Curriculum Vitae

Work experience

Computer Project Scientist @ Lawrence Berkeley National Laboratory | CAMERA | MBIB

• Deep learning and neural network architecture design

• Uncertainty quantification

• Readily working with biologists, physicists, theorists, and experimentalists in many domains

Postdoctoral Appointee @ Lawrence Berkeley National Laboratory | Advanced Light Source

• Deep learning-based image retrieval

• Sparse quadrature numerical integration

PhD in Applied Mathematics @ University of California, Merced

• Topological fluid dynamics

Education

PhD in Applied Mathematics @ University of California, Merced

Advised by: Suzanne Sindi and Kevin A. Mitchell

• Area: Intersection of computational geometry, topology, and Lagrangian fluid dynamics

Bachelors in Applied Mathematics @ University of California, Los Angeles

 Selected Publications

Eric J. Roberts, Eric Betzig, et al. “Ensemble Learning for 3D Scientific Imaging.” arXiv preprint (expected Fall 2023).

Eric J. Roberts and Petrus H. Zwart. “DLSIA: Deep Learning for Scientific Image Analysis.” IUCr: Journal of Applied Crystallography, (forthcoming, 2023).

Eric J. Roberts, Guanhua Hao, et al. “Deploying machine learning based segmentation for scientific imaging analysis at synchrotron facilities. ”Society for Imaging Science and Technology (IS&T), (2023).

Eric J. Roberts, Niraj Gupta, et al. “Deep learning based identification of sub-nuclear structures in FIB-SEM images.” arXiv preprint (expected Winter 2023/24).

Howard Yanxon, Eric J. Roberts , et al. “Image segmentation using U-Net architecture for powder x-ray diffraction images.” ICCV, (submitted 2023).

Zhuowen Zhao, Tanny Chavez, Eric J Roberts, et al. “MLExchange a machine learning platform.” 2022 IEEE 4rd XLOOP Workshop (2022).

Tanny Chavez, Eric J. Roberts, Petrus H. Zwart, et al. “A Comparison of Deep Learning-based Inpainting for Experimental X-ray Scattering.” IUCr: Journal of Applied Crystallography, (2022).

Daniela Ushizima, Romuere Silva, Flavio Araujo, Eric J. Roberts, et al. “Automated Sorting of X-ray Scattering Patterns with Convolutional Neural Networks.” IPCV, Research Book Series: Transactions on Computational Science & Computational Intelligence, (2021).

Amanda Tan, Eric J. Roberts, et al. “Topological chaos in active nematics.” Nature Physics, (2019).

Eric J. Robert, Suzanne Sindi,  et al. “Ensemble-based topological entropy calculation (E-tec).” Chaos: An Interdisciplinary Journal of Nonlinear Sciences, (2019).

Amanda Tan, Eric Roberts, Kevin Mitchell, and Linda Hirst. "Investigating Quality of Mixing of a Biological Active Nematic." Cell: Biophysics Journal, (2018).