Scholar
Tyler Lum
Google Scholar ID: kPq6-XIAAAAJ
Stanford University
Citations & Impact
Citations
268
H-index
6
i10-index
3
Publications
11
Co-authors
0
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- 1. Published paper: First author at Advances in Simplifying Medical UltraSound 2021 conference on developing an attention-based deep learning system to detect COVID-19 pneumonia from lung ultrasound videos, awarded Best Presentation - Runner-up.
Research Experience
- 1. Robotics R&D Intern at NVIDIA (Jun 2023 - Feb 2024): Designed and trained DextrAH-G, a safe, continuously reacting pixels-to-action policy.
- 2. Robotics R&D Intern at NVIDIA (May 2022 - Aug 2022): Built an obstacle-aware global navigation system for robotic arms.
- 3. Deep Reinforcement Learning Research at UBC Motion Control and Character Animation Lab (Sep 2021 - Jun 2022): Developed a quadruped robot control policy for discontinuous terrain.
- 4. Autopilot Software Engineering Intern at Tesla (May 2021 - Aug 2021): Developed safety-critical C++ software for Tesla’s Full Self-Driving Beta system.
- 5. Medical AI Research at UBC Robotics and Control Lab (Sep 2020 - Apr 2021): Spearheaded the development of an attention-based deep learning system for detecting COVID-19 pneumonia from lung ultrasound videos.
Education
- PhD: Stanford University, Computer Science, advised by Professor C. Karen Liu (The Movement Lab) and Professor Jeannette Bohg (Interactive Perception and Robot Learning (IPRL) Lab), supported by NSERC Postgraduate Scholarship; BSc: University of British Columbia (UBC), Engineering Physics, Wesbrook Scholar, advised by Professor Michiel van de Panne and Professor Purang Abolmaesumi.
Background
- Research Interests: Intelligent Robots, Elegant Motion, Interactive Perception, Dexterous Bi-Manual Manipulation, Reasoning through Uncertainty, Long-Horizon Planning, Creative Problem Solving, Common Sense Reasoning. Bio: 3rd year Computer Science PhD student at Stanford University, focusing on artificial intelligence and robotics.
Miscellany
- Long-term goal is to create robots that have some form of common sense reasoning, making them reliable enough to create tremendous value for people in their everyday lives.
Co-authors