Sahel Iqbal
I’m Sahel Iqbal, a third-year PhD student at Aalto University, Finland, where I work with Simo Särkkä. My main research focus is on developing accurate and efficient Monte Carlo algorithms for reinforcement learning and Bayesian experimental design (BED). Recently, I have also developed an interest in how similar algorithms can be used for inference-time alignment of diffusion and large language models.
For details regarding my research, see my Google Scholar profile. I can be contacted on X and at my email sahel[dot]iqbal[at]aalto[dot]fi.
Outside work, my time is mostly taken up by reading, lifting weights, and writing JAX code. The projects that I’m actively working on are available on GitHub.
Recent Posts
Asynchronous Data Copies in CuTe DSL — Part 1 of a multi-part series on GPU kernel development with NVIDIA’s CuTe domain-specific language.
Steering Language Models with Sequential Monte Carlo — How to give your language model the blues with SMC.
Using LaTeX Snippets in Markdown Files in Neovim — How I adapted my LuaSnip LaTeX snippets to work in Markdown for easier math note-taking in Neovim.
Recent News
2026-03: Our paper Maximin robust Bayesian experimental design is now out on ArXiv. We propose a worst-case decision-making rule for dealing with misspecified models in Bayesian experimental design.
2026-01: We released a new JAX library for inference in state-space models called
cuthbert! Checkout the tweet and the code.2025-09: Our paper Sequential Monte Carlo for Policy Optimization in Continuous POMDPs has been accepted to NeurIPS 2025!