified SIR Model

Chen, J.*, Li, R.* and Lin, J.*

SIAM Undergraduate Research Online, 2022

Abs Web PDF Bib

The COIVD pandemic has swept the globe since 2019, posing a grave threat to human life. There are multiple ways for the government to control the pandemic, including promoting the vaccination, limiting the number of people in public places, requiring people to wear masks in public places, and suggesting infected people isolate themselves. In this paper, we used a compartmental model to analyze the spread of COVID-19 under the promotion of rapid tests. The result shows that popularization of rapid tests may have a significant impact on controlling the pandemic. With an estimated minimum requirement for the use of rapid tests, we are able to put forward suggestions on reasonable ways to curtail the pandemic.
@article{covid, title = {Rapid Testing in COVID and Modified SIR Model}, author = {{Chen, J.*, Li, R.* and Lin, J.*}}, journal = {SIAM Undergraduate Research Online,}, volume = {15}, year = {2022}, doi = {10.1137/21S1460399}, publisher = {Society for Industrial and Applied Mathematics,}, }

IROS

Ternary-type Opacity and Hybrid Odometry for RGB-only NeRF-SLAM

Junru Lin, Asen Nachkov, Songyou Peng, and 2 more authors

2023

Bib

@misc{lin2023ternarytypeopacityhybridodometry,
  title = {Ternary-type Opacity and Hybrid Odometry for RGB-only NeRF-SLAM},
  author = {Lin, Junru and Nachkov, Asen and Peng, Songyou and Gool, Luc Van and Paudel, Danda Pani},
  year = {2023},
  eprint = {2312.13332},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
}