Benjamín Béjar Haro

Benjamín Béjar Haro

Lead Data Scientist & group leader SDSC Hub at PSI
Academia
Leadership & Administration
(Alumni)

Benjamín Béjar received a PhD in Electrical Engineering from Universidad Politécnica de Madrid in 2012. He served as a postdoctoral fellow at École Polytechnique Fédérale de Lausanne until 2017, and then he moved to Johns Hopkins University where he held a Research Faculty position until Dec. 2019. His research interests lie at the intersection of signal processing and machine learning methods, and he has worked on topics such as sparse signal recovery, time-series analysis, and computer vision methods with special emphasis on biomedical applications. Since 2021, Benjamin leads the SDSC office at the Paul Scherrer Institute in Villigen.

Projects

ML-L3DNDT

Completed
Robust and scalable Machine Learning algorithms for Laue 3-Dimensional Neutron Diffraction Tomography
Large-scale Infrastructures

LAMP

Completed
Lensless Actinic Metrology for EUV Photomasks
Large-scale Infrastructures

DS4MS

Completed
Data Science for Multiplexing Spectrometers
Large-scale Infrastructures

DUPLET

In Progress
DUal Positron Lifetime Emission Tomography
Biomedical Data Science

ML-ED

Completed
Increased spatial resolution in electron detectors through machine learning
Large-scale Infrastructures

CHIP

In Progress
MaCHIne-Learning-assisted Ptychographic nanotomography
Large-scale Infrastructures

RED-ML

Completed
Reduction of high volume experimental data using machine learning
Large-scale Infrastructures

COVID-19

Completed
Epidemic Forecasting
Biomedical Data Science
Large-scale Infrastructures
Digital Administration

Publications

Xie, X.; Barba Flores, L.; Bejar Haro, B.; Bergamaschi, A.; Fröjdh, E.; Müller, E.; Paton, K.; Poghosyan, E.; Remlinger, C. "Enhancing spatial resolution in MÖNCH for electron microscopy via deep learning" Journal of Instrumentation 19 1 C01020 2024 View publication
Gasparotto, P.; Barba, L.; Stadler, H.; Assmann, G.; Mendonça, H.; Ashton, A. W.; Janousch, M.; Leonarski, F.; Béjar, B. "TORO Indexer: a PyTorch-based indexing algorithm for kilohertz serial crystallography" Journal of Applied Crystallography 57 4 931-944 2024 View publication
Sherratt, K.; Gruson, H.; Grah, R.; Johnson, H.; Niehus, R.; Prasse, B.; Sandmann, F.; Deuschel, J.; Wolffram, D.; Abbott, S.; et al. "Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations" eLife 12 e81916 2023 View publication
Cramer, E. Y.; Huang, Y.; Wang, Y.; Ray, E. L.; Cornell, M.; Bracher, J.; Brennen, A.; Rivadeneira, A. J. C.; Gerding, A.; House, K.; et al. "The United States COVID-19 Forecast Hub dataset" Scientific Data 9 1 462 2022 View publication
Krymova, E.; Béjar, B.; Thanou, D.; Sun, T.; Manetti, E.; Lee, G.; Namigai, K.; Choirat, C.; Flahault, A.; Obozinski, G. "Trend estimation and short-term forecasting of COVID-19 cases and deaths worldwide" Proceedings of the National Academy of Sciences 119 32 e2112656119 2022 View publication
Bracher, J.; Wolffram, D.; Deuschel, J.; Görgen, K.; Ketterer, J. L.; Ullrich, A.; Abbott, S.; Barbarossa, M. V.; Bertsimas, D.; Bhatia, S.; et al. "A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave" Nature Communications 12 1 5173 2021 View publication
Bejar, B.; Mischler, G. "A finite rate of innovation approach for the estimation of a stream of decaying exponentials" 2020 54th Asilomar Conference on Signals, Systems, and Computers 1497-1501 2020 View publication

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