Available Positions
Postdoctoral positions and graduate rotation projects are currently available in the area of sporting brain injuries. We have instrumented multiple Stanford varsity teams with sensors to measure head blows during play. In parallel, we use laboratory impact models to generate injury hypotheses. Our ultimate goal is to uncover the mechanism of concussions and to develop preventative and diagnostic technologies. This research is imperative to understanding and reducing chronic neurodegeneration in athletes, soldiers, and civilians.

We have a Postdoctoral Scholar position opening! Link

Biomechanics of concussion

Traumatic brain injury (TBI) has been identified as a major health concern by the U.S. Center for Disease Control and Prevention and 75% of reported incidents are categorized as concussion or mild. TBI affects a broad swath of the population, from infants to the elderly in falls, and all ages in between due to vehicular accidents, violence, and sports. Injury to one's brain is particularly debilitating as it can affect our most basic functions such as learning, communicating, and thinking. Concussion is a mild form of TBI that has risen at an alarming rate in sports and now accounts for an estimated 1.6-3.8 million cases of TBI in the U.S.

We are instrumenting Stanford athletes with inertial sensors to investigate the mechanism of concussion. The mouthguard to the left is worn by Stanford football players and women's lacrosse to measure the "dose" of impact. We are also characterizing the response of head-blows through imaging, blood, and other neurophysiological measurements. Understanding the mechanism of concussion will allow for change of rules, technique, or the development of preventive equipment and diagnostics to reduce brain injuries.

Reproductive biomechanics

Nearly 1 out of 6 couples in the U.S. seeking to have children experience infertility, and many turn to in vitro fertilization (IVF) to become pregnant. However, only 30% of IVF cycles result in a live birth. During IVF, a clinician attempts to select the most viable embryos to transfer back to the mother based on a morphological assessment at day 3 after fertilization. This assessment is a poor predictor of viability, so multiple embryos are transferred back to the mother in 90% of cases in order to increase the chances for a successful pregnancy. Ideally, only one embryo should be transferred to eliminate the risks associated with multiple gestation pregnancies such as premature birth, low birth weight, and adverse health events for the mother.

We are developing a quantitative, noninvasive and early (day 1) measure of viability in order to allow clinicians to transfer the single most viable embryo, reducing the incidence of multiple gestations while preserving the pregnancy and birth rate of IVF.

Soft surgical robots

The use of robotics for surgical interventions have become more and more popular. By introducing new robotic devices into the body that are controlled remotely by a surgeon, it is possible to improve the dexterity of the surgeon, the precision of cuts, sutures, and ablations. Minimizing the size and number of cuts to the body reduces patient trauma, reduces recovery time and hospital stay.

In our lab, we are currently focusing on robotic catheterization for curing cardiac arrhythmia, a type of chronic diseases where abnormal electrical activity within the heart cause it to beat in a morphologically irregular manner, resulting in poor blood flow efficiency, increased stress on the heart, and formation of blood clots leading to embolisms and strokes. We aim to improve the usability and improve the safety of the process of cardiac catheter ablation through robotic control. We are currently investigating new control methods, medical image guidance, and automation for robotic catheter procedures.

The Camarillo lab are looking for undergraduate and graduate rotation students who have an interest in medical robotics and robot automation for surgery. The students will be in charge of a new project that involves integrating 3D medical imaging data guiding a flexible robotic catheter into the beating heart in order to perform surgical procedures. This would be a multi-disciplinary project, involving medical image registration, robot path planning, and robot automation. Robot sensor instrumentation and robot design may also be involved. The following background and skills are desirable:
  1. C++ programming, Matlab
  2. Familiarity with computer vision, computer graphics or image processing
  3. Statistical signal processing and/or machine learning
  4. Robotics
We are happy to work with you to figure out what what your strengths and interests are so that both of our research goals are achieved, and extensions into the following quarters may be available. Currently, we are only offering course credit for rotation students

Please contact Michael Yip (mcyip@stanford.edu) and cc the Camarillo Lab (camarillolab@gmail.com). When you reply, we'd like to know what you are interested in working on for this project and send a CV, and we will contact you in a few days.