Benjamín Béjar Haro, PhD
Assistant Research Professor
Office: Clark 320A
PhD, Electrical Engineering, Universidad Politécnica de Madrid, Spain, 2012
MSE, Biomedical Engineering, Johns Hopkins University, 2013
BS, Electrical Engineering (double degree), Universidad Politecnica de Catalunya, Spain; the Technische Universität Darmstadt, Germany 2006
Benjamín Béjar Haro is an assistant research professor in the Mathematical Institute for Data Science in the Department of Biomedical Engineering at Johns Hopkins University. His research interests include digital signal processing, sampling and reconstruction of signals, image processing, convex optimization, and machine learning with applications to biomedical imaging.
B. Béjar and M. Vetterli, “Sampling Continuous-time Sparse Signals: A Frequency-domain Perspective,” in IEEE Transactions on Signal Processing, 2018, doi: 10.1109/TSP.2018.2791973.
N. Ahmidi, L. Tao, S. Sefati, Y. Gao, C. Lea, B. Béjar, L. Zappella, S. Khudanpur, R. Vidal and G. D. Hager, “A Dataset and Benchmarks for Segmentation and Recognition of Gestures in Robotic Surgery,” IEEE Transactions on Biomedical Engineering, 2017.
B. Béjar, S. Zazo and D. P. Palomar, “Energy-efficient Collaborative Beamforming in Wireless Sensor Networks,” IEEE Transactions on Signal Processing, Volume 62, Issue 2, January 2014, Pages 496 — 510.
L. Zappella, B. Béjar and R. Vidal, “Surgical gesture classification from video and kinematic data,” Medical Image Analysis, Volume 17, Issue 7, October 2013, Pages 732-745, ISSN 1361-8415, http://dx.doi.org/10.1016/j.media.2013.04.007.
B. Béjar, L. Zappella and R. Vidal, “Surgical Gesture Classification from Video Data,” MICCAI 2012, Nice, October 2012. *Best Paper Award on Surgical Robotics and CAI Systems.