Aivett Bilbao
Computational Scientist
Dr. Aivett Bilbao is a computational scientist in the Computing, Analytics, and Modeling science area, leading the development and application of advanced algorithms and software tools for mass spectrometry (MS) and artificial intelligence/machine learning (AI/ML) integration in scientific research and instrumentation. She works directly with biologists and chemists in interdisciplinary teams and collaborates with EMSL users who are eager to leverage EMSL’s cutting-edge resources, including omics instrumentation and AI software, to advance their research.
Her expertise and interests encompass various omics, MS instrumentation, analytical separations, programming languages, and leveraging modern AI for understanding microbial processes at the molecular scale and for advancing several interdisciplinary research projects spanning biology, biotechnology, and environmental sciences. Bilbao is passionate about creating user-friendly scientific software, utilizing AI for science, mentoring interns, and promoting diversity through inclusive research practices.
She earned a bachelor’s degree in computer engineering (cum laude) from Universidad de Oriente, Venezuela, and an MSc in automatic data processing focused on ML and statistical methods from Telecom SudParis and Université de Versailles Saint-Quentin-en-Yvelines, France. During her graduate studies at the University of Geneva and the SIB Swiss Institute of Bioinformatics, Switzerland, she developed innovative software tools for proteomics and metabolomics, earning a PhD in Interdisciplinary Sciences/Computational Biology in 2016. She then joined Pacific Northwest National Laboratory in the United States as a postdoctoral fellow, where she has been developing tools for MS-based omics research and contributing to high-impact projects since 2019 as a staff scientist.
Research Interests
- Artificial intelligence
- Machine learning
- Mass spectrometry
- Ion mobility spectrometry
- Data-independent acquisition
- Proteomics
- Metabolomics
- Multiomics
- Microbial activity
- Systems and Synthetic biology
- Computational methods
- Algorithm development
- Data science
- Scientific instrumentation,
- Scientific software
Education
- Postdoc in Computational Mass Spectrometry, PNNL (2019)
- PhD in Computational Mass Spectrometry, University of Geneva, Switzerland (2015)
- MSc in Automatic Data Processing, TELECOM SubParis, France (2011)
- BSc in Computer Engineering, Universidad de Oriente, Venezuela (2007)
Awards and Recognition
- 2024 Emerging Investigators Special Issue in the Journal of the American Society for Mass Spectrometry (2024).
- PNNL Outstanding Performance Award for above and beyond contribution organizing the TechFest Conference (2024).
- Outstanding Reviewer Award from the Journal of the American Society for Mass Spectrometry (2023).
- PNNL Pathway to Excellence, Software creator award and Key contributor award (2022)
- The Swiss Initiative in Systems Biology (SystemsX) IPhD funding (2015)
- Fundayacucho Venezuelan Full Scholarship for MSc studies in France (2009-2011)
- Cum Laude BSc degree (2007)
Affiliations and Professional Service
- American Society for Mass Spectrometry
Publications
2020
Conant, C. R., Attah, I. K., Garimella, S. V., Nagy, G., Bilbao, A., Smith, R. D., & Ibrahim, Y. M. (2020). Evaluation of Waveform Profiles for Traveling Wave Ion Mobility Separations in Structures for Lossless Ion Manipulations. Journal of the American Society for Mass Spectrometry. https://doi.org/10.1021/jasms.0c00282
2019
Gabelica, V., A. A. Shvartsburg, C. Afonso, P. Barran, J. L. P. Benesch, C. Bleiholder, M. T. Bowers, A. Bilbao, M. F. Bush, J. L. Campbell, I. D. G. Campuzano, T. Causon, B. H. Clowers, C. S. Creaser, E. De Pauw, J. Far, F. Fernandez-Lima, J. C. Fjeldsted, K. Giles, M. Groessl, C. J. Hogan, Jr., S. Hann, H. I. Kim, R. T. Kurulugama, J. C. May, J. A. McLean, K. Pagel, K. Richardson, M. E. Ridgeway, F. Rosu, F. Sobott, K. Thalassinos, S. J. Valentine, and T. Wyttenbach. 2019. “Recommendations for Reporting Ion Mobility Mass Spectrometry Measurements.” Mass Spectrometry Reviews 38 (3): 291-320. https://doi.org/10.1002/mas.21585.
2018
Bilbao, A. 2018. “Proteomics Mass Spectrometry Data Analysis Tools.” In Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, 84-95. https://doi.org/10.1016/B978-0-12-809633-8.20274-4.
Bilbao, A., B. C. Gibbons, G. W. Slysz, K. L. Crowell, M. E. Monroe, Y. M. Ibrahim, R. D. Smith, S. H. Payne, and E. S. Baker. 2018. “An Algorithm to Correct Saturated Mass Spectrometry Ion Abundances for Enhanced Quantitation and Mass Accuracy in Omic Studies.” International Journal of Mass Spectrometry 427: 91-99. https://doi.org/10.1016/j.ijms.2017.11.003.
Bilbao, A., and F. Lisacek. 2018. “Bioinformatics Support for Farm Animal Proteomics.” In Proteomics in Domestic Animals: From Farm to Systems Biology, 361-386. https://doi.org/10.1007/978-3-319-69682-9_18.
2017
Allen White, R., M. I. Borkum, A. Rivas-Ubach, A. Bilbao, J. P. Wendler, S. M. Colby, M. Köberl, and C. Jansson. 2017. “From Data to Knowledge: The Future of Multi-Omics Data Analysis for the Rhizosphere.” Rhizosphere 3: 222-229. https://doi.org/10.1016/j.rhisph.2017.05.001.
White, R. A., III, A. Rivas-Ubach, M. I. Borkum, M. Köberl, A. Bilbao, S. M. Colby, D. W. Hoyt, K. Bingol, Y. M. Kim, J. P. Wendler, K. K. Hixson, and C. Jansson. 2017. “The State of Rhizospheric Science in the Era of Multi-Omics: A Practical Guide to Omics Technologies.” Rhizosphere 3: 212-221. https://doi.org/10.1016/j.rhisph.2017.05.003.
Zheng, X., N. A. Aly, Y. Zhou, K. T. Dupuis, A. Bilbao, V. L. Paurus, D. J. Orton, R. Wilson, S. H. Payne, R. D. Smith, and E. S. Baker. 2017. “A Structural Examination and Collision Cross Section Database for over 500 Metabolites and Xenobiotics Using Drift Tube Ion Mobility Spectrometry.” Chemical Science 8 (11): 7724-7736. https://doi.org/10.1039/c7sc03464d.