I was a student researcher in Michael (Miki) Lustig's research group. My research was on computational medical imaging, specifically on investigating computer vision/computational imaging algorithms for MR data.My main interest was in unsupervised, single shot learning for inverse problems. I worked on a deep decoder generative network (mDD) for image denoising and subsampled MR image reconstruction that would enable faster scan times. I also worked on deep learning based de-blurring of MR images that were acquired via spiral acquisition of k-space.My previous research in this group related to stitching volumetric MR images in order to minimize overlap artifacts.

I have been a uGSI for EE16B (Designing Information Devices and Systems II), CS61C (Computer Architecture), EE120 (Signals and Systems), and EECS127 (Linear Algebra and Optimization Models).For EECS127, I was in charge of the homework content (creation, consolidation, and release). I also created jupyter notebook labs with an emphasis on imaging related applications (compression, pose estimation, restoration).For EE120, I also created new, application-based jupyter notebook labs related to stock price tracking and communication systems.For all classes, I taught either a lab or discussion of 25-50 students, held my own office hours, and proctored and graded exams.

During my summer at Apple, I worked on two separate projects. In both, my work entailed applying software engineering principles in a cybersecurity context. All my work is under an NDA, but I have a brief description of both projects below.My first project was a solo project, in which I created a Command Line Interface in order to perform complex queries on a distributed graph database.My second project was a group project, where I designed and implemented a server automation workflow. My responsibilities specifically were related to backend scripts and server orchestration.