معرفی
Nazaal Ibrahim is a doctoral researcher in the Department of Computer Science at the School of Science, focusing on probabilistic machine learning and causal inference. He has contributed to projects involving AI assistant development for privacy-preserving deep learning models and computational modeling of optimization tasks.
Research Areas
- Probabilistic Machine Learning
- Causal Inference
- Privacy-Preserving Deep Learning
- Computational Modeling
- Optimization Algorithms
Collaborations
- Collaborated with Samuel Kaski's professorship group
- Worked on projects with international teams (Finland, Japan)
Publications
In 2022, co-authored a paper titled Targeted Causal Elicitation, focusing on elicitation methods in Bayesian modeling frameworks.
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