Niclas Ståhl

449 total citations
6 papers, 231 citations indexed

About

Niclas Ståhl is a scholar working on Molecular Biology, Control and Systems Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Niclas Ståhl has authored 6 papers receiving a total of 231 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Molecular Biology, 2 papers in Control and Systems Engineering and 2 papers in Computational Theory and Mathematics. Recurrent topics in Niclas Ståhl's work include Computational Drug Discovery Methods (2 papers), Fault Detection and Control Systems (2 papers) and Protein Structure and Dynamics (1 paper). Niclas Ståhl is often cited by papers focused on Computational Drug Discovery Methods (2 papers), Fault Detection and Control Systems (2 papers) and Protein Structure and Dynamics (1 paper). Niclas Ståhl collaborates with scholars based in Sweden. Niclas Ståhl's co-authors include Gunnar Mathiason, Göran Falkman, Alexander Karlsson, Jonas Boström, Yurong Li and Juhee Bae and has published in prestigious journals such as Journal of Chemical Information and Modeling, Applied Mathematical Modelling and Metallurgical and Materials Transactions B.

In The Last Decade

Niclas Ståhl

6 papers receiving 221 citations

Peers

Niclas Ståhl
Junkai Liu China
Cong Shen China
Xiran Wang China
Xiao‐Wei Guo China
Ziming Huang China
Chien Lee Taiwan
Vladimir Naumov Russia
Lixin Guan China
Yanlin Chen China
Manuel Pereira Remelhe Germany
Junkai Liu China
Niclas Ståhl
Citations per year, relative to Niclas Ståhl Niclas Ståhl (= 1×) peers Junkai Liu

Countries citing papers authored by Niclas Ståhl

Since Specialization
Citations

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

Fields of papers citing papers by Niclas Ståhl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Niclas Ståhl

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

All Works

6 of 6 papers shown
1.
Ståhl, Niclas, et al.. (2022). Identifying wetland areas in historical maps using deep convolutional neural networks. Ecological Informatics. 68. 101557–101557. 16 indexed citations
2.
Ståhl, Niclas, et al.. (2021). Using Reinforcement Learning for Generating Polynomial Models to Explain Complex Data. SN Computer Science. 2(2). 1 indexed citations
3.
Bae, Juhee, et al.. (2020). Using Machine Learning for Robust Target Prediction in a Basic Oxygen Furnace System. Metallurgical and Materials Transactions B. 51(4). 1632–1645. 38 indexed citations
4.
Ståhl, Niclas, Gunnar Mathiason, Göran Falkman, & Alexander Karlsson. (2019). Using recurrent neural networks with attention for detecting problematic slab shapes in steel rolling. Applied Mathematical Modelling. 70. 365–377. 29 indexed citations
5.
Ståhl, Niclas, Göran Falkman, Alexander Karlsson, Gunnar Mathiason, & Jonas Boström. (2019). Deep Reinforcement Learning for Multiparameter Optimization in de novo Drug Design. Journal of Chemical Information and Modeling. 59(7). 3166–3176. 136 indexed citations
6.
Ståhl, Niclas, Göran Falkman, Alexander Karlsson, Gunnar Mathiason, & Jonas Boström. (2018). Deep Convolutional Neural Networks for the Prediction of Molecular Properties: Challenges and Opportunities Connected to the Data. Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics. 16(1). 11 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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