Appointments

  • Adjunct Associate Professor, Deptartment of Biomedical Engineering, Oregon Health & Science University (OHSU)
  • Research Associate, National Center for Rehabilitative Auditory Research (NCRAR), Portland VA Medical Center.   

Education

  • Ph.D., 1994, Electrical Engineering, Stanford University
  • MS, 1988, Electrical Engineering, Stanford University
  • BS., 1987, Electrical Engineering, Stanford University

Research Interests

Algorithms and architectures for machine learning and adaptive signal processing, recursive Bayesian estimation using the sigma-point filter. Recent research has focused on applications of machine learning to biomedical engineering, with projects including indoor tracking and mobility assessment of elderly to support aging-in-place, noninvasive glucose monitoring, and real-time classification of flying insects for diseases vector monitoring.

Selected Publications

  1. Jacobs, P. G., Wan, E. A., Schafermeyer, E., Adenwala, F., Paul, A. S., Preiser, N., & Kaye, J. (2014, August). Measuring in-home walking speed using wall-mounted RF transceiver arrays. In Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE (pp. 914-917). 
  2. Paul, A. S., Wan, E. A., Adenwala, F., Schafermeyer, E., Preiser, N., Kaye, J., & Jacobs, P. G. (2014, September). MobileRF: a robust device-free tracking system based on a hybrid neural network HMM classifier. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 159-170). ACM.
  3. E. A. Wan and A. S. Paul, "A tag-free solution to unobtrusive indoor tracking using wall-mounted ultrasonic transducers," In proceedings of 2010 IEEE International Conference on Indoor Positioning and Indoor Navigation (IPIN), Zurich, Switzerland, September, 2010.   
  4. D. Gareau, R. Hennessy, E. Wan, G. Pellacani, S. L. Jacques.Automated detection of malignant features in confocal microscopy on superficial spreading melanoma versus nevi. Journal of Biomedical Optics 15(6), 061713 (November/December 2010)
  5. P.G. Jacobs, Wan, E.A., Kagen, D., & Konrad-Martin, D. Methodology for Improving Medial Olivocochlear (MOC) Reflex Measurements, American Auditory Society Annual Conference, March 2009.
  6. S. Paul and E. A. Wan.  RSSI Based Indoor Localization and Tracking Using Sigma-Point Kalman Smoothers. IEEE Journal of Selected topics in signal processing, 2010.
  7. R. van der Merwe and E. A. Wan. Sigma-Point Kalman Filters for Integrated Navigation, In Institute of Navigation Annual Technical Meeting, 2004.
  8. E. A. Wan, A. A. Bogdanov, R. Kieburtz, A. Baptista, M. Carlsson, Y. Zhang, and M. Zulauf, Model Predictive Neural Control for Aggressive Helicopter Maneuvers. In Software Enabled Control: Information Technologies for Dynamical Systems, IEEE Press, edited by Tariq Samad and Gary Balas, 2003.
  9. E. A. Wan and R. van der Merwe, The Unscented Kalman Filter. In Kalman Filtering and Neural Networks, chapter 7. The Unscented Kalman Filter, (62 pages), Wiley Publishing, edited S. Haykin, 2001.
  10. R. van der Merwe, A. Doucet, N. de Freitas and E. A. Wan. The Unscented Particle Filter. In Advances in Neural Information Processing Systems (NIPS13), MIT Press, Eds. T. K. Leen, T. G. Dietterich and V. Tresp, Dec, 2000. 
  11. E. A. Wan. Time Series Prediction Using a Neural Network with Embedded Tapped Delay-Lines. In Predicting the Future and Understanding the Past, A. Weigend and N. Gershenfeld Editors, SFI Studies in the Science of Complexity, Proc. vol. XVII, Addison-Wesley, 1993. 
  12. E. A. Wan. Neural Network Classification: A Bayesian Interpretation. IEEE Transactions on Neural Networks, vol. 1, no. 4, p. 303-305, December 1990.