SUSAN P. IMBERMAN PH.D.  - CURRICULUM VITAE

                                                                        

 

Address:              College of Staten Island, 2800 Victory Blvd, Staten Island NY 100314

                             Voice mail: 1-718-982-3273

                             Email: imberman@mail.csi.cuny.edu

                             Web Site: www.cs.csi.cuny.edu/~imberman/

                                                                               

Education:

 

Institution                                         Degree & Field                         Date Conferred

CUNY Graduate Center                  Ph.D., Computer Science           6/99

CUNY College of Staten Island     MS Computer Science               6/89

CUNY Queens College                   BA Biology                                6/76

 

DISSERTATION

 

Comparative Statistical Analyses of Automated Booleanization Methods, Graduate Center City University of New York, June 1999.

Advisors:  Michael Kress, Bernard Domanski

 

RESEARCH AREAS

 

Medical Data Mining, Frequent Itemset Mining, Educational Robotics

 

REFERRED BOOK CHAPTERS

 

Frequent Itemset Mining and Association Rules, Encyclopedia of Knowledge Management, October 2005, Idea Group Reference, pgs 195 - 201

 

REFEREED JOURNAL PUBLICATIONS 

 

Leveraging online/distance learning methodologies in face to face instruction. : faculty poster Susan P. Imberman. 2012.  J. Comput. Sci. Coll. 27, 6 (June 2012), 73-75.

 

The computer science club: Building a student community with projects and activities that extend beyond the classroom: faculty poster Susan P. Imberman. 2012J. Comput. Sci. Coll. 26, 6 (June 2011), 178-179.

 

Creating the technologically savvy K-12 teacher: faculty poster Susan P. Imberman and Roberta Klibaner. 2010. J. Comput. Small Coll. 25, 6 (June 2010), 237-238

 

A Robotics Lab for CS1, Susan P. Imberman, Roberta Klibaner, Journal of Computing Sciences in Colleges,  Volume 21 Issue 2  December 2005

 

Three Fun Assignments for an Artificial Intelligence Class, Susan P. Imberman, Journal of Computing Sciences in Colleges,  Volume 21 Issue 2  December 2005

 

A Perspective Study of Accommodative Esotropia, Irene H. Ludwig, MD, Susan P. Imberman, PhD, Hilary Thompson, PhD, Marshall M. Parks, MD, December 2005,  Journal of the American Association for Pediatric Ophthalmology and Strabismus

 

An Intelligent Agent Approach for Teaching  Neural Networks Using LEGOŇ Handy Board Robots, Susan P. Imberman, Ph.D.  ACM Journal of Educational Resources in Computing, Volume 4 issue 2, September 2004 (published September 2005)

 

Long Term Study of Accommodative Esotropia,  Irene H. Ludwig, MD, Susan P. Imberman, PhD, Hilary Thompson, PhD, Marshall M. Parks, MD, Transactions of the American Ophthalmological Society, Vol. 101, 2003

 

Using Dependency/Association Rules to Find Indications for Computerized Tomography In A Head Trauma Dataset, Susan P. Imberman, Bernard Domanski, Hilary W. Thompson.   International Journal of Artificial Intelligence in Medicine, special issue on medical data mining.  September 2002, pgs 55-68

 

The KDD Process And Data Mining For Computer Performance Professionals, Susan P. Imberman.  Journal of Computer Resource Management, Summer 2002 Issue 107,   pgs 68-77

 

REFEREED CONFERENCE PROCEEDINGS

 

Using Frequent Pattern Mining To Identify Behaviors In A Naked Mole Rat Colony,  Susan P. Imberman, Michael E. Kress,  Daniel P. McCloskey, Florida Artificial Intelligence Research Seminar, May 2012.

 

       From Market Baskets To Mole Rats: Using Data Mining Techniques To Analyze RFID Data Describing Laboratory Animal Behavior. Daniel P. McCloskey, Michael E. Kress, Susan P. Imberman, Igor Kushnir, and Susan Briffa-Mirabella.  Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '11). ACM, San Diego, CA 301-306.

 

       Using Decision Trees To Find Patterns in a Clinical Ophthalmology Dataset, Susan P. Imberman, Sarah Zelikovitz, Florida Artificial Intelligence Research Seminar, May 2011.

 

Making Nifty Assignments Niftier and Not So Nifty Assignments Nifty with Online Technologies, Susan P. Imberman, AI Education Workshop at Association for Advancement of Artificial Intelligence 2008, Chicago July 2008

 

Robotics As a Component of a General Education Course, Susan P. Imberman, Sarah Zelikovitz, Spring 2008 Symposium of the American Association for Artificial Intelligence.

 

Discovery of Association rules in Temporal databases, Abdullah Uz Tansel, Susan P. Imberman, to appear: IEEE Proceedings 4th International Conference on Information Technology: New Generations, April 2007

 

Student Feedback on Robotics in CS1, Susan P. Imberman, Roberta Klibaner, Sara Zelikovitz, to appear Spring 2007 Symposium of the American Association for Artificial Intelligence.

 

Extra-Curricular Robotics: Entry-level Soccer for Undergraduates, Susan P. Imberman, Aleksandr Barkan, Elizabeth Sklar, to appear Spring 2007 Symposium of the American Association for Artificial Intelligence.

