Esben Jannik Bjerrum
Esben Jannik Bjerrum publishes mostly in Computational Theory and Mathematics, Materials Chemistry and Molecular Biology, on topics such as Computational Drug Discovery Methods, Machine Learning in Materials Science and Chemical Synthesis and Analysis.
- World rank
- #229,580 of 7,710,434 ranked researchers
- Rank in Sweden
- #2,545 of 71,437
- Works
- 135
- Citations
- 5k
- Citations per work
- 37.3
What does Esben Jannik Bjerrum research?
Esben Jannik Bjerrum's work is mostly in Computer Science (31%), Materials Science (24%), Biochemistry, Genetics and Molecular Biology (21%).
Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.
The fields and subfields, with their numbers
- Physical Sciences8563.1%
- Computer Science4130.7%
- Materials Science3324.4%
- Chemistry64.3%
- Engineering53.7%
- Life Sciences2820.6%
- Everything else2216.3%
- 1Computational Theory and Mathematics28% of their works
- 2Materials Chemistry24% of their works
- 3Molecular Biology21% of their works
- 4Spectroscopy4% of their works
- 5Biomedical Engineering4% of their works
- 6Artificial Intelligence3% of their works
Research topics
- Computational Drug Discovery Methods
- Machine Learning in Materials Science
- Chemical Synthesis and Analysis
- Analytical Chemistry and Chromatography
- Protein Structure and Dynamics
- Innovative Microfluidic and Catalytic Techniques Innovation
- Machine Learning in Bioinformatics
- Chemistry and Chemical Engineering
Which keywords describe Esben Jannik Bjerrum's research?
The keywords of their largest research topics: Machine Learning, Medicinal Chemistry, Molecular Dynamics, Molecular Docking, Virtual Screening, High-Throughput, Materials Informatics and Drug Discovery.
- Subcellular Localization
- Amino Acid Composition
- Microfluidics
- Droplet Formation
- Chiral Separation
- Prediction
- Drug Discovery
- High-Throughput
- Molecular Docking
- Medicinal Chemistry
- Machine Learning
- Molecular Dynamics
- Virtual Screening
- Materials Informatics
- Peptide Synthesis
- Protein
- Liquid Chromatography
- Force Field
- Structure
- Solvent Selection
- Sustainable Chemistry
Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.
All 21 words, with their numbers
- Machine Learning1883 topics
- Medicinal Chemistry1032 topics
- Molecular Dynamics972 topics
- Molecular Docking951 topic
- Virtual Screening951 topic
- High-Throughput851 topic
- Materials Informatics851 topic
- Drug Discovery351 topic
- Peptide Synthesis351 topic
- Prediction202 topics
- Protein202 topics
- Chiral Separation151 topic
- Liquid Chromatography151 topic
- Droplet Formation121 topic
- Force Field121 topic
- Microfluidics121 topic
- Structure121 topic
- Amino Acid Composition81 topic
- Solvent Selection81 topic
- Subcellular Localization81 topic
- Sustainable Chemistry81 topic
Where does Esben Jannik Bjerrum work?
Esben Jannik Bjerrum's main affiliation in the publication record is AstraZeneca (Sweden), Sweden.
How many publications and citations does Esben Jannik Bjerrum have?
OpenAlex counts 135 works and 5,030 citations for Esben Jannik Bjerrum, an h-index of 31, ranking #229,580 of 7,710,434 researchers worldwide on the quality score.
Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.
Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.
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