Dynamic graph algorithms and data structures represent a vital research frontier in computer science, underpinning applications from network analysis to real-time system monitoring.

Specialization: Foundations of Data Structures and Algorithms Instructor: Dr. Sriram Sankaranarayanan, Professor of Computer Science Prior knowledge needed: You must understand all concepts covered in ...

Graph data science is when you want to answer questions, not just with your data, but with the connections between your data points — that’s the 30-second explanation, according to Alicia Frame.

Mastering DSA is essential for improving coding efficiency and cracking technical interviews.The right DSA books provide ...

Design algorithms and analyze their complexity in terms of running time and space usage; Create applications that are supported by highly efficient algorithms and data structures for the task at hand; ...

The design, implementation, and analysis of abstract data types, data structures and their algorithms. Topics include: data and procedural abstraction, amortized data structures, trees and search ...

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs ...

The Graph, the decentralized indexing system that works much like Google for blockchains, has introduced a data standard for Web3. Called GRC-20, the standard would define how information is ...

Dr. Alin Deutsch of UC San Diego explains in a Q&A why graph database algorithms will become the driving force behind the next generation of AI and machine learning apps.