Amy E. Hodler Picture

Amy E. Hodler

Analytics & AI Program Manager

Amy manages the Neo4j graph analytics programs and marketing. She loves seeing how our ecosystem uses graph analytics to reveal structures within real-world networks and infer dynamic behavior.

In her career, Amy has consistently helped teams break into new markets at startups and large companies including EDS, Microsoft and Hewlett-Packard (HP). She most recently comes from Cray Inc., where she was the analytics and artificial intelligence market manager.

Amy has a love for science and art with an extreme fascination for complexity science and graph theory. When the weather is good, you’re likely to find her cycling the passes in beautiful Eastern Washington.


Latest Posts by Amy E. Hodler

Check out this Q&A with the author of Graph-Powered Machine Learning.

5-Minute Interview: Graph-Powered Machine Learning with Dr. Alessandro Negro

We're very delighted to talk with Dr. Alessandro Negro, the Chief Scientist of GraphAware, who authored the recently published book, Graph-Powered Machine Learning. Dr. Negro has been a long-time member of the graph community, and was the main author of the very first recommendation engine... read more


Get these 7 quick tips to get more from the GDS library.

7 Quick Tips to Get More from the GDS Library [Tip Sheet]

The Neo4j Graph Data Science (GDS) Library is an enterprise-ready analytics workspace and repository of graph algorithms. With the GDS Library, data scientists can leverage analytics-specific data structures optimized for global traversals and aggregation, and flexibly subset and reshape your... read more


Financial Fraud Detection with Graph Data Science: Identifying Fraud Rings

Financial fraud is growing and it is a costly problem, estimated at 6% of the Global Domestic Product, more than $5 trillion in 2019. Despite using increasingly sophisticated fraud detection tools – often tapping into AI and machine learning – businesses lose more and more money to... read more


Financial Fraud Detection with Graph Data Science: Identifying First-Party Fraud

Financial fraud is growing and it is a costly problem, McKinsey, the fastest-growing type of first-party fraud is synthetic identity fraud. In synthetic identity fraud, the fraudster usually combines fake and real information to establish a credit record under a new, synthetic identity. This type... read more


Financial Fraud Detection with Graph Data Science: Analytics and Feature Engineering

Financial fraud is growing and it is a costly problem, estimated at 6% of the Global Domestic Product, more than $5 trillion in 2019. Despite using increasingly sophisticated fraud detection tools – often tapping into AI and machine learning – businesses lose more and more money to... read more


Financial Fraud Detection with Graph Data Science: Augment Your Approach

Financial fraud is growing and it is a costly problem, fastest-growing types of fraud in the U.S. – synthetic identity theft. Fraudsters meld various false and authentic elements (such as addresses, phone numbers, emails, employers and more) into a synthetic identity, which they then use for... read more


Learn about responsible AI and gain practical tips.

Responsible AI: The Critical Need for Context (and Practical Tips)

Why is it that we naturally talk about graphs as if they were context? That's because graphs were built to understand relationships – in fact, it's how graph theory started. Graphs were not only built to understand relationships, they were built with relationships. And that's... read more


Discover why we need to guide responsible AI.

Real Examples of Why We Need Context for Responsible AI

This was not on my radar 12 months ago. My good friend and smart colleague, Leena Bengani, suggested we look a little more closely into AI standards and tools. Part of the impetus was a White House request of the National Institute for Standards and Tools to engage with the AI community at... read more


Read how you can utilize graph technology to enhance your artificial intelligence and machine learning.

How Graphs Enhance Artificial Intelligence

Editor’s Note: This presentation was given by Amy Hodler at GraphTour San Francisco in May 2019. Presentation Summary In an everlasting race to achieve technological advancement, many companies are looking at artificial intelligence (AI) and machine learning (ML) as the next big step toward... read more


AI & Graph Technology: AI Explainability

This week we reach the final blog in our five-part series on AI and graph technology. Our focus here is on how graphs offer a way to provide transparency into the way AI makes decisions. This area is called AI explainability. One challenge in AI adoption is understanding how an AI solution made... read more


Connections Improve Accuracy

AI & Graph Technology: Connections Improve Accuracy

In last week's blog in our five-part series on AI and graph technology, we looked at how graphs offer greater efficiency of processing, and how graph-accelerated machine learning uses graphs to optimize models and speed up processes. This week, as we continue giving you a glimpse into how... read more


AI & Graph Technology: How Graphs Accelerate Machine Learning

Last week in our five-part series on AI and graph technology, we examined knowledge graphs, which offer context for decision support. This week we continue giving you a glimpse into how a graph technology platform like Neo4j enhances AI with context with a look at how graphs offer greater... read more


AI & Graph Technology: What Are Knowledge Graphs?

