Bayesian Neighborhood Adaptation for Graph Neural Networks
Paribesh Regmi, Rui Li, Kishan KC
Transactions on Machine Learning Research, 2025
About Me
👨💼
Current Role & Education
- Senior Applied Scientist at Amazon
- Ph.D. in Computing and Information Sciences from Rochester Institute of Technology
💡
What Drives Me
Motivated by applying AI to practical problems and communicating complex concepts in a clear, accessible way.
🔬
Research Focus
I specialize in Natural Language Processing (NLP), Generative AI, Multimodal Large Language Models, and Information Retrieval.
My research focuses on designing algorithms/solutions for generative multimodal question answering and multimodal search systems.
🏆
Impact & Achievements
Published multiple research papers that advance the state of Machine Learning, NLP and generative AI. Bridged experimentation and real-world deployment, turning large-scale data into reliable, production-ready solutions.
Technical Expertise
🤖AI/ML Research & Development
Generative AIMultimodal LLMsMultimodal Information RetrievalContext EngineeringRetrieval-Augmented GenerationQuestion-Answering Systems
🧠Machine Learning & Neural Networks
Deep LearningGraph Neural NetworksBayesian MethodsProbabilistic ML
⚡Programming & Technical Tools
PythonPyTorchTensorFlowHugging FaceScikit-learnNumPy/PandasAWSGit
Experience
Current Role
🏢
Sr. Applied Scientist
Amazon AGI
📍 Sunnyvale, CA
July 2025 – Present
🏢
Applied Scientist
Amazon AGI
📍 Sunnyvale, CA
February 2022 – June 2025
🏢
Applied Scientist Intern
Alexa AI, Amazon
📍 Sunnyvale, CA
June 2021 – September 2021
🏢
Research Assistant
Lab of Use-Inspired Computational Intelligence, RIT
📍 Rochester, New York
August 2016 – February 2022
Featured Publications
Highlights of my most impactful research contributions
