Syed S. Ali

Visiting Assistant Professor & Assistant Scientist
Mathematical Sciences Department
University of Wisconsin-Milwaukee

Phone: (414) 229-4364
Fax:(414) 229-4907


Dr. Syed S. Ali is a visiting assistant professor and assistant scientist in the department of Mathematical Sciences at Science at UW-Milwaukee. He has been at UWM since August of 1996, and pursues his interests in teaching (particularly artificial intelligence) and research in knowledge representation, natural language processing, and computational linguistics. 

Short Information:

  • Research Interests
  • Research Activities
  • Archived Links Columns
  • Teaching Activities
  • C.v.
  • Other Activities

  • Syed Ali's Research Activities

  • Research Interests and Projects
  • Publications
  • Natural Language and Knowledge Representation Research Group
  • ANALOG: A NAtural LOGic
  • AAAI '98 Workshop: Representations for Multi-modal Human-Computer Interaction
  • Special Issue of the Journal of Natural Language Engineering: KRR for NLP
  • ETCE '96 Session: Natural Language in Human-Computer Interfaces
  • AAAI Fall '94 Symposium: KR for NLP in Implemented Systems
  • Research Interests and Projects

    I am interested in computational models for human-computer communication. I investigate these models by proposing theories and implementing them in systems. This process has two advantages; first, it permits validation that the methods are computationally tractable; and
    second, it permits evaluation of the models in real-world applications with users.

    My current research is concerned with intelligent dialog systems; such systems should participate in an interactive dialog with a user in much the same way that people converse with each other.  The work is inherently interdisciplinary, and my recent grant proposals have involved colleagues from Linguistics, Educational Psychology,  and Nursing (the latter a domain expert).

    The specific projects that I am currently involved with include:

    1. The ARGUER project aims to develop a computational model of argumentation on the basis of information that characterizes the structure of arguments. The methods being developed can be used both to detect arguments and to generate candidate arguments for rebuttal. No assumption of a priori knowledge about attack and support  relations between propositions, advanced by the agents participating in a dialog, need be made.  Most importantly, the relations are dynamically established while the dialog is taking place. This allows incremental processing since agents need only consider the current utterance advanced by the dialog participant, not necessarily the entire argument, to be able to continue processing.
    2. The B2 project aims to effectively tutor medical students while communicating with them in a natural and flexible way. The primary means of instruction is to allow students to set up hypothetical situations to learn how different factors affect outcomes. B2 supports mixed-initiative interaction in English and maintains an incremental dialog model which allows the interpretation of fragmentary utterances as providing well-tailored responses.
    3. The ColTrain project aims to research methods for enhancing the ability of people and computer systems to collaborate in learning and understanding complex information. Collaborative systems actively help people perform a task, communicating in a natural and flexible manner. For a computer system to collaborate with a user, they must learn from each other and adapt their behavior. They must also be able to communicate, so that they can define goals and negotiate over how to proceed and how to evaluate their progress. The testbed area for collaborative learning that we are using is the curriculum of the Blood Pressure Measurement Education Program, developed by the American Heart Association (AHA) chapter in Milwaukee.
    4. The PEAS (Patient Education and Activation System) project aims to prepare people to take a more active role in health care decisions. The project is investigating strategies for helping people identify their health care concerns, learn what actions they can take on their own, and, if necessary, be able to verbalize their concerns to health care professionals. These strategies combine a multi-modal computer  interface (including typed text and mouse-inputs) with intelligent tutoring and intelligent discourse processing. As PEAS interacts with a patient, it will vary the content and pace of the interaction and  suggest relevant learning activities.
    5. The YAG (Yet Another Generator) project is specifying and building a fast (and hence suitable for interactive dialog) natural language generation (NLG system that is capable of tailoring text to user models for  any application.  YAG employs a template-based approach.  Templates can be  ailored to the user model or application domain. It permits this tailoring by allowing templates to be defined at many different levels, including  yntactic, linguistically-oriented,  templates and semantic, conceptually-oriented, templates.


    A incomplete chronological listing of publications is below. Some publications are available in compressed postscript, Adobe PDF, or HTML.

    A more complete listing can be found in my c.v.

