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hanyas/README.md

Hi there 👋

I am Hany, a postdoctoral researcher at the Amsterdam Machine Learning Lab (AMLab). I received my Phd from the Technical University of Darmstadt, Germany, under the supervision of Jan Peters. My research is centered at the intersection of decision-making theory and statistical inference.

I am interested in sequential decision-making under uncertainty and tackle those problems within the frameworks of reinforcement learning and information-theoretic stochastic optimization. I focus on developing principled and efficient algorithms for stochastic optimal control, sequential experimental design, and approximate inference in state-space models.

To find out more, visit my Google Scholar or find me on Twitter

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  1. Sahel13/InsideOutSMC.jlSahel13/InsideOutSMC.jlPublic

    Implements Inside-Out SMC^2, a nested sequential Monte Carlo algorithm developed for Bayesian experimental design in dynamical systems.

    Julia 7 1

  2. Sahel13/particle-pomdpSahel13/particle-pomdpPublic

    Code accompanying the NeurIPS 2025 paper "Sequential Monte Carlo for Policy Optimization in Continuous POMDPs".

    Python 2 1

  3. variational-iterated-smoothersvariational-iterated-smoothersPublic

    Implements recursive variational inference algorithms from the paper Recursive Entropic Variational Inference for Nonlinear State-Space Models.

    Python 1

  4. wasserstein-flow-filterwasserstein-flow-filterPublic

    Variational Filtering via Wasserstein Gradient Flow

    Python 6 1

  5. second-order-smootherssecond-order-smoothersPublic

    Second-order iterated smoothing algorithms for state estimation

    Python 7 1

  6. parallel-pdeparallel-pdePublic

    Parallel-in-Time Probabilistic Solutions for PDEs

    Jupyter Notebook