Alessandro Negro

Alessandro Negro is the chief scientist at GraphAware, where he supervises the science and technology area responsible for delivering Hume, a mission-critical analytics platform that uses knowledge graphs (KGs) at its core. He holds a Ph.D. in computer science and has successfully deployed machine learning systems combined with graphs for numerous organizations across various industries. Dr. Negro is the author of Graph-Powered Machine Learning (Manning, 2021). His recent work focuses on integrating LLMs with KGs to create more reliable and explainable AI systems at scale. Beyond his role at GraphAware, Alessandro actively mentors and advises startups, helping organizations in specialized domains create custom models tailored to their unique requirements.

books & videos by Alessandro Negro

Knowledge Graphs and LLMs in Action
  • October 2025
  • ISBN 9781633439894
  • 472 pages
Included with a Manning Online subscription
  • printed in black & white
catalog / Data Science / Machine Learning / Knowledge Graphs
resources: Source code Supplememental material Book forum Source code on Github Register your pBook for a free eBook

Knowledge Graphs and LLMs in Action shows you how to introduce knowledge graphs constructed from structured and unstructured sources into LLM-powered applications and RAG pipelines. Real-world case studies for domain-specific applications—from healthcare to financial crime detection—illustrate how this powerful pairing works in practice. You’ll especially appreciate the expert insights on knowledge representation and reasoning strategies.

Advantages of Graph-Based Machine Learning Systems
  • Course duration: 52m
Included with a Manning Online subscription

How do you apply graphs to machine-learning projects such as recommendation engines and chatbots?

Graph-Powered Machine Learning
  • August 2021
  • ISBN 9781617295645
  • 496 pages
Included with a Manning Online subscription
  • printed in black & white
catalog / Data Science / Machine Learning
resources: Book Forum Source code on GitHub 🎙️ Alessandro Negro Shares Tips&Tricks about Graph-Based Machine Learning Systems Creating a Bipartite Graph for a User-Item Dataset Slideshare: Develop Superior Machine Learning Algorithms Register your pBook for a free eBook Managing Data Sources in Machine Learning

Graph-Powered Machine Learning teaches you how to exploit the natural relationships in structured and unstructured datasets using graph-oriented machine learning algorithms and tools. In this authoritative book, you’ll master the architectures and design practices of graphs, and avoid common pitfalls. Author Alessandro Negro explores examples from real-world applications that connect GraphML concepts to real world tasks.