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Shalin Shah

dblp:10/8178 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Machine learning › Trustworthy machine learning › robustness
adversarial robustness
0.712023
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
0.712023
Don't Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting Text · ACL (1) 2023
Bioinformatics and computational biology
systems biology
0.612022
The systems biology simulation core library · Bioinform. 2022
Bioinformatics and computational biology › systems biology
model exchange format
0.212022
The systems biology simulation core library · Bioinform. 2022
Machine learning › Transfer learning and domain adaptation › model adaptation
model interpolation
0.112009
Model Adaptation via Model Interpolation and Boosting for Web Search Ranking · EMNLP 2009
Recommender systems
model update
0.112009
Model Adaptation via Model Interpolation and Boosting for Web Search Ranking · EMNLP 2009
Information retrieval › web search
web search ranking
0.112009
Model Adaptation via Model Interpolation and Boosting for Web Search Ranking · EMNLP 2009
Machine learning › Kernel, tree and ensemble methods › ensemble learning
boosting
0.012009
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
YearPublicationVenuePosition
2023 Don't Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting Text
abstract
Ashim 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 library
abstract
SUMMARY: 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
DNA1
2018 Temporal DNA Barcodes: A Time-Based Approach for Single-Molecule Imaging
Shalin Shah, John H. Reif
DNA1
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
EMNLP7