Research and development of novel deep learning architectures for classification, object detection, landmark detection, semantic segmentation, and more. At Siemens Healthcare we specialize in building software to automate and assist in the process of reading medical images (such as X-ray, CT, MRI, ultrasound, etc.).

Wrote customized, high-performance computer vision software, using state-of-the-art and novel deep learning techniques. In my largest project, I developed an HTTP web service for object classification and semantic segmentation. The server-side application consists of multiple artificial neural networks written using the Torch7 deep learning framework. These neural networks train and evaluate on multi-GPU EC2 instances.

As a graduate researcher, I studied mathematical aspects of exotic quantum field theories. I worked both independently and collaboratively on cutting-edge research and authored papers published in a highly respected physics journal. A more detailed explanation of my research is presented under Education.As a graduate teaching assistant, I taught several different introductory and advanced level undergraduate courses in classical mechanics, electrodynamics, and quantum mechanics. I led discussion sections, giving short lectures to groups of approximately 20-30 students, helping them solve physics problems, occasionally helping to prepare quizzes or exams, and grading solutions. I also led a number of laboratory classes of 30+ students.

As a graduate researcher, I participated in two large neutrino oscillation experiments, writing code for testing and simulation.As a graduate teaching assistant, I assisted in setting up laboratory equipment and guiding students through two hour labs, experimenting with analog and digital circuitry.