Demo Data from EDBT 2026 / reviewers in the wild / expert
Ruijie Yu
dblp:310/5361
· DBLP profile ↗
5ranked-venue papers
1as first author
5since 2021 · last 2026
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 2 since 2021Databases, data management, data science and information retrieval · 2 · 1 first-author · 2 since 2021Computer networks · 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.
| Network and information security
1 paper |
Network security · 100% | |
| Artificial intelligence
2 papers |
Language models and text generation · 79% Generative modeling · 21% | |
| Interdisciplinary, comprehensive, and emerging computing
2 papers |
Bioinformatics and computational biology · 74% Computational science and engineering · 26% | |
| Computer networks
1 paper |
Internet architecture and protocols · 100% |
Topics — the 7 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Natural language and speech › Language models and text generation
large language model evaluation |
1.0 | 1 | 2026 | ChemReason-Bench: Benchmarking Large Language Models for Procedural Reasoning in Experimental Chemistry · ACL (1) 2026 |
Bioinformatics and computational biology › molecular informatics
cheminformatics |
0.9 | 1 | 2025 | ChemActor: Enhancing Automated Extraction of Chemical Synthesis Actions with LLM-Generated Data · ACL (1) 2025 |
Network security
anonymity networks |
0.7 | 1 | 2023 | Demo: PDNS: A Fully Privacy-Preserving DNS · SIGCOMM 2023 |
Network security › protocol security › DNS security
DNS privacy |
0.7 | 1 | 2023 | Demo: PDNS: A Fully Privacy-Preserving DNS · SIGCOMM 2023 |
Computational science and engineering
computational chemistry |
0.3 | 1 | 2026 | ChemReason-Bench: Benchmarking Large Language Models for Procedural Reasoning in Experimental Chemistry · ACL (1) 2026 |
Machine learning › Generative modeling › synthetic data generation
LLM-based data generation |
0.3 | 1 | 2025 | ChemActor: Enhancing Automated Extraction of Chemical Synthesis Actions with LLM-Generated Data · ACL (1) 2025 |
Internet architecture and protocols
domain name system |
0.2 | 1 | 2023 | Demo: PDNS: A Fully Privacy-Preserving DNS · SIGCOMM 2023 |
Methods — techniques the papers use, named apart from their topics
large language model prompting · 2.0benchmark construction · 2.0large language model · 1.7data generation · 1.7private information retrieval · 1.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | ChemReason-Bench: Benchmarking Large Language Models for Procedural Reasoning in Experimental ChemistryabstractJinwei Zhang, Xucheng Liang, Yu Zhang, Ruijie Yu, Xiaokang Yang, Yaohui Jin, Yanyan Xu. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026. Xucheng Liang, Ruijie Yu, Xiaokang Yang 0001, Yaohui Jin, Yanyan Xu 0002 |
ACL (1) | 4 |
| 2026 | Cross-domain adaptive digital twin modelling for dam structures using graph attention networks
Jichen Tian, Ruijie Yu, Chen Chen 0132, Huibao Huang, Jiankang Chen |
Adv. Eng. Informatics | 2 |
| 2026 | A deep transfer learning framework for dynamic cracking risk assessment of gravity dams in cold regions under extreme environmental conditions
Ruijie Yu, Liang Pei, Yongqi Su, Jichen Tian |
Adv. Eng. Informatics | 1 |
| 2025 | ChemActor: Enhancing Automated Extraction of Chemical Synthesis Actions with LLM-Generated DataabstractYu Zhang, Ruijie Yu, Jidong Tian, Feng Zhu, Jiapeng Liu, Xiaokang Yang, Yaohui Jin, Yanyan Xu. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2025. Ruijie Yu, Jidong Tian, Feng Zhu 0006, Xiaokang Yang 0001, Yaohui Jin, Yanyan Xu 0002 |
ACL (1) | 2 |
| 2023 | Demo: PDNS: A Fully Privacy-Preserving DNSabstractThe Domain Name System (DNS) is a key component of Internet-based communication and its privacy has been neglected for years. Recently, DNS over HTTPS has improved the situation by fixing the issue of in-path middleboxes. Further progress has been made with proxy-based solutions such as Oblivious DoH, which separate a user's identity from their DNS queries. However, these solutions rely on non-collusion between DNS resolvers and proxy networks. This paper instead proposes PDNS, a new DNS extension that uses Private Information Retrieval to allow DNS resolvers to operate on blind queries, thereby eliminating any privacy leaks. Yunming Xiao, Chenkai Weng, Ruijie Yu, Peizhi Liu, Matteo Varvello, Aleksandar Kuzmanovic |
SIGCOMM | 3 |