Research Experience for Undergraduates in Computational Sensing and Medical Robotics Program 2015
The Computational Sensing and Medical Robotics Research Experience for Undergraduates program was held from late May through the end of July this year. Eleven students participated in the program and worked on challenging research projects. In addition to working closely with faculty mentors and graduate student mentors on their research, the students also learned about real-world opportunities. They visited a robotics lab at NASA Goddard and toured that facility, as well as had conversations about current projects with engineers at a local medical device company. In addition, the students took a class that helped aimed at honing their scientific presentation skills. The 10-week experience concluded with the students taking part in the Homewood Research Symposium. Ralph Etienne-Cummings, professor and chair of the Department of Electrical and Computer Engineering, and Suchi Saria, assistant professor in the Department of Computer Science, co-directed the program.
Learn more about the program.
REU Student and Research Topic
Alexander Serrano – Joint Spatial and Angular Representation for Sparse Reconstruction of HARDI
Alicia Dagle – Experimental Analysis of Energy Safety Limits for Photoacoustic-Guided Endonasal Surgery
Andreas Fatschel – Flexible Needle Shape Reconstruction based on FBG Sensors
Derek Dalbey – Improvements to Virtual Reality System for Advanced Manufacturing Robots
Jennifer Hu – Development of Interactive Front-end Software for cisst/SAW Medical Robot System
Logan Ellis – RVinci: RViz Interaction and Navigation with da Vinci
Michelle Isaacs – The Role of Active Sensing in Locomotion
Molly O’Brien – Improving Tracking Accuracy via Fusion of Electromagnetic and Inertial Sensing
Sayed Abulnaga – Toolbox to Visually Explore Cerebellar Shape Changes in Cerebellar Disease and Dysfunction
Giorgia Willits – Robotic Drilling for Single-Stage Cranioplasty
Adam Gropp – Dynamically Reconfigurable Silicon Integrate and Fire Array Transceiver using the Mihalas-Niebur Neuron Model