Prakhar Verma

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.

Email  /  CV  /  Google Scholar  /  LinkedIn

profile photo

News

  • [April 2026] Prakhar Verma, David Arbour, Sunav Choudhary, Harshita Chopra, Arno Solin, Atanu R. Sinha. Sequential Causal Discovery with Noisy Language Model Priors accepted in Transactions on Machine Learning Research (TMLR). Link
  • [October 2025] Started as a Senior Machine Learning Engineer at Inven.
  • [August 2025] I will be a workflow chair for AISTATS 2026 with Yo Joong Choe and Program Chairs Aaditya Ramdas and Arno Solin.
  • [March 2025] Prakhar Verma, Sukruta Prakash Midigeshi, Gaurav Sinha, Arno Solin, Nagarajan Natarajan, Amit Sharma. Plan*RAG: Efficient Test-Time Planning for Retrieval Augmented Generation accepted in Workshop on Reasoning and Planning for Large Language Models at ICLR 2025. Link
  • [September 2024] Completed a 3 months Research Internship at Adobe Research.
  • [June 2024] Completed a 3 months Research Internship at Microsoft Research.
  • [January 2024] Prakhar Verma, Vincent Adam, Arno Solin. Variational Gaussian Process Diffusion Processes accepted in the Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 2024. Link
  • [October 2023] Elizaveta Semenova, Prakhar Verma, Max Cairney-Leeming, Arno Solin, Samir Bhatt, Seth Flaxman. PriorCVAE: Scalable MCMC parameter inference with Bayesian deep generative modelling Link
  • [September 2023] Completed a 3 months research visit at University of Oxford.
  • [May 2023] Paul E. Chang*, Prakhar Verma*, ST John, Arno Solin, Mohammad Emtiyaz Khan. Memory-based dual Gaussian processes for sequential learning accepted in International Conference on Machine Learning (ICML), 2023 (Oral Presentation). Link

Theses

Prakhar Verma (2026). Scalable Probabilistic Inference for Sequential Stochastic Models. Doctoral dissertation. Aalto University. PDF

Prakhar Verma (2021). Sparse Gaussian processes for stochastic differential equations. Master’s thesis. Aalto University. PDF

Prakhar Verma (2016). Development of automated GIS Tools on various platforms. Bachelor's thesis. Uttarakhand Technical University, TomTom India. PDF