VLDB 2026 Research / reviewers in the wild / expert
David Furcy
dblp:63/6493
· DBLP profile ↗
16ranked-venue papers
13as first author
5since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 7 · 5 first-author · 1 since 2021Theory of computation · 5 · 4 first-author · 3 since 2021Applied, interdisciplinary, general and emerging computing · 3 · 3 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 first-authorHuman-computer interaction and ubiquitous computing · 1 · 1 first-author
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Proving new directed tile complexity lower bounds at temperature 1 by folding between 2D and just-barely 3D self-assembly
David Furcy, Scott M. Summers, Hailey Vadnais |
Nat. Comput. | 1 |
| 2023 | Improved Lower and Upper Bounds on the Tile Complexity of Uniquely Self-Assembling a Thin Rectangle Non-Cooperatively in 3D
David Furcy, Scott M. Summers, Logan Withers |
Theory Comput. Syst. | 1 |
| 2021 | Improved Lower and Upper Bounds on the Tile Complexity of Uniquely Self-Assembling a Thin Rectangle Non-Cooperatively in 3DabstractWe investigate a fundamental question regarding a benchmark class of shapes in one of the simplest, yet most widely utilized abstract models of algorithmic tile self-assembly. Specifically, we study the directed tile complexity of a $k \times N$ thin rectangle in Winfree's abstract Tile Assembly Model, assuming that cooperative binding cannot be enforced (temperature-1 self-assembly) and that tiles are allowed to be placed at most one step into the third dimension (just-barely 3D). While the directed tile complexities of a square and a scaled-up version of any algorithmically specified shape at temperature 1 in just-barely 3D are both asymptotically the same as they are (respectively) at temperature 2 in 2D, the bounds on the directed tile complexity of a thin rectangle at temperature 2 in 2D are not known to hold at temperature 1 in just-barely 3D. Motivated by this discrepancy, we establish new lower and upper bounds on the directed tile complexity of a thin rectangle at temperature 1 in just-barely 3D. We develop a new, more powerful type of Window Movie Lemma that lets us upper bound the number of "sufficiently similar" ways to assign glues to a set of fixed locations. Consequently, our lower bound, $Ω\left(N^{\frac{1}{k}}\right)$, is an asymptotic improvement over the previous best lower bound and is more aesthetically pleasing since it eliminates the $k$ that used to divide $N^{\frac{1}{k}}$. The proof of our upper bound is based on a just-barely 3D, temperature-1 counter, organized according to "digit regions", which affords it roughly fifty percent more digits for the same target rectangle compared to the previous best counter. This increase in digit density results in an upper bound of $O\left(N^{\frac{1}{\left\lfloor\frac{k}{2}\right\rfloor}}+\log N\right)$, that is an asymptotic improvement over the previous best upper bound and roughly the square of our lower bound. David Furcy, Scott M. Summers, Logan Withers |
DNA | 1 |
| 2021 | On the effects of hierarchical self-assembly for reducing program-size complexity
Sarah Cannon, Erik D. Demaine, Martin L. Demaine, Sarah Eisenstat, David Furcy, Matthew J. Patitz, Robert Schweller, Scott M. Summers, Andrew Winslow |
Theor. Comput. Sci. | 5 |
| 2021 | Self-assembly of and optimal encoding within thin rectangles at temperature-1 in 3D
David Furcy, Scott M. Summers, Christian Wendlandt |
Theor. Comput. Sci. | 1 |
| 2019 | New Bounds on the Tile Complexity of Thin Rectangles at Temperature-1
David Furcy, Scott M. Summers, Christian Wendlandt |
DNA | 1 |
| 2018 | Optimal Self-Assembly of Finite Shapes at Temperature 1 in 3D
David Furcy, Scott M. Summers |
Algorithmica | 1 |
| 2017 | Optimal Program-Size Complexity for Self-Assembled Squares at Temperature 1 in 3D
David Furcy, Samuel Micka, Scott M. Summers |
Algorithmica | 1 |
| 2017 | Scaled pier fractals do not strictly self-assemble
David Furcy, Scott M. Summers |
Nat. Comput. | 1 |
| 2015 | Optimal Self-assembly of Finite Shapes at Temperature 1 in 3D
David Furcy, Scott M. Summers |
COCOA | 1 |
| 2015 | Optimal Program-Size Complexity for Self-Assembly at Temperature 1 in 3D
David Furcy, Samuel Micka, Scott M. Summers |
DNA | 1 |
| 2008 | Sorting out sorting: the sequelabstractRonald Baecker's Sorting Out Sorting (SOS) set the stage for much of what has followed in the evolution of algorithm visualization (AV). That period of evolution has now spanned over a quarter century, and we have learned much about how to effectively use AV. This paper addresses how we can incorporate that knowledge into a new rendition of SOS, which we call SOS - The Sequel. In this sequel we attempt to transform Baecker's original video into a highly interactive multimedia learning resource delivered over the Web using Macromedia Flash. The paper describes the design and use of this new resource and reports on a small empirical study designed to measure its effectiveness. David Furcy, Thomas L. Naps, Jason Wentworth |
ITiCSE | 1 |
| 2006 | Maximizing over multiple pattern databases speeds up heuristic search
Robert C. Holte, Ariel Felner, Jack Newton, Ram Meshulam, David Furcy |
Artif. Intell. | 5 |
| 2005 | Limited Discrepancy Beam Search
David Furcy, Sven Koenig |
IJCAI | 1 |
| 2005 | Scaling up WA* with Commitment and Diversity
David Furcy, Sven Koenig |
IJCAI | 1 |
| 2004 | Lifelong Planning A
Sven Koenig, Maxim Likhachev, David Furcy |
Artif. Intell. | 3 |