Three teams of students from Illinois Institute of Technology competed in the 23-hour Kraft Data Dive Challenge on April 18-19 in Kraft’s downtown Chicago office. They solved real-world big data problems in one of three categories–clustering, segmentation, or predictive modeling–using Kraft’s large database of consumer information.
Each team was supported by a coach designated by Kraft, as well as technical experts from Kraft and event co-sponsors Intel, SAP, and IBM. Teams had between 11 a.m. on April 18 until 10 a.m. on April 19 to solve their problem. Each team presented their findings to a panel of judges. Winning teams from the University of Illinois at Chicago, Purdue University, and Northwestern University each received $5,000.
Participating Illinois Tech student teams were:
Jason Giesler, Master of Data Science
Shilpa Mandal, Master of Data Science
Saurabh Sharma, Master of Data Science
Yuzhang Hu, Master of Computer Science
Xiaoyu Qian, Master of Data Science
Xiaoang Zhang, Master of Data Science
Chengnan Zhao, Master of Computer Science
Jingyu Zhu, Master of Science in Computer Science
Haocheng Bian, B.S. in Computer Science and B.S. in Applied Math
Yi Jin, Master of Data Science
Jingqian Li, Master of Data Science
Kraft is one of the largest consumer packaged goods companies in North America, with 22,500 employees across the United States and Canada and $18 billion in annual sales.
“This was an exciting opportunity for our students to engage with a leading company in the food industry and show what innovative things they can do,” said Shlomo Engelson Argamon, professor of computer science and director of the Master of Data Science program. “The difficulties of working with the plethora of data in a company like Kraft are enormous. This is exactly the kind of challenge that our students are passionate about addressing.”
Unlike many business or liberal arts school programs, which teach students how to answer well-defined questions, IIT’s Master of Data Science program teaches students how to analyze data like a scientist and creatively uncover value hidden in data. Students acquire a deep and broad knowledge of theoretical principles of machine learning, statistics, high-performance computing, and data engineering, as well as the practical skills to apply them. They also learn how to be effective communicators and ethically work with data. Students integrate this knowledge through a real-world data science practicum, working with leading Chicago-area companies and researchers.