    1. "Mixed Depth Representations for Dialog Processing", with Susan McRoy and Susan Haller, Proceedings of the 20th annual meeting of the Cognitive Science Society, Madison, WI, August 1-4, 1998. Postscript, Adobe PDF
    2. "Interactive Computerized Health Care Education", with Susan W. McRoy and Alfredo Liu-Perez, to appear (July 1998) in the Journal of the American Medical Informatics AssociationHTML, Compressed Postscript, Adobe PDF
    3. "Uniform Knowledge Representation for Language Processing in the B2 System", with Susan McRoy and Susan Haller. Journal of Natural Language Engineering, 3(3), 1997. PostScript, Adobe PDF
    4. "Knowledge Representation for Natural Language Processing in Implemented Systems", with Lucja Iwanska. Journal of Natural Language Engineering, 3(2), 1997
    5. "Towards a Model for Dialogic Discourse", with Susan Haller and Susan McRoy, AAAI Spring Symposium on Computational Models for Mixed Initiative Interaction, Standford, CA, March 1997. PostScript,Adobe PDF
    6. "Knowledge Representation and Inference for Natural Language Processing", with Lucja Iwanska and Stuart C. Shapiro, International Journal of Expert Systems, 9(1), 1996.
    7. "Knowledge Representation for Natural Language Processing in Implemented Systems", AI Magazine, v. 16 (Spring '95) p. 8-9, 1995.
    8. "ANALOG: A Knowledge Representation System for Natural Language Processing", Intelligent Systems, Yfantis, E. A. (ed.), 327-332, Kluwer Academic Publishers, Dordrecht, The Netherlands, 1995. Postscript, Adobe PDF
    9. "Recognizing Text Plans", Susan M. Haller and Syed S. Ali, Proceedings of the Fourth Golden West International Conference on Intelligent Systems, 76--80, ISCA, Raleigh, NC, 1995. Postscript, Adobe PDF
    10. "ANALOG: A Logical Language for Natural Language Processing", American Association for Artificial Intelligence Fall 1994 Symposium Working Notes, Knowledge Representation for Natural Language Processing, 1--11, November 4--6, 1994, New Orleans. Postscript, Adobe PDF
    11. "A Logical Language for Natural Language Processing, Proceedings of the 10th Biennial Canadian Artificial Intelligence Conference, Banff, Alberta, Canada, May 16-20, 1994. Postscript, Adobe PDF
    12. "A `Natural Logic' for Natural Language Processing and Knowledge Representation", Ph. D. Thesis, TR 94-01, Department of Computer Science, State University of New York at Buffalo, January 1994.
    13. ANALOG: A Knowledge Representation and Reasoning System for Natural Language Reasoning, Proceedings of the Third International SNePS Workshop, July 28-29, 1994, Buffalo, NY.  Postscript, Adobe PDF
    14. "Towards a Unified AI Formalism", with S. M. Haller and D. Kumar, Proceedings of the 27th Hawaii International Conference on System Sciences, 92--101, IEEE Press, Los Alamitos, CA, 1994.
    15. "Natural Language Processing Using a Propositional Semantic Network with Structured Variables", with S. C. Shapiro, Minds and Machines, 3(4), 1993.
    16. "A Propositional Semantic Network with Structured Variables for Natural Language Processing", Proceedings of the Sixth Australian Joint Conference on Artificial Intelligence, Melbourne, Australia, World Scientific, NJ, 1993.
    17. "Node Subsumption in a Propositional Semantic Network with Structured Variables", Proceedings of the Sixth Australian Joint Conference on Artificial Intelligence, Melbourne, Australia, World Scientific, NJ, 1993.
    18. "A Structured Representation for Noun Phrases and Anaphora", Proceedings of the Fifteenth Annual Meeting of the Cognitive Science Society, Lawrence Erlbaum, Hillsdale, NJ, 1993.
    19. "Using Focus for Generating Felicitous Locative Expressions" Susan. M. Haller and Syed S. Ali, Proceedings of the Third International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, 472--477, Charleston, S. Carolina, July 1990.

    Syed Ali's Teaching Activities

  • Teaching Artificial Intelligence
  • Some of my former students.

  • Syed Ali's Other Activities

    Due to time constraints, I currently have a very limited range of other activities. These activities include aerobics, running, weights, and top-rope climbing. 
    Sy Ali (