- Ph.D. in Applied Mathematics, University of Washington, 2018
- M.S. in Applied Mathematics, University of Washington, 2015
- B.S. in Mathematics and Computer Science, University of Massachusetts Lowell, 2013
- Von Kármán Instructor in Computing and Mathematical Sciences, Caltech, Sep - Dec 2020
- Postdoctoral Scholar in Computing and Mathematical Sciences, Caltech, Oct 2018 - Aug 2020
Dr. Manohar’s research focuses on developing algorithms for data-driven prediction and control of complex dynamical systems. Her work uses dimensionality reduction techniques rooted in operator theory and manifold learning to discover physically meaningful features from data, and optimize sensors and actuators for downstream decision-making (sparse sensing). Target applications of sparse sensing optimization include fluid flow reconstruction, control, image recovery, and aircraft manufacturing. She is also interested in sparse sensing and forecasting in the context of partially observed multiscale systems, which commonly occur in fluid dynamics, materials science, and biology.
- Manohar, K., Kaiser, E., Brunton, S. L., & Kutz, J. N. (2019). "Optimized sampling for multiscale dynamics." Multiscale Modeling & Simulation, 17(1), 117-136.
- Manohar, K., Brunton, B. W., Kutz, J. N., & Brunton, S. L. (2018). "Data-driven sparse sensor placement for reconstruction: Demonstrating the benefits of exploiting known patterns." IEEE Control Systems Magazine, 38(3), 63-86.
- Manohar, K., Hogan, T., Buttrick, J., Banerjee, A. G., Kutz, J. N., & Brunton, S. L. (2018). "Predicting shim gaps in aircraft assembly with machine learning and sparse sensing." Journal of manufacturing systems, 48, 87-95.
- Manohar, K., Brunton, S. L., & Kutz, J. N. (2017). "Environment identification in flight using sparse approximation of wing strain." Journal of Fluids and Structures, 70, 162-180.
Honors & awards
- National Science Foundation Mathematical Sciences Postdoctoral Research Fellowship, 2018
- Boeing Award for Excellence in Research, University of Washington, 2017
- Seattle ARCS Foundation Fellowship, University of Washington, 2013-2017
AI Institute for Dynamic Systems
UW leading new NSF institute for using artificial intelligence to understand dynamic systems.
Welcome new faculty
Join us in welcoming new faculty to the ME department this school year.