CS 784: Programming Languages

This course introduces concepts related to the specification and design of high-level programming languages. It discusses different programming paradigms, algebraic specification and implementation of data types, and develops interpreters for specifying operationally the various programming language features/constructs. It also introduces attribute grammar formalism and axiomatic semantics briefly. The programming assignments will be coded in Scheme

CS 884: Advanced Topics in Programming Languages

The primary focus of this course is the design and specification of the Object-Oriented language Java

CS 780: Compiler Design and Construction I

This course deals with the theory and practice of compiler design. Topics emphasized are scanning and parsing. If time permits, semantic analysis will also be covered

CS 891-01: Information Retrieval, Extraction, and Management

This course expects an advanced Ph.D. student to (i) review background material in the area of Information Retrieval, Extraction, and Management, and (ii) develop/deliver a presentation on a mutually acceptable topic

CS 884: Advanced Topics in Programming Languages

The primary focus of this course is the design and specification of the Object-Oriented language Java

CEG 860-01: Object-Oriented Programming

This course motivates the need for object-oriented programming, and studies, in detail, object-oriented programming techniques, languages, and technology. The lectures will focus on the foundations of OOP, while the student presentations will focus on the applications and extensions of Object Technology

Value Oriented Big Data Processing with Applications

We discuss the nature of Big Data and address the role of semantics in analyzing and processing Big Data that arises in the context of Physical-Cyber-Social Systems. To handle Volume, we advocate semantic perception that can convert low-level observational data to higher-level abstractions more suitable for decision- making. To handle Variety, we resort to semantic models and annotations of data so that intelligent processing can be done independent of heterogeneity of data formats and media. To handle Velocity, we seek to use continuous semantics capability to dynamically create event or situation specific models and recognize relevant new concepts, entities and facts. To handle Veracity, we explore trust models and approaches to glean trustworthiness. Our ultimate goal is to deal with the challenges due to the four Vs of Big Data to derive Value to enable decision-making and action. In what follows, we discuss the primary characteristics of the Big Data problem as it pertains to the Five Vs

An XML-Based Approach to Handling Tables in Documents

We explore application of XML technology for handling tables in legacy semi-structured documents. Specifically, we analyze annotating heterogeneous documents containing tables to obtain a formalized XML Master document that improves traceability (hence easing verification and update) and enables manipulation using XSLT stylesheets. This approach is useful when table instances far outnumber distinct table types because the effort required to annotate a table instance is relatively less compared to formalizing table processing that respects table’s semantics. This work is also relevant for authoring new documents with tables that should be accessible to both humans and machines