Welcome to my website!
Leonel Rozo
Lead Research scientist @ Bosch center for AI
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I love machine learning and robotics!
When I started my studies in Colombia, I got excited about how the future in AI and robotics would look like. Passion, endurance and great mentors have led me to work on what I love: research the intersection of machine learning and robotics. I envision a world where smart robots augment our capabilities at physical, cognitive, and social levels! AI and robots that can easily assist, help, and empower people in a large diversity of scenarios and tasks. To make this dream come true, I spend my days working on machine learning tools that allow robots to naturally and smartly interact with their environment and humans. Day by day, I hit the books and investigate machine learning methods, robot control, differential geometry and optimization. |
News and updates!
[January, 2025] What a way to start the year! Our first paper at AISTATS! This time, we could not be more Riemannian! Check out our new paper "Riemann2: Learning Riemannian Submanifolds from Riemannian Data".
[May 2, 2024] So happy we made it in ICML'24! If you are curious about how motion taxonomies can be leveraged to build taxonomy-aware embeddings in hyperbolic manifolds, then check out our new paper on "Bringing Motion Taxonomies to Continuous Domains via GPLVM on Hyperbolic manifolds".
[January, 2024] Good news from ICRA'24! My partner in crime and I will be talking about "The Single Tangent Space Fallacy", a paper about technically-sound practices when applying Riemannian geometry in robot learning problems. See you in Japan!
[January, 2024] Super happy about Hadi's paper accepted as a spotlight in ICLR'24! We propose "Neural Contractive Dynamical Systems", a new method to learn low-dimensional dyn. systems in a VAE latent space with contraction-stability guarantees, and it works in the SE(3) Lie group!
[January, 2024] ICRA'24 will host the second edition of our tutorial on Riemannian manifolds applied in robot learning, optimization a control! We are so excited to meet you in Japan and talk about what is and how to exploit Riemannian methods in robotics problems.
[May 2, 2024] So happy we made it in ICML'24! If you are curious about how motion taxonomies can be leveraged to build taxonomy-aware embeddings in hyperbolic manifolds, then check out our new paper on "Bringing Motion Taxonomies to Continuous Domains via GPLVM on Hyperbolic manifolds".
[January, 2024] Good news from ICRA'24! My partner in crime and I will be talking about "The Single Tangent Space Fallacy", a paper about technically-sound practices when applying Riemannian geometry in robot learning problems. See you in Japan!
[January, 2024] Super happy about Hadi's paper accepted as a spotlight in ICLR'24! We propose "Neural Contractive Dynamical Systems", a new method to learn low-dimensional dyn. systems in a VAE latent space with contraction-stability guarantees, and it works in the SE(3) Lie group!
[January, 2024] ICRA'24 will host the second edition of our tutorial on Riemannian manifolds applied in robot learning, optimization a control! We are so excited to meet you in Japan and talk about what is and how to exploit Riemannian methods in robotics problems.
