Hi! I'm Clément, a second-year PhD student at MIT CSAIL where I work in the Algorithmic Design Group under the supervision of Mina Konaković Luković. I'm broadly interested in computer graphics and its intersections with machine learning. My research bridges design, generative modeling, and physics-based simulation by developing new methods to create physically sound, functional, and fabricable objects, metamaterials, and robots.
Before MIT, I earned an engineering degree from École Polytechnique in Paris and an M.Sc. in Computer Science from ETH Zürich. I also gained research experience as a research intern with the GraphDECO team at Inria, a research intern at NVIDIA Research, and a visiting student at the 3D Vision Lab of Seoul National University.
In my free time, I enjoy running (sometimes with a compass and a map 🗺️), cycling up (and, mercifully, down) steep hills 🚴, hiking mountains (or just stairs) ⛰️, reading random research papers and delicious cookbooks 📖, watching movies (especially very niche ones) 🎥, and most importantly talking and socializing 👋. So if you want to chat or grab a beer, count me in! 🍻
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MIT
Computer Science and Artificial
Intelligence Laboratory
PhD program
Supervised by Prof.
Mina Konaković Luković in the Algorithmic Design Group
September 2024 - now
ETH Zürich
Department of Computer Science
Master of Science
Major in Visual and Interactive Computing, Minor in Machine Learning
September 2022 - August 2024
École polytechnique
Department of Computer Science
Postgraduate engineering degree
Major in Image, Vision and Learning
September 2019 - August 2023
PhysiOpt: Physics-Driven Shape Optimization for 3D
Generative Models (SIGGRAPH Asia 2025)
Sean Zhan*,
Clément Jambon*,
Evan Thompson,
Kenney Ng,
Mina Konaković Luković, *equal
contribution
PhysiOpt is a differentiable physics optimizer that improves the physical integrity
of 3D
generative model outputs by operating directly in the latent space of shape priors. It
builds on FEM to incorporate user-specified loads and constraints while enabling fast and
semantic-preserving optimization to retain the creative capabilities of generative modeling.
Project page (Soon)
|
Paper
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Code (Soon)
BrepDiff: Single-stage B-rep Diffusion
Model (SIGGRAPH 2025)
Mingi Lee*,
Dongsu Zhang*,
Clément Jambon*,
Young Min Kim, *equal contribution
BrepDiff is a simple, single-stage diffusion model for generating Boundary Representations
(B-reps). It generates B-reps by denoising point-based face samples with a
dedicated noise schedule. Unlike multi-stage methods, BrepDiff enables intuitive, editable
geometry creation, including completion, merging, and interpolation, while achieving competitive
performance on unconditional generation.
Project page
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Paper
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Video
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Code
NeRFshop: Interactive Editing of
Neural Radiance Fields (I3D 2023)
Clément Jambon,
Bernhard Kerbl,
Georgios Kopanas,
Stavros Diolatzis,
Thomas Leimkühler,
George Drettakis
NeRFshop is an end-to-end method that allows users to interactively select and
deform objects through cage-based transformations within NeRFs. Once complete, edits can be
collapsed and
saved as a portable NeRF representation through a distillation process.
Project page
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Paper
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Video
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Talk
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Slides
Neural Point
Catacaustics for Novel-View Synthesis of Reflections (SIGGRAPH Asia 2022)
Georgios Kopanas,
Thomas Leimkühler,
Gilles Reiner,
Clément Jambon,
George Drettakis
Neural Point Catacaustics is a new point-based representation that allows novel-view
synthesis of scenes with curved reflectors, from a set of casually-captured
input.
Project page
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Paper
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Video
3D Vision Lab
Visiting Research Student
Supervisor: Young Min Kim
February 2024 - August 2024
NVIDIA
Research Intern
Supervisors: Thomas Müller and Merlin Nimier-David
October 2023 - February 2024
Inria
-
GraphDeco Team
Research Intern
Supervisor: George Drettakis
March 2022 - August 2022
Wemap
Computer Vision Engineer (Internship)
Supervisor: Thibaud Michel
June 2021 - August 2021
Institute of Technology of Cambodia
Teacher and Research Assistant (Internship)
October 2019 - March 2020