Peter Schulam

1.3k total citations
23 papers, 496 citations indexed

About

Peter Schulam is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Peter Schulam has authored 23 papers receiving a total of 496 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 5 papers in Signal Processing. Recurrent topics in Peter Schulam's work include Machine Learning in Healthcare (6 papers), Video Analysis and Summarization (5 papers) and Music and Audio Processing (5 papers). Peter Schulam is often cited by papers focused on Machine Learning in Healthcare (6 papers), Video Analysis and Summarization (5 papers) and Music and Audio Processing (5 papers). Peter Schulam collaborates with scholars based in United States, Canada and Finland. Peter Schulam's co-authors include Suchi Saria, Andrew L. Beam, Tristan Naumann, Marzyeh Ghassemi, Rajesh Ranganath, Irene Y. Chen, Fredrick M. Wigley, Florian Metze, Susanne Burger and Duo Ding and has published in prestigious journals such as Annals of Internal Medicine, Journal of Machine Learning Research and Arthritis Research & Therapy.

In The Last Decade

Peter Schulam

20 papers receiving 461 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Peter Schulam United States	10	219	115	88	82	75	23	496
Jose Posada United States	12	268 1.2×	60 0.5×	174 2.0×	23 0.3×	61 0.8×	31	552
Changchang Yin United States	14	488 2.2×	55 0.5×	116 1.3×	43 0.5×	150 2.0×	28	679
David C. Kale United States	11	467 2.1×	261 2.3×	52 0.6×	84 1.0×	179 2.4×	16	943
Artuur Leeuwenberg Netherlands	8	275 1.3×	123 1.1×	17 0.2×	15 0.2×	58 0.8×	23	579
Shishir Rao United Kingdom	10	351 1.6×	65 0.6×	21 0.2×	21 0.3×	182 2.4×	20	656
Shinjini Kundu United States	11	173 0.8×	164 1.4×	50 0.6×	10 0.1×	36 0.5×	19	690
Christian Bock Switzerland	9	156 0.7×	37 0.3×	22 0.3×	37 0.5×	30 0.4×	28	452
Liebin Zhao China	14	58 0.3×	47 0.4×	52 0.6×	28 0.3×	17 0.2×	37	505
Junyi Gao China	12	314 1.4×	22 0.2×	22 0.3×	45 0.5×	148 2.0×	30	469
Malek Hammou Norway	3	133 0.6×	64 0.6×	51 0.6×	10 0.1×	34 0.5×	5	473

Countries citing papers authored by Peter Schulam

Since Specialization

Citations

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

Fields of papers citing papers by Peter Schulam

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Schulam

This figure shows the co-authorship network connecting the top 25 collaborators of Peter Schulam. A scholar is included among the top collaborators of Peter Schulam 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 Peter Schulam. Peter Schulam 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

Saria, Suchi, Peter Schulam, Brian J. Yeh, et al.. (2021). Development and Validation of ARC, a Model for Anticipating Acute Respiratory Failure in Coronavirus Disease 2019 Patients. Critical Care Explorations. 3(6). e0441–e0441. 1 indexed citations

Bates, David W., Andrew D. Auerbach, Peter Schulam, Adam Wright, & Suchi Saria. (2020). Reporting and Implementing Interventions Involving Machine Learning and Artificial Intelligence. Annals of Internal Medicine. 172(11_Supplement). S137–S144. 60 indexed citations

Ghassemi, Marzyeh, Tristan Naumann, Peter Schulam, et al.. (2019). Practical guidance on artificial intelligence for health-care data. The Lancet Digital Health. 1(4). e157–e159. 52 indexed citations

Schulam, Peter & Suchi Saria. (2019). Can You Trust This Prediction? Auditing Pointwise Reliability After Learning. 1022–1031. 10 indexed citations

Schulam, Peter, et al.. (2019). Active Learning for Decision-Making from Imbalanced Observational Data. Research Explorer (The University of Manchester). 10578–10587. 2 indexed citations

Subbaswamy, Adarsh, Peter Schulam, & Suchi Saria. (2018). Learning Predictive Models That Transport.. arXiv (Cornell University). 1 indexed citations

Xu, Zhongwen, Duo Ding, Francisco Vicente, et al.. (2018). Informedia E-Lamp@TRECVID 2012: Multimedia Event Detection and Recounting (MED and MER). Figshare.

Burger, Susanne, Qin Jin, Peter Schulam, & Florian Metze. (2018). Noisemes: Manual Annotation of Environmental Noise in Audio Streams. Research Showcase @ Carnegie Mellon University (Carnegie Mellon University). 6 indexed citations

Kan, Hong, Peter Schulam, Suchi Saria, et al.. (2018). Factors associated with physicians’ prescriptions for rheumatoid arthritis drugs not filled by patients. Arthritis Research & Therapy. 20(1). 79–79. 11 indexed citations

10.

Schulam, Peter, et al.. (2018). Using Counterfactual Queries To Improve Models For Decision-Support. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations

11.

Schulam, Peter & Suchi Saria. (2017). What-If Reasoning with Counterfactual Gaussian Processes. arXiv (Cornell University). 1 indexed citations

12.

Schulam, Peter & Suchi Saria. (2017). What-If Reasoning using Counterfactual Gaussian Processes. arXiv (Cornell University). 1696–1706. 1 indexed citations

13.

Schulam, Peter & Suchi Saria. (2016). Integrative analysis using coupled latent variable models for individualizing prognoses. Journal of Machine Learning Research. 17(1). 8244–8278. 6 indexed citations

14.

Schulam, Peter, Fredrick M. Wigley, & Suchi Saria. (2015). Clustering Longitudinal Clinical Marker Trajectories from Electronic Health Data: Applications to Phenotyping and Endotype Discovery. Proceedings of the AAAI Conference on Artificial Intelligence. 29(1). 61 indexed citations

15.

Schulam, Peter & Murat Akbacak. (2014). Diagnostic techniques for spoken keyword discovery. 1752–1756. 1 indexed citations

16.

Fellbaum, Christiane, et al.. (2013). Large, huge or gigantic? Identifying and encoding intensity relations among adjectives in WordNet. Language Resources and Evaluation. 47(3). 797–816. 14 indexed citations

17.

Schulam, Peter, et al.. (2013). Robust audio-codebooks for large-scale event detection in consumer videos. Figshare. 18 indexed citations

18.

Ding, Duo, et al.. (2012). Generating Natural Language Summaries for Multimedia. 128–130. 2 indexed citations

19.

Jin, Qin, et al.. (2012). Event-based video retrieval using audio. Figshare. 2085–2088. 42 indexed citations

20.

Schulam, Peter & Christiane Fellbaum. (2010). Automatically Determining the Semantic Gradation of German Adjectives.. 163–167. 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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