  Computer science has grown rapidly since its inception in the 1950s and the
pioneers in the field are celebrated annually by the A.M. Turing Award. In this
paper, we attempt to shed light on the path to influential computer scientists
by examining the characteristics of the 72 Turing Award laureates. To achieve
this goal, we build a comprehensive dataset of the Turing Award laureates and
analyze their characteristics, including their personal information, family
background, academic background, and industry experience. The FP-Growth
algorithm is used for frequent feature mining. Logistic regression plot, pie
chart, word cloud and map are generated accordingly for each of the interesting
features to uncover insights regarding personal factors that drive influential
work in the field of computer science. In particular, we show that the Turing
Award laureates are most commonly white, male, married, United States citizen,
and received a PhD degree. Our results also show that the age at which the
laureate won the award increases over the years; most of the Turing Award
laureates did not major in computer science; birth order is strongly related to
the winners' success; and the number of citations is not as important as one
would expect.
