2026 Sameer Singh: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	59	3318	3222	1607	1548	177	35487

Research.com Recognitions

2020 - Hellman Fellow

Overview

Sameer Singh is a researcher affiliated with the University of California, Irvine in the United States. Their primary domain of work lies within Computer Science, with a substantial number of publications-196 in total. Their research spans several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Plant Science, Sociology and Political Science, and Molecular Biology.

Their research interests include multiple main topics such as Topic Modeling, Natural Language Processing Techniques, Explainable Artificial Intelligence (XAI), Multimodal Machine Learning Applications, Adversarial Robustness in Machine Learning, Agricultural pest management studies, and Machine Learning and Data Classification.

Sameer Singh has contributed to various scholarly venues, with frequent publications appearing in:

arXiv (Cornell University)
Zenodo (CERN European Organization for Nuclear Research)
Proceedings of the AAAI Conference on Artificial Intelligence
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Journal of Thoracic and Cardiovascular Surgery

Their recent papers demonstrate a focus on topics related to machine learning interpretability, natural language processing, and generative adversarial networks. Notable works include:

"Fooling LIME and SHAP" (2020), published in Proceedings of the AAAI/ACM Conference on AI Ethics and Society
"An empirical comparison of machine learning methods for text-based sentiment analysis of online consumer reviews" (2021), published in International Journal of Research in Marketing
"Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models" (2022), published in Findings of the Association for Computational Linguistics: ACL 2022
"Image Augmentations for GAN Training" (2020), published on arXiv (Cornell University)
"Improved Consistency Regularization for GANs" (2021), published in Proceedings of the AAAI Conference on Artificial Intelligence

Frequent collaborators in their research include Matt Gardner, Kamal Ravi Sharma, Dylan Slack, Himabindu Lakkaraju, and Padhraic Smyth, reflecting ongoing partnerships across different areas of study.

Sameer Singh's work has been recognized with awards such as the Hellman Fellowship, which was received in 2020.

Best Publications

“Why Should I Trust You?”: Explaining the Predictions of Any Classifier

Marco Túlio Ribeiro;Sameer Singh;Carlos Guestrin

18964
Citations
Anchors: High-Precision Model-Agnostic Explanations

Marco Tulio Ribeiro;Sameer Singh;Carlos Guestrin

2120
Citations
AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts

Taylor Shin;Yasaman Razeghi;Robert L. Logan;Eric Wallace

1180
Citations
Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods

Dylan Slack;Sophie Hilgard;Emily Jia;Sameer Singh

876
Citations
Knowledge Enhanced Contextual Word Representations

Matthew E. Peters;Mark Neumann;Robert L. Logan;Roy Schwartz

833
Citations
Beyond accuracy: Behavioral testing of NLP models with checklist

Marco Tulio Ribeiro;Tongshuang Wu;Carlos Guestrin;Sameer Singh

776
Citations
Model-Agnostic Interpretability of Machine Learning.

Marco Túlio Ribeiro;Sameer Singh;Carlos Guestrin

745
Citations
Universal Adversarial Triggers for Attacking and Analyzing NLP

Eric Wallace;Shi Feng;Nikhil Kandpal;Matt Gardner

616
Citations
DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs

Dheeru Dua;Yizhong Wang;Pradeep Dasigi;Gabriel Stanovsky

504
Citations
Semantically Equivalent Adversarial Rules for Debugging NLP models

Marco Tulio Ribeiro;Sameer Singh;Carlos Guestrin

488
Citations
Generating Natural Adversarial Examples

Zhengli Zhao;Dheeru Dua;Sameer Singh

474
Citations
Calibrate Before Use: Improving Few-shot Performance of Language Models

Zihao Zhao;Eric Wallace;Shi Feng;Dan Klein

334
Citations
Evaluating Models’ Local Decision Boundaries via Contrast Sets

Matt Gardner;Yoav Artzi;Victoria Basmov;Jonathan Berant

318
Citations
FACTORIE: Probabilistic Programming via Imperatively Defined Factor Graphs

Andrew McCallum;Karl Schultz;Sameer Singh

294
Citations
Injecting Logical Background Knowledge into Embeddings for Relation Extraction

Tim Rocktäschel;Sameer Singh;Sebastian Riedel

272
Citations
Design Challenges for Entity Linking

Xiao Ling;Sameer Singh;Daniel Weld

243
Citations
Entity Linking via Joint Encoding of Types, Descriptions, and Context

Nitish Gupta;Sameer Singh;Dan Roth

233
Citations
Do NLP Models Know Numbers? Probing Numeracy in Embeddings

Eric Wallace;Yizhong Wang;Sujian Li;Sameer Singh

230
Citations
COVIDLIES: Detecting COVID-19 Misinformation on Social Media

Tamanna Hossain;Robert L. Logan;Arjuna Ugarte;Yoshitomo Matsubara

201
Citations
Barack's Wife Hillary: Using Knowledge-Graphs for Fact-Aware Language Modeling

Robert L. Logan;Nelson F. Liu;Matthew E. Peters;Matt Gardner

189
Citations
Evaluating Models' Local Decision Boundaries via Contrast Sets.

Matt Gardner;Yoav Artzi;Victoria Basmova;Jonathan Berant

98
Citations
Calibrate Before Use: Improving Few-Shot Performance of Language Models

Tony Z. Zhao;Eric Wallace;Shi Feng;Dan Klein

69
Citations

Frequent Co-Authors

Matt Gardner Allen Institute for Artificial Intelligence

Andrew McCallum University of Massachusetts Amherst

Sebastian Riedel University College London

Carlos Guestrin Stanford University

Tim Rocktäschel University College London

Dan Roth University of Pennsylvania

Noah A. Smith University of Washington

Anthony Chen Hong Kong Polytechnic University

Jonathan Berant Tel Aviv University

Hannaneh Hajishirzi University of Washington

External Links

Personal website of Sameer Singh Google Scholar page

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