David Tench, a Grace Hopper postdoctoral fellow at Lawrence Berkeley National Labs, specializes in scalable graph algorithms. He discusses how his techniques enable real-time analysis of massive datasets while reducing storage needs. David challenges the idea that large graphs are typically sparse, suggesting a potential bias in data analysis processes. He emphasizes the importance of context in network analysis and introduces innovative approaches like CubeSketch and Graph Zeppelin to enhance computation efficiency in handling complex graphs.