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GenPhi : 3D Generative AI conditioned by geometry, structure and physics


Thesis topic details

General information

Organisation

The French Alternative Energies and Atomic Energy Commission (CEA) is a key player in research, development and innovation in four main areas :
• defence and security,
• nuclear energy (fission and fusion),
• technological research for industry,
• fundamental research in the physical sciences and life sciences.

Drawing on its widely acknowledged expertise, and thanks to its 16000 technicians, engineers, researchers and staff, the CEA actively participates in collaborative projects with a large number of academic and industrial partners.

The CEA is established in ten centers spread throughout France
  

Reference

SL-DRT-25-0904  

Direction

DRT

Thesis topic details

Category

Technological challenges

Thesis topics

GenPhi : 3D Generative AI conditioned by geometry, structure and physics

Contract

Thèse

Job description

The aim of this thesis is to design new 3D model generators based on Generative Artificial Intelligence (GenAI), capable of producing faithful, coherent and physically viable shapes. While 3D generation has become essential in many fields, current automatic generation approaches suffer from limitations in terms of respecting geometric, structural and physical constraints. The goal is to develop methods for integrating constraints related to geometry, topology, internal structure and physical laws, both stationary (equilibrium, statics) and dynamic (kinematics, deformation), right from the generation stage. The study will combine geometric perception, semantic enrichment and physical simulation approaches to produce robust, realistic 3D models that can be directly exploited without human intervention.

University / doctoral school

Sciences et Technologies de l’Information et de la Communication (STIC)
Paris-Saclay

Thesis topic location

Site

Saclay

Requester

Position start date

01/11/2025

Person to be contacted by the applicant

CHAOUCH Mohamed mohamed.chaouch@cea.fr
CEA
DRT/DIASI/SIALV/LVA
Institut CEA LIST
DIASI / Laboratoire Vision et Apprentissage pour l'analyse de scène
CEA Saclay - Nano-INNOV
Bât 861 - F91191 Gif-sur-Yvette Cedex
0169080117

Tutor / Responsible thesis director

PHAM Quoc Cuong quoc-cuong.pham@cea.fr
CEA
DRT/DIASI/SIALV/LVA
CEA SACLAY - Nano-INNOV
Bât. 861 - Point courrier 173
91191 Gif-sur-Yvette Cedex
0169082716

En savoir plus


https://kalisteo.cea.fr/