I am a fourth year PhD student in Computing and Information Science at Rochester Institute of Technology (RIT), working with Prof. Rui Li in the Lab of Use-Inspired Computational Intelligence (LUCI). Before starting my PhD, I completed my undergraduate in Electronics and Communication Engineering at Pulchowk Campus, IOE, Nepal.

Research

My research spans Bayesian methods, graph learning, and generative models. I have worked on developing Bayesian model selection frameworks for both generative modeling and graph learning. Currently, I am focused on designing efficient algorithms to improve the inference speed of diffusion- and flow-based generative models.

News

Oct, 2024 Serving as a reviewer for International Conference on Learning Representations (ICLR), 2024.
Dec, 2023 Presented our poster on "AdaVAE: Bayesian Structural Adaptation for Variational Autoencoders" at NeurIPS 2023 in New Orleans, LA.
Sep, 2023 Our paper titled "AdaVAE: Bayesian Structural Adaptation for Variational Autoencoders" is accepted as a full conference paper at NeurIPS 2023 - Paribesh Regmi; Rui Li
May, 2022 Passed my research potential assessment (PhD qualifying exam)
Dec, 2021 Volunteered at the Thirty-Fifth Conference on Neural Information Processing Systems (NeurIPS), 2021
Aug, 2021 Started PhD in Computing and Information Science at Rochester Institute of Technology (RIT), advised by Prof. Rui Li
May, 2021 Promoted to Solutions Engineer at LogPoint
Jul, 2019 Our paper titled "Nepali Speech Recognition Using RNN-CTC Model" is published in the International Journal of Computer Applications -- Paribesh Regmi; Arjun Dahal; Basanta Joshi
Oct, 2018 Joined LogPoint, a SIEM company as an Associate Solutions Engineer
Sep, 2018 Successfully completed an undergraduate degree in Electronics and Communication Engineering at Pulchowk Campus, IOE, Nepal