Ramesh Baral is a Principal Data Scientist in Durham, NC with 11 years of experience building production ML systems and recommendations for large enterprises. He designs personalization and GenAI products for financial services at Fidelity, and previously created hybrid GNN-based recommenders, multimodal movie and music recommenders, and knowledge graphs at Xperi. His background blends a PhD-level research focus on explainable and multi-aspect recommender systems with hands-on engineering across PyTorch/DGL, TensorFlow, PySpark, Neo4j and AWS. Ramesh has a track record of turning research prototypes into scalable production services—evidenced by end-to-end systems from preference elicitation to cold-start solutions and automated data pipelines. He also brings early-career strengths in systems automation and performance optimization, having saved substantial human effort through workflow and file-acquisition tooling. Curious and interdisciplinary, he pairs deep algorithmic knowledge with practical software delivery to solve complex personalization and LLM-driven use cases.
11 years of coding experience
13 years of employment as a software developer
Bachelor of Science - BS, Bachelor of Science - BS at Tribhuwan University, Prithvi Narayan Campus
Doctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at Florida International University
B.E Software Engineering, B.E Software Engineering at Pokhara Vishwavidalaya (Gandaki College Of Engineering and Science)
Contributions:6 commits, 2 PRs, 3 pushes in 1 year 10 months
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