My internship allowed my to rotate between three different roles, you can read the description of each role below. Software Engineer: - Develop code in Python for innovative DNA sequencing instrument - Fixing bugs and implementing new functionalities - Assembling and testing new instrument prototypes - Testing electrical characteristics of certain critical components - Designing Breakout PCB Systems Engineer: Increasing the yield of functioning sequencing cells on the chip - Design and execute experiments on nanopore sequencing platform - Scheduling of experiments, reserving instruments, ordering reagents and consumables, and assembling and organizing personnel as needed - Analysis of data - Visualization of spatial distribution of metrics, to reveal fluidic and electronic interactions - Statistical analysis of metrics including application of MANOVA - Develop, program and test new protocols that optimize the effect of the flow rate, volume of the reagents as well as the voltage waveform applied to the nanopore array during different steps. Deep Learning Engineer: - Developing the pipeline for training, evaluating and analyzing neural network models - Optimizing hyperparameters of the neural network models - Researching new deep learning methods (attentional layers, causal dilated convolutions, and memory networks)

Hypoxia (lack of oxygen) event Prediction for Patients with Traumatic Brain Injuries in the Neurological ICU Project: - Coordinated with Doctors and other Stakeholders (Luciole Start-up, Hospital IT team) to understand data, goals and status quo patient care procedures in the hospital. - Evaluated different technologies to use for project components. - Developed a multi-processed modular data processing pipeline with Python that processed 42TB of high resolution ICU time series measurement data in 30min. - Developed a visualization tool using Potly and Dash to inspect the data provided. Smart Toilet Seat Project: - Analyzed different market segments of advanced technological toilets and evaluated the market fit of the smart toilet project. - Evaluated technological feasibility of different sensors to be integrated in the toilet seat product. - Helped build the back-end solution using Python (Flask) and SQL that handles incoming toilet seat data. Built up and managed the lab LinkedIn page along with another teammate, to gain more traction and visibility from international LinkedIn members. It also became a very effective tool for hiring new employees for the lab.