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prakharverma/README.md

I am a machine learning researcher specializing in probabilistic modeling, Bayesian inference, and large language models. I am currently a Senior Machine Learning Engineer at Inven and a Ph.D. researcher at Aalto University, advised by Prof. Arno Solin. My doctoral dissertation has been completed and successfully pre-examined, and is pending public defense in June 2026.

My research spans industry and academia through roles at Microsoft Research, Adobe Research, and the University of Oxford. I work on uncertainty-aware reasoning, sequential decision-making, and scalable inference methods for language models and probabilistic systems with applications to retrieval, entity understanding, and reasoning over noisy real-world data. Recent work includes efficient test-time planning for retrieval-augmented generation (RAG) and Bayesian causal discovery with language model priors.

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  1. GPflow/GPflow GPflow/GPflow Public

    Gaussian processes in TensorFlow

    Python 1.9k 432

  2. MLGlobalHealth/PriorCVAE MLGlobalHealth/PriorCVAE Public

    The PriorCVAE method extends PriorVAE (Semenova et al, Royal Society Interface 2022) to enable parameter inference

    Python 5

  3. AaltoML/scalable-inference-in-sdes AaltoML/scalable-inference-in-sdes Public

    Methods and experiments for assumed density SDE approximations

    Jupyter Notebook 12 3