
About
Daniel Anderson is an Assistant Teaching Professor in the Computer Science Department at Carnegie Mellon University's School of Computer Science. He teaches Algorithm Design and Analysis (15-451) and previously taught at Monash University in Australia. His academic journey includes a PhD from CMU under Professor Guy Blelloch and a Bachelor of Science (Honours) in Applied Mathematics from Monash University.
His research spans multiple areas of computer science with a strong focus on parallel computing. Anderson develops practical libraries like ParlayLib to make parallel programming more accessible, works on concurrent memory management techniques including "smarter atomic smart pointers," and explores parallel graph algorithms. His work bridges theoretical algorithm design with practical implementation challenges, particularly in making high-performance parallel computing more approachable for programmers.
Anderson's publications reveal a strong trajectory in parallel algorithms and memory management, with significant contributions to wait-free algorithms, reference counting techniques, and batch-dynamic data structures. His research consistently appears in top venues like PLDI, SPAA, and EuroPar, demonstrating both theoretical rigor and practical relevance. Recent work focuses on making reference counting as efficient as manual memory reclamation while maintaining usability.
Scientific Awards:
- Herbert A. Simon Award for Teaching Excellence in Computer Science (2024)
- Alan J. Perlis Graduate Student Teaching Award (2022)
While Anderson currently focuses primarily on teaching, he remains active in research supervision, particularly for undergraduate and master's projects related to parallel computing. His work with the ParlayLib research group continues to advance the state of parallel programming tools. Anderson also has experience coaching the Monash University Programming Team for the International Collegiate Programming Contest (ICPC) and serving as a judge for South Pacific Programming Contests.
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