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Robert Ren I'm a undergraduate reserach intern at the Toronto Robotics and AI Lab (TRAIL) supervised by Professor Steven Waslander. Previously, I have interned at Toronto Intelligent Systems Lab at the University of Toronto, supervised by Professor Igor Gilitschenski and the FORCOLAB, supervised by Professor Shurui Zhou. I'm also the 3D object detection team lead (LiDAR + Radar) at University of Toronto's autonomous driving team, aUToronto, where we aim to achieve level 4 autonomy. My current research focuses on the intersection of Gaussian Splatting and Diffusion Models. I'm interested in how we can leverage the rich diffusion prior to significantly improve the accuracy and speed of generative reconstructions.
Note: I'm actively looking for PhD positions starting in Fall 2025. Please feel free to reach out if you are interested in taking me as a PhD student! |
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ResearchI'm interested in computer vision and generative models. You can find my research projects and papers below. |
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Project on 3D Gaussian Splatting
In progress Details coming soon... |
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AvatarOne: Monocular 3D Human Animation
Akash Karthikeyan, Robert Ren, Yash Kant, Igor Gilitschenski WACV, 2024 Fast and robust solution for both surface modeling and novel-view animation. |
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SWTrack: Multiple Hypothesis Sliding Window
3D Multi-Object Tracking
Sandro Papais, Robert Ren, Steven Waslander ICRA, 2024 Graph-based optimization method that uses additional temporal information to prevent missed objects and improve the performance of tracking methods, especially when objects are occluded in the current viewpoint. |
Projects |
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ContactNet: Pedestrian Detection and Person Re-identification University of Toronto, APS360 Course Project | May, 2022 - August 2022 |
Experience |
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Toronto Robotics and AI Laboratory Research Intern | Aug, 2023 - Present Working on 3D Gaussian Splatting with Diffusion Models. Prior to this project, I worked on LiDAR-based 3D object tracking. |
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Toronto Intelligent Systems Lab Research Intern | Jan, 2023 - June, 2024 Worked on Neural Radience Fields (NeRFs) and diffusion models. |
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FORCOLAB Research Intern | May, 2022 - August, 2022 Researched on the disclosure patterns of OSS vulnerabilities on official vulnerability websites and social media, along with heuristics for predicting undisclosed software vulnerabilities. |
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aUToronto, University of Toronto's autonomous driving team Radar Object Detection Lead | August, 2023 - present Integrating radar detections into the current perception pipeline to improve the object tracking performance and aid perception under adverse weather. |
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aUToronto, University of Toronto's autonomous driving team 3D Object Detection Developer | August, 2022 - May, 2023 Develop and research on LiDAR-based 3D object detection method. Placed first in the perception challenge in the SAE autonomous driving competition. |
Education |
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University of Toronto BASc. in Engineering Science | 2020 - 2025 Robotics Major, Machine Intelligence Minor |
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