Data Science Showcase
Organized by Nouhad Rizk, Ph.D., Claudia Neuhauser, Ph.D., and Ishita Sharma, M.S., the event featured a keynote presentation by Feng Yan, Ph.D., and capstone presentations of Data Science by Rizk’s undergraduate Computer Science students.
“Our showcase is a terrific opportunity to expose undergraduate students to other research,” Rizk said. “This can not only help improve their research skills, but it may spark their interest in expanding their learning by seeking a graduate degree.”
Over the course of the fall semester, students in Rizk’s Data Science 2 class were given the opportunity to research a real-life topic using methods of Data Science. A total of 20 student groups presented. Each group explained their research using a guided visual analysis, which included details on their background, research methods, results and more.
The showcase aimed at educating students on the research process and research-related academic resources, while also providing them a channel of peer support and colloquia for a future in data analytics.
“Student participation in the showcase improves their ability to work through obstacles when learning something new,” Rizk said. “This is incredibly valuable and one of the true, lifelong benefits of undergraduate lessons.”
At the end of the event, a jury voted on the best student visualization presentations. Each winning group received a certificate of accomplishment, as well as cash prizes.
The winners included:
1st place - Group 9 (“Data Analyzation, Deep Learning and Cancer Diagnosis” by Tung Dinh, Sevban Sonmez and Benjamin Price)
2nd place - Group 7 (“Detection of Lung Cancer Using Convolutional Neural Networks” by Dosboi Allev, Kurmanbek Bazarov, Michael Moorman and Abraar Patel)
3rd place - Group 2 (“Detecting and Classifying Alzheimer’s Disease from MRI Scans Using Convolutional Neural Networks” by Alex Burns, Isaac Burns, Allen Arani and Victor Artiles)
4th place - Group 20 (“Classifying Text Messages as Spam Using Convolutional Neural Networks” by Elliot Farmer Garcia and Clark Nelson)
5th place - Group 21 (“Using Convolutional Neural Networks [CNN] to Detect Invasive Ductal Carcinoma” by Nathan Acosta, Seyed Hosseini Darabi, Mohammad Mahmoudzadeh and Shaz Maknojia)
“Our young researchers always surprise us with their research in great ways,” Sharma said. “Not to mention the data visualizations they presented were quite impressive.”
Yan’s short presentation, titled “Deep Learning in the Wild”, introduced the learning processes and structures of Deep Learning AI, where neural networks use vast amounts of data to learn like humans and construct proper features to a given problem. Focusing on the larger picture of deep learning mechanics, Yan also discussed real life applications, including face-tracking, object detection and virtual voice assistants.