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Victor Lee

Head, Product Marketing Distinguished Graph Specialist

Dr. Victor Lee is a long-time technical and product leader at TigerGraph. He combines technical knowledge in graph analytics, databases, and ML/AI with strengths in strategic planning, communication, customer/user experience, and leadership to help to bring to market category-leading graph analytics & AI products. He is the author of Graph-Powered Analytics and Machine Learning with TigerGraph. At TigerGraph, he has previously served as Head of Product Strategy/Developer Relations and Head of Machine Learning/AI. He has degrees from UC Berkeley (BS Electrical Engineering and Computer Science), Stanford University, (MS EE) and Kent State University (PhD Computer Science, research on graph data mining). Before TigerGraph he was a visiting professor at John Carroll University.

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TigerGraph graphic illustrating circular money flow between individuals and institutions, with icons for coordinated fraud and shared infrastructure; text reads How to Supercharge Fraud Detection with Graph Models.
Fraud / Anti-Money Laundering, Graph Databases
Fri 10 Apr 2026
How to Supercharge Fraud Detection with Graph Models
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Three clipboard icons with question marks and warning symbols are connected by arrows, representing unresolved cases. The background features a blue gradient and network lines, with the text: Repeat Investigations Signal Entity Resolution Failures That Inflate Casework.
Entity Resolution, Fraud / Anti-Money Laundering, Graph Databases
Thu 9 Apr 2026
Repeat Investigations Signal Entity Resolution Failures That Inflate Casework
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An infographic by TigerGraph shows two networks: one with duplicate and fragmented records, and another with unified, complete identities, illustrating how graph technology resolves broken entity resolution.
Entity Resolution, Fraud / Anti-Money Laundering, Graph Databases
Wed 8 Apr 2026
Entity Resolution is Broken & Here’s How Graph Fixes it
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Infographic with TigerGraph logo, network graphs labeled Centrality and Community Detection, and a map showing airline routes between ATL and LHR. Text reads: What Airline Routes Teach Us About Graph Analytics at Scale.
Data Science, Graph Databases, Risk and Fraud Analytics
Wed 8 Apr 2026
What Airline Routes Teach Us About Graph Analytics at Scale
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A comparison graphic showing Traditional BI with bar and table icons versus Graph Analytics with a network node icon, highlighting differences, with the text: What You’re Missing with Traditional BI vs Graph Analytics.
Graph Databases, Risk and Fraud Analytics
Thu 5 Mar 2026
What You’re Missing with Traditional BI vs Graph Analytics
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Infographic by TigerGraph showing how Entity Resolution Gaps in Fraud and AML Detection cause duplicate identities and coverage gaps, illustrated with network diagrams, magnifying glass, and caution icons. Text highlights graph search benefits.
Entity Resolution, Fraud / Anti-Money Laundering
Thu 26 Feb 2026
When Entity Resolution Stops Short, Graph Search Exposes Duplicate Networks and Coverage Gaps
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A flowchart shows money moving through a respondent bank to multiple correspondent banks, ending at a beneficiary bank. The image highlights the process, with the TigerGraph logo and title text about banking escalations and chain evidence.
Finance, Fraud / Anti-Money Laundering, Graph Databases
Tue 24 Feb 2026
How to Keep Correspondent Banking Escalations Reviewable with Chain Evidence
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Flowchart showing a customer connecting through a company, bank, and offshore entity to a sanctioned entity, illustrating indirect sanctions exposure. TigerGraph logo appears in the top left corner.
Fraud / Anti-Money Laundering
Thu 19 Feb 2026
How to Find Indirect Sanctions Exposure by Following Connection Paths
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