Kristen Severson

5.0k total citations · 2 hit papers
24 papers, 3.4k citations indexed

About

Kristen Severson is a scholar working on Artificial Intelligence, Molecular Biology and Control and Systems Engineering. According to data from OpenAlex, Kristen Severson has authored 24 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Molecular Biology and 4 papers in Control and Systems Engineering. Recurrent topics in Kristen Severson's work include Machine Learning in Healthcare (3 papers), Fault Detection and Control Systems (3 papers) and Mineral Processing and Grinding (3 papers). Kristen Severson is often cited by papers focused on Machine Learning in Healthcare (3 papers), Fault Detection and Control Systems (3 papers) and Mineral Processing and Grinding (3 papers). Kristen Severson collaborates with scholars based in United States, Sweden and United Kingdom. Kristen Severson's co-authors include Richard D. Braatz, Patrick K. Herring, Zi Yang, Muratahan Aykol, Peter M. Attia, Michael H. Chen, Stephen J. Harris, William C. Chueh, Norman Jin and Martin Z. Bazant and has published in prestigious journals such as Nature, Bioinformatics and Cement and Concrete Research.

In The Last Decade

Kristen Severson

23 papers receiving 3.3k citations

Hit Papers

Data-driven prediction of... 2019 2026 2021 2023 2019 2020 500 1000 1.5k
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. Data-driven prediction of battery cycle life before capacity degradation
    2019 2.0k citations Kristen Severson, Peter M. Attia et al. profile →
  2. Closed-loop optimization of fast-charging protocols for batteries with machine learning
    2020 748 citations Peter M. Attia, Aditya Grover et al. Nature profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kristen Severson United States 15 2.3k 2.3k 604 422 270 24 3.4k
Michael H. Chen United States 11 2.3k 1.0× 2.2k 1.0× 382 0.6× 411 1.0× 250 0.9× 21 3.0k
Bin Duan China 30 2.1k 0.9× 2.4k 1.0× 1.0k 1.7× 264 0.6× 198 0.7× 200 3.4k
Benben Jiang China 19 2.2k 1.0× 2.1k 0.9× 853 1.4× 434 1.0× 149 0.6× 48 3.1k
Xueyuan Wang China 31 2.9k 1.2× 2.9k 1.3× 551 0.9× 215 0.5× 229 0.8× 131 3.7k
Yan Chen United States 25 1.8k 0.8× 837 0.4× 949 1.6× 100 0.2× 93 0.3× 132 3.0k
Lifeng Wu China 26 921 0.4× 925 0.4× 820 1.4× 361 0.9× 343 1.3× 77 2.3k
Weirong Chen China 45 3.2k 1.4× 5.1k 2.3× 1.7k 2.8× 108 0.3× 587 2.2× 260 6.8k
Widanalage Dhammika Widanage United Kingdom 37 4.8k 2.1× 4.6k 2.0× 821 1.4× 568 1.3× 114 0.4× 102 5.6k
Saurabh Saxena United States 19 1.2k 0.5× 1.2k 0.5× 200 0.3× 231 0.5× 80 0.3× 42 1.8k
Qi Zhang China 31 1.9k 0.8× 2.1k 0.9× 615 1.0× 173 0.4× 272 1.0× 183 3.1k

Countries citing papers authored by Kristen Severson

Since Specialization
Citations

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

Fields of papers citing papers by Kristen Severson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kristen Severson

This figure shows the co-authorship network connecting the top 25 collaborators of Kristen Severson. A scholar is included among the top collaborators of Kristen Severson 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 Kristen Severson. Kristen Severson 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.
2.
Hall, James M., et al.. (2024). Improving Mitosis Detection on Histopathology Images Using Large Vision-Language Models. 1–5. 3 indexed citations
3.
Severson, Kristen, Lana M. Chahine, Mark Frasier, et al.. (2021). Discovery of Parkinson's disease states and disease progression modelling: a longitudinal data study using machine learning. The Lancet Digital Health. 3(9). e555–e564. 52 indexed citations
4.
Severson, Kristen, et al.. (2020). Personalized Input-Output Hidden Markov Models for Disease Progression Modeling.. 309–330. 2 indexed citations
5.
Salemi, Marco, Kenney Ng, Kristen Severson, et al.. (2020). Identifying unreliable predictions in clinical risk models. npj Digital Medicine. 3(1). 14 indexed citations
6.
Kwon, Bum Chul, Vibha Anand, Kristen Severson, et al.. (2020). DPVis: Visual Analytics With Hidden Markov Models for Disease Progression Pathways. IEEE Transactions on Visualization and Computer Graphics. 27(9). 3685–3700. 42 indexed citations
7.
Attia, Peter M., Aditya Grover, Norman Jin, et al.. (2020). Closed-loop optimization of fast-charging protocols for batteries with machine learning. Nature. 578(7795). 397–402. 748 indexed citations breakdown →
8.
Shields, Alan L., et al.. (2019). PRO142 PSYCHOMETRIC PERFORMANCE OF THE INDOLENT SYSTEMIC MASTOCYTOSIS SYMPTOM ASSESSMENT FORM (ISM-SAF). Value in Health. 22. S867–S868. 1 indexed citations
9.
Ng, Kenney, et al.. (2019). Generative Oversampling with a Contrastive Variational Autoencoder. 101–109. 20 indexed citations
10.
11.
Severson, Kristen, et al.. (2018). Vasopressin Administration Is Associated With Rising Serum Lactate Levels in Patients With Sepsis. Journal of Intensive Care Medicine. 35(9). 881–888. 4 indexed citations
12.
13.
Severson, Kristen, Brinda Monian, J. Christopher Love, & Richard D. Braatz. (2017). A method for learning a sparse classifier in the presence of missing data for high-dimensional biological datasets. Bioinformatics. 33(18). 2897–2905. 9 indexed citations
14.
Hong, Moo Sun, et al.. (2017). Challenges and opportunities in biopharmaceutical manufacturing control. Computers & Chemical Engineering. 110. 106–114. 87 indexed citations
15.
Jiang, Mo, Kristen Severson, J. Christopher Love, et al.. (2017). Opportunities and challenges of real‐time release testing in biopharmaceutical manufacturing. Biotechnology and Bioengineering. 114(11). 2445–2456. 73 indexed citations
16.
Severson, Kristen, et al.. (2016). Perspectives on process monitoring of industrial systems. Annual Reviews in Control. 42. 190–200. 152 indexed citations
17.
Severson, Kristen, et al.. (2015). Perspectives on Process Monitoring of Industrial Systems ★ ★BP is acknowledged for funding.. IFAC-PapersOnLine. 48(21). 931–939. 18 indexed citations
18.
Severson, Kristen, et al.. (2015). Elastic net with Monte Carlo sampling for data-based modeling in biopharmaceutical manufacturing facilities. Computers & Chemical Engineering. 80. 30–36. 25 indexed citations
19.
Severson, Kristen, Mariano Martı́n, & Ignacio E. Grossmann. (2012). Optimal integration for biodiesel production using bioethanol. AIChE Journal. 59(3). 834–844. 30 indexed citations
20.
Severson, Kristen, et al.. (2010). Emergency Department Physical Therapist Service: A Pilot Study Examining Physician Perceptions. Internet Journal of Allied Health Sciences and Practice. 22 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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