Tobias Rubel
I am a PhD student in computer science at the University of Maryland, College Park, advised by Laxman Dhulipala. I am supported by an NSF Graduate Research Fellowship.
I work on parallel algorithms and data structures, mostly for similarity search. My current focus is making graph-based indexes for approximate nearest neighbor search fast to build as well as fast to query, at billion-point scale. I am also interested in uniquely represented (history-independent) data structures and in randomized parallel algorithms more broadly.
Before Maryland I was a post-baccalaureate research assistant at Reed College, working on algorithms for biological networks with Anna Ritz and on models of technological innovation with Mark Bedau. I received a BA in philosophy from Reed College in 2019, with a thesis on metaphysical fundamentality advised by Paul Hovda.
Research interests
- Approximate nearest neighbor search and vector databases
- Parallel and cache-efficient algorithms
- Uniquely represented and history-independent data structures
- Randomized algorithms and graph algorithms
- Algorithms for computational biology
Publications
* denotes equal contribution.
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PiPNN: Ultra-Scalable Graph-Based Nearest Neighbor Indexing
Tobias Rubel, Richard Wen, Laxman Dhulipala, Lars Gottesbüren, Rajesh Jayaram, Jakub Łącki.
arXiv preprint, 2026. -
Fast, parallel, and cache-friendly suffix array construction
Jamshed Khan, Tobias Rubel, Erin K. Molloy, Laxman Dhulipala, Rob Patro.
Algorithms for Molecular Biology, 2024. Preliminary version in WABI 2023. -
Dollo-CDP: a polynomial-time algorithm for the clade-constrained large Dollo parsimony problem
Junyan Dai, Tobias Rubel, Yunheng Han, Erin K. Molloy.
Algorithms for Molecular Biology, 2024. Preliminary version in WABI 2023. -
Reconciling signaling pathway databases with network topologies
Tobias Rubel*, Pramesh Singh*, Anna Ritz.
Pacific Symposium on Biocomputing (PSB), 2022. -
Dropping diversity of products of large US firms: models and measures
Ananthan Nambiar*, Tobias Rubel*, James McCaull, Jon deVries, Mark A. Bedau.
PLOS ONE, 2022. -
Graphery: interactive tutorials for biological network algorithms
Heyuan Zeng, Jinbiao Zhang, Gabriel A. Preising, Tobias Rubel, Pramesh Singh, Anna Ritz.
Nucleic Acids Research, 2021. -
Augmenting signaling pathway reconstructions
Tobias Rubel, Anna Ritz.
ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB), 2020. -
Open-ended technological innovation
Mark A. Bedau, Nicholas Gigliotti, Tobias Janssen, Alec Kosik, Ananthan Nambiar, Norman Packard.
Artificial Life, 2019.