Jonathan Rubin

1.1k total citations
23 papers, 603 citations indexed

About

Jonathan Rubin is a scholar working on Artificial Intelligence, Cardiology and Cardiovascular Medicine and Cognitive Neuroscience. According to data from OpenAlex, Jonathan Rubin has authored 23 papers receiving a total of 603 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 7 papers in Cardiology and Cardiovascular Medicine and 7 papers in Cognitive Neuroscience. Recurrent topics in Jonathan Rubin's work include Artificial Intelligence in Games (8 papers), EEG and Brain-Computer Interfaces (7 papers) and ECG Monitoring and Analysis (6 papers). Jonathan Rubin is often cited by papers focused on Artificial Intelligence in Games (8 papers), EEG and Brain-Computer Interfaces (7 papers) and ECG Monitoring and Analysis (6 papers). Jonathan Rubin collaborates with scholars based in United States, New Zealand and India. Jonathan Rubin's co-authors include Saman Parvaneh, Saeed Babaeizadeh, Asif Rahman, Bryan Conroy, Ian Watson, Rui Abreu, Minnan Xu-Wilson, Anurag Ganguli, Ion Matei and Kumar Sricharan and has published in prestigious journals such as Artificial Intelligence, Physiological Measurement and AI Magazine.

In The Last Decade

Jonathan Rubin

22 papers receiving 578 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jonathan Rubin United States	11	381	226	158	114	80	23	603
Tatjana Lončar-Turukalo Serbia	13	120 0.3×	72 0.3×	174 1.1×	57 0.5×	84 1.1×	50	618
Leandro Rodrı́guez-Liñares Spain	8	195 0.5×	83 0.4×	20 0.1×	40 0.4×	120 1.5×	34	356
James Pardey United Kingdom	7	99 0.3×	244 1.1×	83 0.5×	50 0.4×	65 0.8×	15	511
Goran Krstačić Croatia	10	190 0.5×	48 0.2×	48 0.3×	47 0.4×	60 0.8×	38	343
Paulo R. Gomes Brazil	9	668 1.8×	241 1.1×	140 0.9×	100 0.9×	139 1.7×	33	855
Remo Mueller United States	5	116 0.3×	410 1.8×	62 0.4×	77 0.7×	150 1.9×	8	823
F. Bereksi Reguig Algeria	9	148 0.4×	115 0.5×	62 0.4×	21 0.2×	70 0.9×	31	299
Daniel Mobley United States	6	115 0.3×	425 1.9×	70 0.4×	40 0.4×	154 1.9×	8	811
Changchun Liu China	10	313 0.8×	157 0.7×	23 0.1×	26 0.2×	145 1.8×	22	478

Countries citing papers authored by Jonathan Rubin

Since Specialization

Citations

This map shows the geographic impact of Jonathan Rubin'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 Jonathan Rubin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Rubin more than expected).

Fields of papers citing papers by Jonathan Rubin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan Rubin. 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 Jonathan Rubin. The network helps show where Jonathan Rubin may publish in the future.

Co-authorship network of co-authors of Jonathan Rubin

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan Rubin. A scholar is included among the top collaborators of Jonathan Rubin 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 Jonathan Rubin. Jonathan Rubin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Rubin, Jonathan, et al.. (2023). Entity Contrastive Learning in a Large-Scale Virtual Assistant System. 159–171.

Rubin, Jonathan, et al.. (2022). Adaptive Beamformer based Left-Right Ambiguity Resolution Using Twin array. OCEANS 2022 - Chennai. 1–8. 2 indexed citations

Rubin, Jonathan, et al.. (2021). Efficient Video-Based Deep Learning for Ultrasound Guided Needle Insertion. 1 indexed citations

Natarajan, Annamalai, Yale Chang, Sara Mariani, et al.. (2020). A Wide and Deep Transformer Neural Network for 12-Lead ECG Classification. Computing in cardiology. 47. 87 indexed citations

Parvaneh, Saman, Jonathan Rubin, Saeed Babaeizadeh, & Minnan Xu-Wilson. (2019). Cardiac arrhythmia detection using deep learning: A review. Journal of Electrocardiology. 57. S70–S74. 93 indexed citations

Wang, Xin, Jonathan Rubin, Seth J. Berkowitz, et al.. (2019). Pulmonary Edema Severity Estimation in Chest Radiographs Using Deep Learning. 3 indexed citations

Parvaneh, Saman, et al.. (2018). Automatic Detection of Arousals During Sleep Using Multiple Physiological Signals. Computing in cardiology. 45. 4 indexed citations

Parvaneh, Saman & Jonathan Rubin. (2018). Electrocardiogram Monitoring and Interpretation: From Traditional Machine Learning to Deep Learning, and Their Combination. Computing in cardiology. 45. 22 indexed citations

Rubin, Jonathan, Saman Parvaneh, Asif Rahman, Bryan Conroy, & Saeed Babaeizadeh. (2018). Densely connected convolutional networks for detection of atrial fibrillation from short single-lead ECG recordings. Journal of Electrocardiology. 51(6). S18–S21. 74 indexed citations

10.

Parvaneh, Saman, Jonathan Rubin, Asif Rahman, Bryan Conroy, & Saeed Babaeizadeh. (2018). Analyzing single-lead short ECG recordings using dense convolutional neural networks and feature-based post-processing to detect atrial fibrillation. Physiological Measurement. 39(8). 84003–84003. 50 indexed citations

11.

Parvaneh, Saman, et al.. (2017). Densely Connected Convolutional Networks and Signal Quality Analysis to Detect Atrial Fibrillation Using Short Single-Lead ECG Recordings. Computing in cardiology. 43 indexed citations

12.

Rubin, Jonathan, Rui Abreu, Anurag Ganguli, et al.. (2016). Classifying Heart Sound Recordings using Deep Convolutional Neural Networks and Mel:Frequency Cepstral Coefficients. Computing in cardiology. 43. 100 indexed citations

13.

Rubin, Jonathan, Rui Abreu, Shane Ahern, Hoda Eldardiry, & Daniel G. Bobrow. (2016). Time, Frequency & Complexity Analysis for Recognizing Panic States from Physiologic Time-Series. 10 indexed citations

14.

Rubin, Jonathan, Hoda Eldardiry, Rui Abreu, et al.. (2015). Towards a mobile and wearable system for predicting panic attacks. 529–533. 19 indexed citations

15.

Bard, Nolan, et al.. (2013). The Annual Computer Poker Competition. AI Magazine. 34(2). 112–114. 10 indexed citations

16.

Rubin, Jonathan & Ian Watson. (2012). Case-based strategies in computer poker. AI Communications. 25(1). 19–48. 10 indexed citations

17.

Rubin, Jonathan & Ian Watson. (2011). On Combining Decisions from Multiple Expert Imitators for Performance. ResearchSpace (University of Auckland). 10 indexed citations

18.

Rubin, Jonathan & Ian Watson. (2011). Computer poker: A review. Artificial Intelligence. 175(5-6). 958–987. 40 indexed citations

19.

Watson, Ian, et al.. (2008). Improving a case-based texas hold'em poker bot. 1. 350–356. 2 indexed citations

20.

Rubin, Jonathan. (2007). Investigating the Effectiveness of Applying Case-Based Reasoning to the Game of Texas Hold'em. The Florida AI Research Society. 417–422. 5 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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