CV

Education

• Ph.D. in Computer Science, University of New Mexico
• B.S. in Electrical and Computer Engineering, Carnegie Mellon University

Research

• Scientist, Information Sciences, Los Alamos National Laboratory
  • Project Leader / Principal Investigator:
    • Uncertainty quantification for robust machine learning
    • Visual data analytics tools
    • Image analysis using graphs
  • Applications of machine learning projects include learning image analysis, ChemCam spectroscopy data analysis, malware characaterization, and other scientific data analysis problems.
• Postdoctoral Research Associate, Space Data Science and Systems, Los Alamos National Laboratory
  • Interactive machine learning for ChemCam data analysis, image analysis and satellite system state-of-health anomaly detection.

Recent Publications

• Generative Structured Normalizing Flow Gaussian Processes Applied to Spectroscopic Data. (2022). AAAI Workshop on AI to Accelerate Science and Engineering (AI2ASE) [Best Paper Award].
• Kucer, M., Oyen, D., Castorena, J., & Wu, J. (2022). DeepPatent: Large scale patent drawing recognition and retrieval. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision.
• Oyen, D., Kucer, M., & Wohlberg, B. (2021). VisHash: visual similarity preserving image hashing for diagram retrieval. Applications of Machine Learning 2021.
• Kontolati, K., Klein, N., Panda, N., & Oyen, D. (2021). Neural density estimation and uncertainty quantification for laser induced breakdown spectroscopy spectra. ArXiv Preprint ArXiv:2108.08709.
• Banesh, D., Panda, N., Biswas, A., Van Roekel, L., Oyen, D., Urban, N., Grosskopf, M., Wolfe, J., & Lawrence, E. (2021). Fast Gaussian Process Estimation for Large-Scale In Situ Inference using Convolutional Neural Networks. IEEE International Conference on Big Data.
• Wang, Y., Oyen, D., Guo, W. G., Mehta, A., Scott, C. B., Panda, N., Fernández-Godino, M. G., Srinivasan, G., & Yue, X. (2021). StressNet: Deep learning to predict stress with fracture propagation in brittle materials. Npj Materials Degradation, 5(1), 1–10.
• Castorena, J., Oyen, D., Ollila, A., Legget, C., & Lanza, N. (2021). Deep Spectral CNN for Laser Induced Breakdown Spectroscopy. Spectrochimica Acta Part B: Atomic Spectroscopy.
• Fernandez-Godino, M. G., Panda, N., O’Malley, D., Hickmann, K. S., Oyen, D. A., Haftka, R. T., & Srinivasan, G. (2020). Flyer Plate Continuum Simulations Informed with Machine Learning Crack Evolution. AIAA Scitech 2020 Forum.

• See longer list

Teaching

• How to Lie with Statistics: Uses and Misuses of Numbers in Argument
  • Honors 302-005, University of New Mexico, 2013
  • See website

Service and Leadership

• Co-organizer, Applied Machine Learning Summer Research Fellowship (AML)
• Program committee member of AAAI, ICML, NIPS, IJCAI, UAI, AIStats, others