Lili Meng
Scholar

Lili Meng

Google Scholar ID: JzNMKQoAAAAJ
Postdoc of Computer Science, University of British Columbia
Large Language ModelsComputer VisionTime Series forecastingRobotics
Citations & Impact
All-time
Citations
1,633
 
H-index
16
 
i10-index
18
 
Publications
20
 
Co-authors
30
list available
Resume (English only)
Academic Achievements
  • Publications: - Multi-level Residual Networks from Dynamical Systems View (ICLR 2018)- Reversible Architectures for Arbitrarily Deep Residual Neural Networks (AAAI 2018)- Exploiting Point and Line Features in Regression Forests for Camera Relocalization (IROS 2018)- Backtracking Regression Forests for Accurate Camera Relocalization (IROS 2017)- Autonomous Mobile Robot Navigation in Uneven and Unstructured Indoor Environments (IROS 2017)- The Raincouver scene parsing benchmark for self-driving in adverse weather and at night (IEEE Robotics and Automation Letters, 2017)- Learning Motion Predictors for Smart Wheelchair using Auto-regressive Sparse Gaussian Process (ICRA 2018)- Exploiting Random RGB and Sparse Features for Camera Pose Estimation (BMVC 2016)Awards: - Ranked 5th globally and 1st in North America in the MIT Moments in Time Challenge.
Research Experience
  • Research Scientist at Xtract Technologies; Postdoc Fellow at the University of British Columbia's Computer Science Department; Visiting Scientist at Cornell University.
Education
  • Ph.D. in Robotics from the Institute for Computing, Information and Cognitive Systems at the University of British Columbia, under the supervision of Prof. Clarence W. de Silva, Prof. James J. Little, and Prof. Ian M. Mitchell.
Background
  • Research Interests: Machine Learning, Computer Vision, and Robotics. Background: A research scientist at Xtract Technologies and a postdoc fellow at the University of British Columbia's Computer Science Department, working with Prof. Leonid Sigal and Prof. Eldad Haber on deep learning and computer vision. Previously, she worked as a visiting scientist at Cornell University with Prof. Kilian Weinberger on Bayesian optimization and deep learning.
Miscellany
  • Interests: Reading, running, swimming, playing the violin and piano, getting together with friends and family, table tennis, karate, yoga, dancing, biking, hiking, etc.