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Todd AustinView profile

Professor

• Computer Architecture
• Hardware Security
• Secure System Design
• +4 more

Todd Austin is the S. Jack Hu Collegiate Professor of Electrical Engineering and Computer Science at the University of Michigan's College of Engineering. His research focuses on secure computer architecture and hardware-software co-design for security-critical systems. His primary research interests include computer architecture , hardware security , secure system design , and side-channel protection . Austin's work emphasizes practical solutions for real-world security challenges through hardware-software co-design and formal verification techniques. Recent publications (2022-2025) demonstrate a strong focus on data-oblivious execution , moving target defenses , and hardware-based security primitives . Key themes include eliminating side-channel leakage through program transformations, sequestered encryption techniques, and architectural support for vulnerability-tolerant systems. Austin maintains active research engagement through his Austin-Lab and open-source contributions, including the widely-forked bringup-bench repository for CPU and system validation. Contact: austin@umich.edu | Office: 4637 BBB, 2260 Hayward Avenue, Ann Arbor, MI 48109-2121 | Phone: 734-936-0370

Gerth Stølting BrodalView profile

Professor

• Algorithms
• Data Structures
• Computational Geometry
• +6 more

Gerth Stølting Brodal is a Professor in the Department of Computer Science at Aarhus University, Denmark, holding this position since January 2016. Previously, he served as an Associate Professor (tenured) at the same department from 2004 to 2015. His career includes a PostDoc at the Max-Planck-Institute for Computer Science in Saarbrücken, Germany (1997-1998) and long-term affiliations with research centers BRICS (1998-2005) and MADALGO (2007-2017). Education: PhD in Computer Science, Aarhus University (1997). Thesis: "Worst Case Efficient Data Structures". Research Focus: Brodal specializes in the design and analysis of algorithms and data structures. His work spans fundamental data structures (dictionaries, priority queues, persistent structures), computational geometry, graph/string algorithms, I/O-efficient and cache-oblivious methods, algorithm engineering, and computational biology. He is renowned for worst-case efficient solutions and external memory algorithm contributions, with a fingerprint emphasizing data structures (100%), worst-case analysis (42%), and I/O efficiency (27%). Recent Publication Trends: His 2024-2025 output reveals sustained innovation in advanced data structures—dynamic convex hulls, binary search trees with finger search capabilities, strict Fibonacci heaps, and cache-oblivious selection algorithms—demonstrating theoretical rigor with practical engineering applications in massive data processing. Academic Leadership: Brodal has supervised PhD students (evidenced by one thesis in his output) and contributed to major collaborative initiatives. His 141 research outputs include journal articles, conference papers, and book chapters, reflecting deep engagement with algorithmic theory and its real-world implementations.