Srinivasan Iyer

2.8k total citations · 1 hit paper
37 papers, 1.6k citations indexed

About

Srinivasan Iyer is a scholar working on Artificial Intelligence, Molecular Biology and Toxicology. According to data from OpenAlex, Srinivasan Iyer has authored 37 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 10 papers in Molecular Biology and 7 papers in Toxicology. Recurrent topics in Srinivasan Iyer's work include Topic Modeling (11 papers), Biomedical Text Mining and Ontologies (9 papers) and Natural Language Processing Techniques (8 papers). Srinivasan Iyer is often cited by papers focused on Topic Modeling (11 papers), Biomedical Text Mining and Ontologies (9 papers) and Natural Language Processing Techniques (8 papers). Srinivasan Iyer collaborates with scholars based in United States, India and Israel. Srinivasan Iyer's co-authors include Paea LePendu, Nigam H. Shah, Luke Zettlemoyer, Ioannis Konstas, Alvin Cheung, Anna Bauer‐Mehren, Rave Harpaz, Nicholas J. Leeper, Yohannes T. Ghebremariam and John P. Cooke and has published in prestigious journals such as Circulation, PLoS ONE and Journal of Lipid Research.

In The Last Decade

Srinivasan Iyer

35 papers receiving 1.6k citations

Hit Papers

Summarizing Source Code using a Neural Attention Model 2016 2026 2019 2022 2016 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Summarizing Source Code using a Neural Attention Model
    2016 415 citations Srinivasan Iyer, Ioannis Konstas et al. profile →

Peers

Srinivasan Iyer
David Madigan United States
Jon Duke United States
Huilong Duan China
Paea LePendu United States
Zhengxing Huang China
Ping Zhang United States
Rae Woong Park South Korea
E. Jönsson Sweden
Dingcheng Li United States
Christian Reich United States
David Madigan United States
Srinivasan Iyer
Citations per year, relative to Srinivasan Iyer Srinivasan Iyer (= 1×) peers David Madigan

Countries citing papers authored by Srinivasan Iyer

Since Specialization
Citations

This map shows the geographic impact of Srinivasan Iyer's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Srinivasan Iyer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Srinivasan Iyer more than expected).

Fields of papers citing papers by Srinivasan Iyer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Srinivasan Iyer. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Srinivasan Iyer. The network helps show where Srinivasan Iyer may publish in the future.

Co-authorship network of co-authors of Srinivasan Iyer

This figure shows the co-authorship network connecting the top 25 collaborators of Srinivasan Iyer. A scholar is included among the top collaborators of Srinivasan Iyer based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Srinivasan Iyer. Srinivasan Iyer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Hase, Peter, Mona Diab, Aslı Çelikyılmaz, et al.. (2023). Methods for Measuring, Updating, and Visualizing Factual Beliefs in Language Models. 2714–2731. 15 indexed citations
2.
Ye, Xi, Srinivasan Iyer, Aslı Çelikyılmaz, et al.. (2023). Complementary Explanations for Effective In-Context Learning. 4469–4484. 24 indexed citations
3.
Yadav, Poonam, et al.. (2023). Auto-Regressive Integrated Moving Average Threshold Influence Techniques for Stock Data Analysis. International Journal of Advanced Computer Science and Applications. 14(6). 3 indexed citations
4.
Khan, Sania, et al.. (2023). Enhancing and sustaining employee engagement through HRM practices: A study on Indian unicorn startups. Problems and Perspectives in Management. 21(4). 202–213.
5.
Ladhak, Faisal, Srinivasan Iyer, Veselin Stoyanov, et al.. (2022). ToKen: Task Decomposition and Knowledge Infusion for Few-Shot Hate Speech Detection. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 2109–2120. 8 indexed citations
6.
Iyer, Srinivasan, Sewon Min, Yashar Mehdad, & Wen-tau Yih. (2021). RECONSIDER: Improved Re-Ranking using Span-Focused Cross-Attention for Open Domain Question Answering. 1280–1287. 13 indexed citations
7.
8.
Mehta, Sachin, Marjan Ghazvininejad, Srinivasan Iyer, Luke Zettlemoyer, & Hannaneh Hajishirzi. (2020). DeLighT: Very Deep and Light-weight Transformer. arXiv (Cornell University). 15 indexed citations
9.
Iyer, Srinivasan, Ioannis Konstas, Alvin Cheung, & Luke Zettlemoyer. (2016). Summarizing Source Code using a Neural Attention Model. 2073–2083. 415 indexed citations breakdown →
10.
Iyer, Srinivasan, et al.. (2015). CLOUD BASED COMPILER. 1(3). 308–322. 3 indexed citations
11.
Jung, Kenneth, Paea LePendu, William S. Chen, et al.. (2014). Automated Detection of Off-Label Drug Use. PLoS ONE. 9(2). e89324–e89324. 48 indexed citations
12.
Huang, Sandy H., Paea LePendu, Srinivasan Iyer, et al.. (2014). Toward personalizing treatment for depression: predicting diagnosis and severity. Journal of the American Medical Informatics Association. 21(6). 1069–1075. 77 indexed citations
13.
Lyalina, Svetlana, Bethany Percha, Paea LePendu, et al.. (2013). Identifying phenotypic signatures of neuropsychiatric disorders from electronic medical records. Journal of the American Medical Informatics Association. 20(e2). e297–e305. 42 indexed citations
14.
Cole, Tyler S., Jennifer Frankovich, Srinivasan Iyer, et al.. (2013). Profiling risk factors for chronic uveitis in juvenile idiopathic arthritis: a new model for EHR-based research. Pediatric Rheumatology. 11(1). 45–45. 30 indexed citations
15.
LePendu, Paea, Srinivasan Iyer, Anna Bauer‐Mehren, et al.. (2013). Pharmacovigilance Using Clinical Notes. Clinical Pharmacology & Therapeutics. 93(6). 547–555. 124 indexed citations
16.
Leeper, Nicholas J., Anna Bauer‐Mehren, Srinivasan Iyer, et al.. (2013). Practice-Based Evidence: Profiling the Safety of Cilostazol by Text-Mining of Clinical Notes. PLoS ONE. 8(5). e63499–e63499. 60 indexed citations
17.
Iyer, Srinivasan, Rave Harpaz, Paea LePendu, Anna Bauer‐Mehren, & Nigam H. Shah. (2013). Mining clinical text for signals of adverse drug-drug interactions. Journal of the American Medical Informatics Association. 21(2). 353–362. 125 indexed citations
18.
LePendu, Paea, Anna Bauer‐Mehren, Srinivasan Iyer, & Nigam H. Shah. (2012). Abstract 15727: Analyzing Unstructured Clinical Notes for Phase IV Drug Safety Surveillance. Circulation. 126. 1 indexed citations
19.
LePendu, Paea, Srinivasan Iyer, Cédrick Fairon, & Nigam H. Shah. (2012). Annotation Analysis for Testing Drug Safety Signals using Unstructured Clinical Notes. Journal of Biomedical Semantics. 3(S1). S5–S5. 73 indexed citations
20.
Fitzpatrick, Richard, et al.. (2008). A histopathologic evaluation of the plasma skin regeneration system (PSR) versus a standard carbon dioxide resurfacing laser in an animal model. Lasers in Surgery and Medicine. 40(2). 93–99. 39 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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