STIP Student Alexis Robbins Works with Machine Learning to Integrate Medical Applications with Computer Science

 What initially interested me about this project was the future implications to biomedical advancement. These cutting-edge computer science techniques, computer vision and machine learning, allow pattern recognition to be successful in problems that were previously too complex and contained to many variables. And the future medical applications of this, especially with systems as complex as the human body, are practically endless.

This project has given me a great amount of experience with coding and research that will be very useful in my future career. Specifically, learning data science research procedures in a biomedical setting was extremely valuable.

A typical workweek begins with a Monday morning group meeting discussing our successes and failures and how to improve our trajectory for the research and well as key ideas to explore. During the week we are mostly conducting in depth research and experimentation; this is mostly writing scripts, troubleshooting, organizing input data and possibly running neural network trials, comparing and analyzing results. The week concludes with a team meeting on Friday with our other partner research groups, Health Informatics and Nursing, along with all respective faculty mentors.

After looking back on the project, I realized that I discovered a passion for data science. I have begun to build an understanding of how powerful recent technology can be in solving problems that were previously unsolvable.