Algorithm for success: Student gets awesome research experience
Algorithms are everywhere. Looking to bake a cake? There’s an algorithm for that. Want to throw in a load of laundry? There’s one for that too. A complex math equation? You guessed it.
In simplest terms, algorithms are processes for solving problems or accomplishing tasks. Key to the functionality of computer search engines, they are found in every computerized device. According to Britannica.com, algorithms are fundamental to all aspects of computer science: artificial intelligence, databases, graphics, networking, operating systems, security, and so on.
Heidelberg junior computer science major Chloe Duquette has some new expertise in algorithms after completing a 10-week Research Experience for Undergraduates through East Carolina University. Although originally planned to be in person, COVID-19 forced Chloe’s experience to move to remote.
Throughout the experience, she worked to expand her research on published and unpublished papers with ECU’s Computer Science professors.
“I learned a lot in those 10 weeks,” Chloe says. And all because she has an interest and desire to dive deeper into data science.
Each day, she spent about four hours researching and about three hours in meetings with her mentor and his grad students, as well as attending lectures by other professors at ECU and visiting lectures by experts from companies such as IBM and other universities. Additionally, she attended lectures about software engineering and code recommendation systems, and graduate student meetings, where discussion centered on research progress and recommendations for other research projects.
Chloe’s mentor, Dr. Sartipi, was working on training artificial intelligence (AI) to look through the event logs at hospitals and find events that were undermining hospitals’ cybersecurity.
“For example, if a staff member is signed in on two different computers, this could allow a non-staff member to access private patient data,” she explains.
Dr. Sarpiti had written a paper about creating artificial medical data for his AI to use since real medical data has restrictions surrounding its use. In response, Chloe wrote a paper on replacing an inefficient algorithm from an older published paper, with the newer Monte Carlo Tree Search algorithm.
Ultimately, Chloe pulled all of her research together in a presentation with an online trifold poster and PowerPoint “explaining why it was better to use the Monte Carlo algorithm.”
She feels much more confident now in understanding algorithms more quickly. And an unexpected takeaway: her communication skills improved.
“I have definitely improved my communication skills because I had to present my progress and my finished paper to esteemed computer science professors on a weekly basis,” she says. “I also learned to document my research daily, which was then compiled into a weekly report that was also presented to everyone.”
All of her research – and essentially, the entire REU experience – will be a great springboard for Chloe’s planned career in data science.