I am a Senior Machine Learning Engineer at Inven and a final-year Ph.D. student (expected June 2026) in Machine Learning at Aalto University, Finland, advised by Prof. Arno Solin, with publications at NeurIPS, AISTATS, and ICML.
My research spans both academic and industrial research through roles at Adobe Research, Microsoft Research, and University of Oxford. I work at the intersection of probabilistic modeling, Bayesian inference, and LLMs, developing theoretically grounded methods with practical impact. My focus is on principled approaches for reasoning, planning, and decision-making that enable uncertainty-aware, efficient, and interpretable machine learning at scale. Recent work includes efficient test-time planning for retrieval-augmented generation (RAG) and Bayesian sequential causal discovery with language models.
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News
- [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.
- [June 2025] Prakhar Verma, David Arbour, Sunav Choudhary, Harshita Chopra, Arno Solin, Atanu R. Sinha. Think Global, Act Local: Bayesian Causal Discovery with Language Models in Sequential Data. Pre-print
- [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
- [March 2023] Prakhar Verma, Vincent Adam, Arno Solin. Gaussian Variational Inference for Diffusion Processes Revisited accepted as a poster in "BayesComp" 2023. Poster
- [November 2022] Prakhar Verma, Paul E. Chang, Arno Solin, Mohammad Emtiyaz Khan. Sequential Learning in GPs with Memory and Bayesian Leverage Score accepted in Asian Conference in Machine Learning (ACML) workshop "Continual Lifelong Learning" 2022 (Contributed talk). Link Slide
- [October 2022] Paul E. Chang, Prakhar Verma, ST John, Victor Picheny, Henry Moss, Arno Solin. Fantasizing with Dual GPs in Bayesian Optimization and Active Learning accepted in NeurIPS workshop "Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems" 2022. Link Poster