EDBT 2026 Demo / reviewers in the wild / expert
Shalin Shah
dblp:10/8178
· DBLP profile ↗
8ranked-venue papers
2as first author
4since 2021 · last 2023
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3 · 2 first-author · 1 since 2021Artificial intelligence and machine learning · 2 · 1 since 2021Theory of computation · 2 · 1 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.
| Artificial intelligence
2 papers |
Trustworthy machine learning · 46% Language models and text generation · 46% Transfer learning and domain adaptation · 7% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Information retrieval · 50% Recommender systems · 50% |
Topics — the 8 heaviest of 9, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Trustworthy machine learning › robustness
adversarial robustness |
0.7 | 1 | 2023 | Don't Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting Text · ACL (1) 2023 |
Natural language and speech › Language models and text generation › text generation
text rewriting |
0.7 | 1 | 2023 | Don't Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting Text · ACL (1) 2023 |
Bioinformatics and computational biology
systems biology |
0.6 | 1 | 2022 | The systems biology simulation core library · Bioinform. 2022 |
Bioinformatics and computational biology › systems biology
model exchange format |
0.2 | 1 | 2022 | The systems biology simulation core library · Bioinform. 2022 |
Machine learning › Transfer learning and domain adaptation › model adaptation
model interpolation |
0.1 | 1 | 2009 | Model Adaptation via Model Interpolation and Boosting for Web Search Ranking · EMNLP 2009 |
Recommender systems
model update |
0.1 | 1 | 2009 | Model Adaptation via Model Interpolation and Boosting for Web Search Ranking · EMNLP 2009 |
Information retrieval › web search
web search ranking |
0.1 | 1 | 2009 | Model Adaptation via Model Interpolation and Boosting for Web Search Ranking · EMNLP 2009 |
Machine learning › Kernel, tree and ensemble methods › ensemble learning
boosting |
0.0 | 1 | 2009 | Model Adaptation via Model Interpolation and Boosting for Web Search Ranking · EMNLP 2009 |
Methods — techniques the papers use, named apart from their topics
text rewriting · 0.7adversarial defense · 0.7stochastic differential equation solver · 0.6ordinary differential equation solver · 0.6constraint-based analysis · 0.6model interpolation · 0.2boosting · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Don't Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting TextabstractAshim Gupta, Carter Blum, Temma Choji, Yingjie Fei, Shalin Shah, Alakananda Vempala, Vivek Srikumar. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2023. Ashim Gupta, Carter Wood Blum, Temma Choji, Yingjie Fei, Shalin Shah, Alakananda Vempala, Vivek Srikumar |
ACL (1) | 5 |
| 2022 | The systems biology simulation core libraryabstractSUMMARY: Studying biological systems generally relies on computational modeling and simulation, e.g., model-driven discovery and hypothesis testing. Progress in standardization efforts led to the development of interrelated file formats to exchange and reuse models in systems biology, such as SBML, the Simulation Experiment Description Markup Language (SED-ML) or the Open Modeling EXchange format. Conducting simulation experiments based on these formats requires efficient and reusable implementations to make them accessible to the broader scientific community and to ensure the reproducibility of the results. The Systems Biology Simulation Core Library (SBSCL) provides interpreters and solvers for these standards as a versatile open-source API in JavaTM. The library simulates even complex bio-models and supports deterministic Ordinary Differential Equations; Stochastic Differential Equations; constraint-based analyses; recent SBML and SED-ML versions; exchange of results, and visualization of in silico experiments; open modeling exchange formats (COMBINE archives); hierarchically structured models; and compatibility with standard testing systems, including the Systems Biology Test Suite and published models from the BioModels and BiGG databases. AVAILABILITY AND IMPLEMENTATION: SBSCL is freely available at https://draeger-lab.github.io/SBSCL/ and via Maven Central. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Hemil Panchiwala, Shalin Shah, Hannes Planatscher, Mykola Zakharchuk, Matthias König 0003, Andreas Dräger |
Bioinform. | 2 |
| 2021 | Machine learning models and techniques for VANET based traffic management: Implementation issues and challenges
Sahil Khatri, Hrishikesh Vachhani, Shalin Shah, Jitendra Bhatia, Manish Chaturvedi, Sudeep Tanwar, Neeraj Kumar 0001 |
Peer-to-Peer Netw. Appl. | 3 |
| 2021 | Multidimensional data organization and random access in large-scale DNA storage systems
Shalin Shah, John H. Reif |
Theor. Comput. Sci. | 2 |
| 2019 | Implementing Arbitrary CRNs Using Strand Displacing Polymerase
Shalin Shah, John H. Reif |
DNA | 1 |
| 2018 | Temporal DNA Barcodes: A Time-Based Approach for Single-Molecule Imaging
Shalin Shah, John H. Reif |
DNA | 1 |
| 2013 | Strong matching preclusion for augmented cubes
Eddie Cheng 0001, Shalin Shah, Vyom Shah, Daniel E. Steffy |
Theor. Comput. Sci. | 2 |
| 2009 | Model Adaptation via Model Interpolation and Boosting for Web Search Ranking
Jianfeng Gao 0001, Christopher J. C. Burges, Krysta M. Svore, Nazan Khan, Shalin Shah |
EMNLP | 7 |