- Designed and coded a framework in Python to emulate the functionality of the backend of a data storage product- Learned how the existing backend communicates using XML-RPC and sockets, and how it responds to requests sent to it by looking at the existing code base, using Postman to send out REST requests to the backend, and looking through log files- Wrote a clean API so later engineers can easily add to the emulator’s functionality, and wrote a unit test suite for easy testing- Modified existing executables’ Maven and Java configurations to instead send messages to and from the emulator- Packaged the emulator and other components in a container using Docker and a shell script, and extensively documented the emulator so future users can easily set up and use the emulator

- Used Python to process a day’s stock exchange orders to return max # orders in 1s, 1ms, 1us timeframes using Pandas and Multithreading libraries and a sliding window algorithm- Researched feasibility of calculating options prices using a GPU vs. CPU- Learned under-the-hood details of CUDA to implement different GPU approaches utilizing streams and callbacks considering shared memory, register, block size, and stream limits, warp execution, and memcpy overhead of the GPU- Used Matplotlib to compare and understand results- Observed that the GPU outperforms CPU in terms of total calculation time for more complex pricing models at the cost of higher per-option calculation time- Implemented a production tool to price incoming options using sockets and a GPU during market hours

- Learned and performed proper cell culture and pipetting techniques, electrohydrodynamic co-jetting (nanoparticle synthesis) procedure, nanoparticle separation protocol, and Dynamic Light Scattering and Nanosight operation- Started my own independent project towards the end of August designing multicompartmental protein nanoparticles with genetic payloads to escape degradation by swelling and rupturing lysosomes in the presence of low pH. I analyzed my data and did a poster presentation of my work at Biomaterials Day of U of M on October 6, 2017.