Last week in the first installment of our five-part blog series on AI and graph technology, we gave an overview of four ways graphs add context for artificial intelligence: context for decisions with knowledge graphs, context for efficiency with graph accelerated ML, context for accuracy with... read more


AI and Graph Technology: 4 Ways Graphs Add Context

The idea of artificial intelligence (AI) has a long history. Loosely defined, AI is a solution or set of tools to solve problems in ways that mimic human intelligence. Usually its most practical goal is to make predictions – either classifying things (such as adding a label) or predicting a value... read more


Learn how context makes artificial intelligence more reliable and trustworthy,

Toward AI Standards: Context Makes AI More Reliable and Trustworthy

In part three of our series Toward AI Solutions, we explain how and why context makes AI more robust to manage difficult problems and help make the most informed decisions. Trustworthiness is a critical topic for AI standards efforts and called out in the NIST draft engagement plan for U.S.... read more


Discover how graph technology makes AI more robust.

Toward AI Standards: Context Makes AI More Robust

Last week, in part two of our series Toward AI Solutions, we explore graph technology as the fabric for AI context: "More recently, graph technologies have been increasingly integrated with machine learning and artificial intelligence solutions. These applications include using connections to... read more


Learn more about moving towards AI standards with graph technology.

Toward AI Standards: Graph Technology as a Fabric for Context

Last week, part one of our "Toward AI Standards" blog series set the stage for defining what responsible artificial intelligence is and how graph technology provides the necessary context to make deeply informed decisions based on intelligent data. In this week's installment, we further break... read more


Learn more about how graphs provide context for responsible AI.

Toward AI Standards: Graph Technology for Responsible AI

Last week, Neo4j CEO Emil Eifrem published the blog, "Towards AI Standards, Why Context Is Critical for Artificial Intelligence" that spoke about our recent response to the request for information from the U.S. The National Institute of Standards and Technology (NIST). The NIST is looking to... read more


Discover the relationships of retail that you must master to delight your customers.

How to Exploit the 6 Relationships of Retail to Delight Your Customers [Infographic]

Retail opportunities are as big and dynamic as the industry has ever seen, and yet, knowing what to do or how to attack said opportunities is a bit more difficult to ascertain. U.S. retail sales per year are in the trillions and the impact of social media influencers are turning in billions.... read more


Different your solutions to achieve next-generation service assurance.

The Next Generation of Service Assurance: Differentiating Your Solution

Successful companies are embracing next-generation service assurance that leverages a comprehensive, real-time view of services and infrastructure with an eye on end-user experiences, new service creation and predictive modeling. But to compete in today’s market, communication service... read more


The next generation of service assurance, learn how your network is a graph.

The Next Generation of Service Assurance:
Your Network Is a Graph

Service complexity is exploding. Communication Service Providers (CSPs) need a complete view of their network and its myriad interdependencies to drive real-time decisions and predict the impact of changes on the user experience. A native graph approach makes sense of complex networks and... read more


Examine the challenges of network services and discover next-generation service assurance.

The Next Generation of Service Assurance:
The Imperative to Advance

Service assurance is the way organizations optimize various services offered over networks (from phone calls and email to video and applications) to deliver a better end-user experience. For decades, service assurance practices used fragmented views of the network and services that are... read more


Learn about the 15 most powerful and effective graph algorithms in the Neo4j Graph Platform

Graph Algorithms in Neo4j:
15 Different Graph Algorithms & What They Do

Graph analytics have value only if you have the skills to use them and if they can quickly provide the insights you need. Therefore, the best graph algorithms are easy to use, fast to execute and produce powerful results. Neo4j includes a growing, open library of high-performance graph... read more


Free Download O'Reilly Graph Algorithms book

Graph Algorithms in Neo4j: Streamline Data Discoveries with Graph Analytics

To analyze the billions of relationships in your connected data, you need efficiency and high performance, as well as powerful analytical tools that address a wide variety of graph problems. Fortunately, graph algorithms are up to the challenge. In this series on graph algorithms, we’ll... read more


Free Download O'Reilly Graph Algorithms book

Graph Algorithms in Neo4j: How Connections Drive Discoveries

Graph algorithms are the powerhouse behind the analysis of real-world networks — from identifying fraud rings and optimizing the location of public services to evaluating the strength of a group and predicting the spread of disease or ideas. In this series on graph algorithms, we’ll... read more