Halieab Hilafu has background unique among college professors in the United States. “I was born in a remote village near Keren, Eritrea, and finished my college studies in Eritrea,” he says.
In the fall of 2009, Hilafu came to the United States to attend graduate school at the University of Georgia. During his time at UGA, he worked as a volunteer at the statistical consulting center, interned with Johnson & Johnson and worked on a dissertation to develop dimension reduction and variable selection methods for high-dimensional datasets (also referred to as “wide data”).
Hilafu chose the Business Analytics and Statistics Department at Haslam because it offers opportunities that a traditional statistics department does not. “Haslam’s BAS department has embraced the contemporary challenges and opportunities of big data,” Hilafu says. “The departmant has aligned its resources to educate students to solve practical business problems with the aid of analytics, and the faculty has the right mix of expertise in a multitude of relevant areas to analytics: statistical methodology, statistical learning, supply chain and optimization, and computational methods.”
Now in his second year at Haslam, Hilafu is developing dimension reduction methods, focusing on time series data with special application on predicting out-of-sample stoke price index. In coordination with Drew Schmidt, a current doctoral student, he has submitted a proposal to the National Science Foundation regarding a novel dimension reduction method for large data sets.
Hilafu wants to be remembered personally and professionally for being there to lend a helping hand for people in need, and for a significant contribution to the literature of high-dimensional data analysis.