Tom Sercu
Impact in
- Molecular Biology top 1%
- Machine Learning in Bioinformatics
- Protein Structure and Dynamics
- vaccines and immunoinformatics approaches
- Enzyme Catalysis and Immobilization
- Genomics and Phylogenetic Studies
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
Papers in
-
- Speech Recognition and Synthesis 6
- Adversarial Robustness in Machine Learning 1
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- Data Visualization and Analytics 1
- Multimodal Machine Learning Applications 1
- Generative Adversarial Networks and Image Synthesis 1
- Co-authors
- Alexander W. Rives (2 shared papers)Zeming Lin (2 shared papers)Allan dos Santos Costa (1 shared paper)Brian Hie (1 shared paper)Salvatore Candido (1 shared paper)Maryam Fazel-Zarandi (1 shared paper)Roshan Rao (1 shared paper)Zhongkai Zhu (1 shared paper)
- Journals
- Science (2 papers)Proceedings of the National Academy of Sciences (1 paper)International Conference on Learning Representations (2 papers)IEEE International Conference on Acoustics Speech and Signal Processing (3 papers)Interspeech (USB) (3 papers)
- Partner nations
- United States
In The Last Decade
Tom Sercu
14 papers receiving 5.6k citations
Tom Sercu's Hit Papers
Peers
Comparison fields: 5 of 107
- Molecular Biology 2.6k
- Computational Theory and Mathematics 524
- Microbiology 112
- Artificial Intelligence 472
- Health Informatics 27
Countries citing papers authored by Tom Sercu
This map shows the geographic impact of Tom Sercu'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 Tom Sercu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom Sercu more than expected).
Fields of papers citing papers by Tom Sercu
This network shows the impact of papers produced by Tom Sercu. 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 Tom Sercu. The network helps show where Tom Sercu may publish in the future.
Co-authors
The 25 scholars most cited alongside Tom Sercu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Evolutionary-scale prediction of atomic-level protein structure with a language model Hit paper breakdown → | 2023 | 2950 |
| 2 | Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences Hit paper breakdown → | 2021 | 1843 |
| 3 | Simulating 500 million years of evolution with a language model Hit paper breakdown → | 2025 | 376 |
| 4 | 2017 | 265 | |
| 5 | 2016 | 157 | |
| 6 | 2016 | 82 | |
| 7 | 2019 | 33 | |
| 8 | 2017 | 29 | |
| 9 | 2016 | 25 | |
| 10 | 2017 | 16 | |
| 11 | Fisher GAN | 2017 | 15 |
| 12 | 2021 | 7 | |
| 13 | Interactive Visual Exploration of Latent Space (IVELS) for Peptide Auto-Encoder Model Selection | 2019 | 4 |
| 14 | Improved Adversarial Image Captioning | 2019 | 1 |
About Tom Sercu
Tom Sercu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Nuclear Energy and Engineering and Waste Management and Disposal, having authored 14 papers that have together received 5.8k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (6 papers), Protein Structure and Dynamics (2 papers), Adversarial Robustness in Machine Learning (1 paper), Data Visualization and Analytics (1 paper), Multimodal Machine Learning Applications (1 paper), Generative Adversarial Networks and Image Synthesis (1 paper) and Machine Learning in Bioinformatics (1 paper). The work is most often cited by research in Molecular Biology (2.6k citations), Computational Theory and Mathematics (524 citations), Microbiology (112 citations), Artificial Intelligence (472 citations) and Health Informatics (27 citations). Tom Sercu has collaborated with scholars based in United States. Frequent co-authors include Alexander W. Rives, Zeming Lin, Allan dos Santos Costa, Brian Hie, Salvatore Candido, Maryam Fazel-Zarandi, Roshan Rao, Zhongkai Zhu, Robert Verkuil and C. Lawrence Zitnick. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences, International Conference on Learning Representations, IEEE International Conference on Acoustics Speech and Signal Processing and Interspeech (USB).
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.