While 3DGS (3D Gaussian Splatting) has recently emerged as a powerful approach for real-time novel view synthesis, its storage and computational demands remain significant. This PhD project focuses on compressive radiance fields, and more specifically 3DGS for efficient scene representation and rendering. The aim of the project is to explore compressive strategies to reduce memory […]
PHD Projects
This project investigates the development of reliable and explainable evaluation metrics for generative models, with a particular focus on applications in game development. While state-of-the-art approaches such as GANs and diffusion models are capable of generating increasingly high-quality content, their adoption in production pipelines is limited by the lack of robust automated evaluation methods. This […]
This research project uses language models to understand software artifacts such as source code, bytecode, and metadata. The aim is to strengthen software security by detecting malicious or tampered software earlier, reducing false negatives, and helping developers focus reviews where they matter most. The current focus is on Android malware detection and Java obfuscation detection. […]
In interpersonal communication, nonverbal signals—including facial and body cues—convey far more emotional content than spoken words. To capture and analyse emotion expressed in often-unconscious nonverbal behaviour, this project builds a generative pipeline that reconstructs 3D meshes from 2D images and video using 3D morphable face models and human parametric body models (e.g., the SMPL family). […]
The latest generation of large language models (LLMs) is extremely resource-hungry, to the point where training and even deploying models has become infeasible for most actors. This project proposes tackleling this problem by dissecting LLMs into modules that encapsulate functional capabilities such as languages and knowledge retrieval and that can be trained and updated independently […]
The PhD project envisions creating a framework for designing and building LLM-systems tailored for human-centric, safety-critical applications. The aim is to research how to effectively integrate specialized data and domain knowledge in the decision making processes. Moreover, the research group aims to investigate how to integrate risk assessment and bias in the generated outputs. Lastly, […]