Arpad Rimmel
Associate Professor
CentraleSupélec
Arpad Rimmel is an Associate Professor at CentraleSupélec. He carries out his research at LISN (Laboratoire Interdisciplinaire des Sciences du Numérique) within the GALAC team (Graphes, Algorithmes et Combinatoire — Graphs, Algorithms and Combinatorics).
He focuses on problem solving, from formalization and complexity analysis through to the delivery of solutions, generally using machine learning and deep learning algorithms. He has supervised several PhD theses in this area, including one currently on the classification of drones from micro-Doppler signals using deep neural networks.
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- activation steering
- ai
- algorithmic trading
- anomaly detection
- autoencoders
- automated trading
- backtesting
- causal discovery
- causal inference
- causality
- code generation
- compiler optimization
- concept drift
- conformal prediction
- decision trees
- deep-learning
- evolutionary search
- experimental memory
- explainability
- explanation
- financial factors
- financial news
- flow matching
- fraud
- gradient boosting
- graphs
- hawkes processes
- health
- hopfield networks
- imitation learning
- inverse reinforcement learning
- ivae
- jepa
- knowledge graphs
- knowledge-graph
- large language models
- llms
- machine learning
- memory networks
- metrics
- microbiome
- monte carlo dropout
- music
- one-class svm
- personalization
- portfolio allocation
- reinforcement learning
- representation learning
- rnn
- rule learning
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- self-supervised learning
- sentiment analysis
- tabpfn
- tabular data
- tabular foundation models
- temporal series
- time series
- trading
- transaction networks
- transformers
- uncertainty quantification
- world models