New book "Blockchain Fundamentals, Data Structures, and Algorithms for Data Science"
Congratulations to Yulia R. Gel on her book "Blockchain Fundamentals, Data Structures, and Algorithms for Data Science" that has just been published by Cambridge University Press in co-authorship with Cüneyt Akçora, University of Central Florida and Murat Kantarcioglu, CS, Virginia Tech.
The book offers a systematic exploration of blockchain networks from both technical and analytical viewpoints and introduces the core structures that underpin blockchain systems, transactions, addresses, and smart contracts, explaining how these can be modeled, visualized, and analyzed using modern data science methods. Bridging computer science, finance, and statistics, the book integrates algorithmic reasoning with economic intuition to study decentralization, risk, and trust in digital economies. Through examples drawn from Bitcoin, Ethereum, Ripple, Monero, Zcash, IOTA, and DeFi, readers learn how blockchain data can be transformed into graph and temporal models for fraud detection, systemic risk analysis, and network behavior prediction. Featuring clear explanations, illustrative figures, and Solidity code, the book aims to serve as an essential reference for students, researchers, and practitioners in finance, data science, statistics, machine learning, and distributed systems.
The new book "Blockchain Fundamentals, Data Structures, and Algorithms for Data Science"