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My research interests include bioinformatics, computer science education, artificial intelligence (natural language processing), android app development, java development and competitive programming. My personal interests include Philadelphia Pro sports teams, Union College Hockey, Magic the Gathering, and QuizUp.

Degree Program University
Ph.D. Computer Science RPI
B.S. Computer Science Moravian College

My Siena Experience

My Teaching Philosophy

My feeling, with regards to programming, is that students learn through practice and repetition. It may seem that lectures of mine may look like homework assignments (but just in class), but they are just a launching point for the learning process. Work outside of class makes the skills come faster, and makes my job (and ultimately, the students' job) much easier.

What I Love About Siena

The great relationships I have with my colleagues and students.

My Favorite Courses to Teach

My two favorite courses to teach are CSIS-225: Object-Oriented Design and Programming, and CSIS-019: Computer Science in Film.

My Professional Experience

Year Title Organization
2004 - 2004 Adjunct, Computer Science ITT Technical Institute
2004 - Now Assistant Prof., Computer Science Siena College
2003 - 2004 Consultant, Computer Science Self-employed
1996 - 2003 Teaching Assistant/Instructor, Computer Science RPI

Articles & Book Reviews

  • Come code with codester: an educational APP that teaches computer science to K-6 students
    Journal of Computing Sciences in Colleges, vol. 29
    2014
  • 10 Weeks 'Till TREC
    NYCWiC 2013
    April, 2013
  • Siena's Twitter Information Retrieval System: The 2012 Microblog Track
    The Twenty-First Annual Text Retrieval Conference Proceedings
    November, 2012
  • Lights...Camera...Computer Science: Using Films to Introduce Computer Science to Non-Majors
    Journal of Computing Sciences in Colleges
    2008
  • Taking Students Out for a Ride: Using a Boardgame to Teach Graph Theory
    SIGCSE, vol. 39
    March, 2007
  • A Ruby in the Rough: Using VHLLs in Bioinformatics
    Journal of Computing Sciences in Colleges
    2006
  • Discovering Optimization Algorithms Through Automated Learning
    Graphs and Discovery: DIMACS Series in Discrete Mathematics and Theoretical Computer Science, vol. 69
    2005
  • A Learning Algorithm for the Longest Common Subsequence Problem
    Journal of Experimental Algorithmics
    2003

Awards & Distinctions

  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 2011
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 2011
  • Upsilon Pi Epsilon
    Category: Other
    Upsilon Pi Epsilon, 2011
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 2010
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 2010
  • Upsilon Pi Epsilon
    Category: Other
    Upsilon Pi Epsilon, 2010
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 2009
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 2009
  • Upsilon Pi Epsilon
    Category: Other
    Upsilon Pi Epsilon, 2009
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 2008
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 2008
  • Upsilon Pi Epsilon
    Category: Other
    Upsilon Pi Epsilon, 2008
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 2007
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 2007
  • Upsilon Pi Epsilon
    Category: Other
    Upsilon Pi Epsilon, 2007
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 2006
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 2006
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 2005
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 2005
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 2004
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 2004
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 2003
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 2003
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 2002
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 2002
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 2001
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 2001
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 2000
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 2000
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 1999
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 1999
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 1998
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 1998
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 1997
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 1997
  • NSF Minority Fellow
    Category: Other
    NSF Minority Fellow, 1996
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 1996
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 1996
  • NSF Minority Fellow
    Category: Other
    NSF Minority Fellow, 1995
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 1995
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 1995
  • NSF Minority Fellow
    Category: Other
    NSF Minority Fellow, 1994
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 1994
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 1994
  • NSF Minority Fellow
    Category: Other
    NSF Minority Fellow, 1993
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 1993
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 1993
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 1992
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 1992
  • Omicron Delta Kappa
    Category: Other
    Omicron Delta Kappa, 1991
  • Pi Mu Epsilon
    Category: Other
    Pi Mu Epsilon, 1991

Books & Book Chapters

  • Graphs and Discovery: DIMACS Series in Discrete Mathematics and Theoretical Computer Science

    2005

Presentations

  • Lights...Camera...Computer Science: Using Films to Introduce Computer Science to Non-Majors
    2008
    CCSCNE (Consortium For Computing Sciences in Colleges NorthEast region), Staten Island, New York
  • Fibonacci: The Game
    2007
    HRUMC XIV (Hudson River Undergraduate Mathematics Conference), Loudonville, New York
  • Problems and Programmers: Using a Card Game to Teach Software Engineering
    2007
    HRUMC XIV (Hudson River Undergraduate Mathematics Conference), Loudonville, New York
  • Taking Students Out for a Ride
    2007
    SIG-CSE (Special Interest Group: Computer Science Education), Covington, Kentucky
  • A Ruby in the Rough: Using VHLLs in Bioinformatics
    2006
    11th Consortium For Computing Sciences in Colleges, Worcester, Massachusetts
  • Protein Folding using the HP Model
    2006
    HRUMC XIII (Hudson River Undergraduate Mathematics Conference), Westfield, Massachusetts
  • Streamlining Code for Performance
    2006
    HRUMC XIII (Hudson River Undergraduate Mathematics Conference), Westfield, Massachusetts
  • The Effect of Computer Specifications on Performance
    2006
    HRUMC XIII (Hudson River Undergraduate Mathematics Conference), Westfield, Massachusetts
  • The Mathematics of 'A Ticket to Ride'
    2006
    HRUMC XIII (Hudson River Undergraduate Mathematics Conference), Westfield, Massachusetts
  • Predicting the Secondary Structure of Proteins
    2005
    HRUMC XII (Hudson River Undergraduate Mathematics Conference), Williamstown, Massachusetts
  • Scoring Matrices for the Protein Secondary Structure Prediction Problem
    2005
    HRUMC XII (Hudson River Undergraduate Mathematics Conference), Williamstown, Massachusetts
  • Statistical Learning for the Protein Secondary Structure Prediction Problem
    2005
    HRUMC XII (Hudson River Undergraduate Mathematics Conference), Williamstown, Massachusetts
  • VEDA: A New DNA Fragment Assembler
    2003
    BIOKDD-CBGI (Biological Knowledge Discovery and Data Mining  Computational Biology and Genomic Informatics), Cary, North Carolina
  • Improving Shotgun Sequencing by Learning
    2002
    2nd RECOMB (Research in Computational Molecular Biology) Satellite Meeting on DNA Sequencing and Characterization, Stanford, California
  • Improving Shotgun Sequencing by Learning
    2002
    RECOMB (Research in Computational Molecular Biology), Washington, District of Columbia
  • A Learning Algorithm for the Shortest Superstring Problem
    2001
    CBGI 2001 (Computational Biology and Genomic Informatics), Raleigh, North Carolina
  • A Learning Algorithm for the Shortest Superstring Problem
    2001
    RECOMB (Research in Computational Molecular Biology), Los Angeles, California
  • Discovering Optimization Algorithms Through Automated Learning
    2001
    DIMACS Working Group: Computer-Generated Conjectures from Theoretic and Chemical Databases, New Brunswick, New Jersey