VLDB 2026 Research / reviewers in the wild / expert
Runze Xue
dblp:250/4841
· DBLP profile ↗
3ranked-venue papers
1as first author
3since 2021 · last 2025
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 2 · 1 first-author · 2 since 2021Software engineering, systems software and programming languages · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Software engineering, system software, and programming languages
1 paper |
Programming languages and type systems · 100% | |
| Computer graphics and multimedia
1 paper |
Computational fabrication · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Programming languages and type systems › lambda calculus
call-by-push-value |
0.9 | 1 | 2025 | Notions of Stack-Manipulating Computation and Relative Monads · Proc. ACM Program. Lang. 2025 |
Programming languages and type systems
computational effects |
0.9 | 1 | 2025 | Notions of Stack-Manipulating Computation and Relative Monads · Proc. ACM Program. Lang. 2025 |
Programming languages and type systems
language semantics |
0.9 | 1 | 2025 | Notions of Stack-Manipulating Computation and Relative Monads · Proc. ACM Program. Lang. 2025 |
Programming languages and type systems › computational effects
monads |
0.9 | 1 | 2025 | Notions of Stack-Manipulating Computation and Relative Monads · Proc. ACM Program. Lang. 2025 |
Methods — techniques the papers use, named apart from their topics
monad transformers · 0.9category theory · 0.9bilevel optimization · 0.8beam search · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | WireSculptor: Interactive Guided Bending Workflow for Novice-Friendly Wire Sculpture Fabrication
Runze Xue, Baohang Zhou, Fan Zhong 0001, Qiong Zeng, Haisen Zhao |
ICXR | 1 |
| 2025 | Notions of Stack-Manipulating Computation and Relative MonadsabstractMonads provide a simple and concise interface to user-defined computational effects in functional programming languages. This enables equational reasoning about effects, abstraction over monadic interfaces and the development of monad transformer stacks to allow for multiple effects. Compiler implementors and assembly code programmers similarly virtualize effects, and would benefit from similar abstractions if possible. However, the implementation details of effects seem disconnected from the high-level monad interface: at this lower level much of the design is in the layout of the runtime stack , which is not accessible in a high-level programming language. We demonstrate that the monadic interface can be faithfully adapted from high-level functional programming to a lower level setting with explicit stack manipulation. We use a polymorphic call-by-push-value (CBPV) calculus as a setting that captures the essence of stack-manipulation, with a type system that allows programs to define domain-specific stack structures. Within this setting, we show that the existing category-theoretic notion of a relative monad can be used to model the stack-based implementation of computational effects. To demonstrate generality, we adapt a variety of standard monads to relative monads. Additionally, we show that stack-manipulating programs can benefit from a generalization of do-notation we call “monadic blocks” that allow all CBPV code to be reinterpreted to work with an arbitrary relative monad. As an application, we show that all relative monads extend automatically to relative monad transformers, a process which is not automatic for monads in pure languages. Yuchen Jiang 0006, Runze Xue, Max S. New |
Proc. ACM Program. Lang. | 2 |
| 2024 | Tune-It: Optimizing Wire Reconfiguration for Sculpture Manufacturingabstractthe input target wire with consecutive line segments and circular segments to ensure the bending manufacturing constraints for each segment, then generate tuned wire through a bilevel optimization.This involves selecting the bending points at the upper level with a beam search strategy and determining the specifically tuned angles at the lower level.We perform a thorough physical evaluation using a DIY wire-bending machine.The results show the effectiveness of our proposed approach in realizing a wide range of intricate and complex wire sculptures. Qibing Wu, Fanchao Zhong, Yueze Zhu, Xurong Lu, Runze Xue, Rui Li 0110, Changhe Tu, Haisen Zhao |
SIGGRAPH Asia | 7 |