 

An Efficient Method For Finding Emerging Large Itemsets, Susan P. Imberman, Abdullah Uz Tansel, Eric Pacuit, The Third Workshop on Mining Temporal and Sequential Data, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 2004

 

A Laboratory Exercise Using LEGO Handy Board Robots to Demonstrate Neural Networks in an Artificial Intelligence Class, Susan P. Imberman, Spring 2004 Symposium of the American Association for Artificial Intelligence. On Accessible Hands-on Artificial Intelligence and Robotics Education

 

Teaching Neural Networks Using Lego-Handyboard Robots in an Artificial Intelligence Course,  Susan P. Imberman.  ACM SIGCSE Technical Symposium on Computer Education, February 2003

 

Effective Use Of The KDD Process And Data Mining For Computer Performance Professionals, Susan P. Imberman, Proceedings of CMG 2001, December 2001

 

Boolean Analyzer - An Algorithm That Uses A Probabilistic Interestingness Measure to find Dependency/Association Rules In A Head Trauma Dataset, Susan P. Imberman, Bernard Domanski, Hilary W. Thompson, Intelligent Data Analysis in Medicine and Pharmacology, A Workshop at the Tenth World Congress on Health and Medical Informatics, Medinfo 2001, September 2001

 

Finding Association Rules From Quantitative Data Using Data Booleanization, Susan P. Imberman, Bernard Domanski, Proceedings of the Seventh Americas Conference on Information Systems, August 2001

 

Using Booleanized Data to Discover Better Relationships Between Metrics, Susan P. Imberman, Bernard Domanski, Robert Orchard, Proceedings of CMG99, December 1999

 

 

RESEARCH GRANTS

 

Software grant from Microsoft Corporation ($108,000 with B. Domanski, M. Kress,   and R. Klibaner) to help provide courseware using Microsoft software products (1996). This grant was renewed for 1997 (additional $108,000), and again in 1999 (additional $40,000).

 

PSC-CUNY grant, ($5,300) Analysis of Clinical Pediatric Ophthalmology Data Using Intelligent Data Analysis, funded July 1, 2000 - June 30 2001.

 

Microsoft Instructional Lab Grant ($57,125/year) with B. Domanski, R. Klibaner, E. Chi, N. Gueorguieva, and M. Kress) (6/2000 - 6/2002) provides web based course materials for use by other Universities and Colleges using Microsoft products.  This is part of the Microsoft Academic Cooperative.

 

PSC-CUNY grant, ($4,142) Analysis of Clinical Pediatric Ophthalmology Data Using Intelligent Data Analysis, funded July 1, 2001 - June 30 2002.

 

GRTI - 6  ($48,658.89) Real Time Interactive Smart Wireless Classrooms with Mike Kress, Roberta Klibaner, Bernie Domanski, Emile Chi funded September 2001

 

PSC-CUNY grant ($3,453) Cluster Analysis of Clinical Ophthalmologic Data, funded July 1, 2003 - June 30 2004.

 

PSC-CUNY grant ($2805) Using Data Mining For Finding Patterns In a Clinical Ophthalmology Dataset, funded July 1, 2005 - June 30 2006.

 

PSC-CUNY grant ($3,176) Using Data Mining For Finding Patterns In a Clinical Ophthalmology Dataset renewal funded July 1, 2006- June 30 2007

 

PSC-CUNY grant ($2,805) Using Data Mining For Finding Patterns In a Clinical Ophthalmology Dataset, funded July 1, 2005 - June 30 2006.

 

HONORS

 

        Awarded CSI's Dolphin Award for excellence in teaching

 

 

AWARDS

 

Recipient Journal Best Paper 2002, Computer Measurement Group

 

OTHER PROFESSIONAL ACTIVITIES

 

LECTURES PRESENTED

 

9/14/03 Using LEGO® Handyboard Robots As a Pedagogical Tool in the Computer Science Curriculum, CUNY’s 2nd Annual IT Conference - Instructional/Information Technology in CUNY:  Issues, Innovations, Integration

 

9/14/03  The Smart Wireless Interactive Classroom (SWIC), Susan P. Imberman, with Michael Ziselman,  CUNY's 2nd Annual IT Conference - Instructional/Information Technology in CUNY:  Issues, Innovations, Integration

 

9/17/99 Invited talk at Philadelphia meeting of Computer Measurement Group - Topic: Using Booleanized Data to Find Relationships in Quantitative Data

 

5/4/00 Invited talk at Baruch College, CUNY - Topic: Boolean Analyzer, A Method for Finding Disjunctive Association Rules

 

9/25/02 Invited talk at The Graduate Center CUNY - Topic: Data Mining, KDD, and ELI

 

REFEREEING

 

9/2005 Reviewed paper for Knowledge Engineering Review

9/2004 Reviewed paper for Journal Information Sciences

6/2003 Reviewed paper for International Journal for Artificial Intelligence in Medicine.

8/2002 Reviewed papers for the International Conference on Data Engineering

5/2001 Reviewed papers for Americas Conference on Information Systems

3/30/00 Reviewed journal paper Data Mining of Software Development Databases for Software Quality Journal

      

CURRENT MEMBERSHIP IN PROFESSIONAL SOCIETIES

 

·         Association for Computing Machinery (since 1993)

·         Special Interest Group in Computer Science Education (SIG CSE)

·         Special Interest Group in Artificial Intelligence (SIG ART)

·         Special Interest Group in Data Mining (SIG KDD)

·         Special Interest Group in Computer Uses in Education (SIG CUE)

·         American Association for Artificial Intelligence (since 1996)