Susan
Imberman's Home Page
For a list of publications CLICK HERE
COURSES TAUGHT
Introduction
to Computer Science: CSC 126
Artificial
Intelligence: CSC 480
Information Structures
CSC 326
Graduate Operating Systems
CSC718
Data Mining, CUNY
Graduate Center CSc 80000
Click
Here for CURRICULUM VITAE
For Robot Pages CLICK HERE
SHORT BIO
Susan Imberman shares her
life with family, friends, tweethearts, and a
frog!! Her "free time"
passions include the Jersey Shore, Broadway musicals, Gilbert and Sullivan
operettas, science fiction novels, "Buffy the Vampire Slayer", and anything Star Trek. (not necessarily in that order!!). In her "other" time, Susan is an
Assistant Professor of in the Computer
Science Department at the The
College of Staten Island. Susan received her Master's Degree from CSI in
1989. She has taught at CSI as a
lecturer, adjunct, and now professor
since 1986.
Her most significant
academic achievement has been the introduction and integration of LEGO
handyboard based robots into the Computer Science curriculum. Each beginning
computer science student has one lab assignment using robots. The Artificial
Intelligence students use neural networks to teach robots path following
behavior. She is also the recipient of
the Computer Measurement Group's best journal article award 2002.
Data mining is a field that deals
with the automated analysis of large amounts of data. Susan's research in this
area has taken several directions. Mainly, her work focuses on the application
of data mining algorithms to analyzing medical data sets. Most medical data
sets are not as large, with regards to the number of records, as data usually
analyzed through data mining. Notwithstanding, they are highly dimensional,
containing large numbers of variables. Thus, data mining techniques are well
suited for finding hidden patterns in this data. She is also looking at the
patterns formed by frequent itemsets over time in incremental association rule
algorithms. Lastly, she is researching
clustering algorithms with a research group from the Pattern Recognition Lab at the
Graduate Center, City University of New York