Home  | News

26.08.2023

Tiny logo
Teaser image to ERC Starting Grant for Angela Dai

ERC Starting Grant for Angela Dai

Spatial 3D Semantic Understanding for Perception in the Wild

For her project entitled "Spatial 3D Semantic Understanding for Perception in the Wild" our PI Angela Dai has been awarded an ERC Starting Grant 2022 by the European Research Council (ERC).

Angela Dai's research focuses on attaining a 3D understanding of the world around us, capturing and constructing semantically-informed 3D models of real-world environments. This includes 3D reconstruction and semantic understanding from commodity RGB-D sensor data, leveraging generative 3D deep learning towards enabling understanding and interaction with 3D scenes for content creation and virtual or robotic agents.

Congrats from us!

#award #research #dai

Related

Link to How Should Researchers Report Their Use of LLMs?

10.06.2026

How Should Researchers Report Their Use of LLMs?

Is AI making science impossible to replicate? Stefan Feuerriegel and the MCML team introduce the GUIDE-LLM framework in Nature.

Read more
Link to Benjamin Lange: The Real Risk of AI Agents is Manipulation Through Kindness

02.06.2026

Benjamin Lange: The Real Risk of AI Agents Is Manipulation Through Kindness

MCML Junior Research Group Leader Benjamin Lange examines how trust in AI agents can itself become a source of risk.

Read more
Tiny logo
Link to MCML at CVPR 2026

02.06.2026

MCML at CVPR 2026

MCML researchers are represented with 28 papers at CVPR 2026 (26 Main, and 2 Workshops).

Read more
Tiny logo
Link to MCML at ICRA 2026

29.05.2026

MCML at ICRA 2026

MCML researchers are represented with 4 papers at ICRA 2026 (3 Main, and 1 Workshop).

Read more
Link to Zeynep Akata: To Trust AI, We Need to Understand What Goes On Behind the Scenes

28.05.2026

Zeynep Akata: To Trust AI, We Need to Understand What Goes on Behind the Scenes

MCML PI Zeynep Akata explains that to trust AI, we must understand its inner workings, address foundation model bias, and make explainability central.

Read more
Back to Top