Caesar Wu

Caesar Wu is a Researcher at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT) within the PCOG department. His work focuses on trustworthy AI, distributed learning systems, machine learning optimization, and strategic decision-making frameworks. He holds a Postdoctoral researcher position and contributes to advancing methodologies in data-centric AI, transformer models, and cybersecurity.

Research interests include:
- Trustworthy AI: Developing robust frameworks for explainability, fairness, and algorithmic transparency.
- Distributed Systems: Optimizing communication and fault tolerance in distributed machine learning.
- Time Series Forecasting: Hyperparameter tuning and transformer-based predictive models.
- Financial Applications: Strategic decision-making in credit risk assessments using ML.

Recent publications (2023-2025) emphasize:

• Trustworthiness metrics for stochastic gradient descent in distributed environments
• Unified hyperparameter optimization pipelines for transformer models
• Survey analysis of data-centric AI in time series forecasting
• Ethical considerations in AI-driven strategic decisions

No scientific awards were explicitly mentioned in the provided texts.

Current role involves no formal advisees, but contributes to interdisciplinary research teams within SnT. His work integrates machine learning with cloud computing principles, reflecting expertise in both theoretical and applied domains.