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Sridhar Panchapakesan Nerur

Name

[Nerur, Sridhar Panchapakesan]
  • Goolsby-Virginia and Paul Dorman Endowed Chair in Leadership
  • Professor

Biography

Sridhar Nerur is the Goolsby-Virginia and Paul Dorman Endowed Chair in Leadership and professor of Information Systems at the University of Texas at Arlington. Professor Nerur's academic training includes a Bachelor of Engineering degree in Electronics, a post-graduate diploma in management (PGDM) from the prestigious Indian Institute of Management (Bangalore, India), and a Ph.D. in Business Administration from the University of Texas at Arlington.

A 2014 article in the Journal of Systems and Software (by Chuang, Luor, and Lu) ranked Professor Nerur among the top 3 worldwide researchers in the field of Agile Software Development. Much of his research in this area draws on the conceptual foundations of small groups research as well as theoretical insights from distributed cognition, team mental models, systems thinking, and experiential learning. In addition, he has made significant contributions to the literature on citation analysis, particularly in terms of how it can be applied to unravel the intellectual structure of disciplines. In recent times, Professor Nerur's research interests have expanded to include Deep Learning/AI, Machine Learning, Social Network Analysis, and Natural Language Processing (NLP). Specifically, he has been using NLP to gain personality insights, assess the technological similarity of firms, trace changes in "vernacular perspectives on health", and affirm CEO narcissism, to name but a few projects. Professor Nerur's research has been published in the MIS Quarterly, Strategic Management Journal, Communications of the ACM, Communications of the AIS, The DATA BASE for Advances in Information Systems, European Journal of Information Systems, Information Systems Management, Information & Management, and the Journal of International Business Studies. He has also served on the editorial boards of the European Journal of Information Systems (EJIS) and the Journal of Association for Information Systems (JAIS). He continues to serve as a guest SE for JAIS.

Professor Nerur is currently the chair of the graduate studies committee on Business Analytics, which was set up to oversee the Masters in Business Analytics Program. In addition to teaching state-of-the-art courses in data analytics, he has actively engaged with the community to advance the analytics program in the College of Business.

Professional Preparation

    • 1994 Ph.D. in Business AdministrationUniversity of Texas at Arlington
    • 1988 Post Graduate Diploma in Management in ManagementIndian Institute of Management
    • 1983 BEng in ElectronicsBangalore University

Appointments

    • Sept 1994 to Aug 1995 Programmer
      Compucom Systems
    • Oct 1988 to Aug 1990 Senior Customer Support Executive
      Wipro Information Technology Ltd., India
    • Dec 1984 to May 1986 Member Design Development Team
      Semiconductor Complex Ltd., India

Memberships

  • Membership
    • Aug 2013 to Present University of Texas at Arlington  Business Administration  Association for Information Systems

Awards and Honors

    • May  2012 Endowed faculty fellowship, College of Business sponsored by Dean, College of Business
      Achievements:

      For my reserach productivity.

    • May  2010 Distinguished Research Publication Award sponsored by College of BusinessOffice of the Provost and Vice President for Academic AffairsOffice of the PresidentUniversity of Texas at Arlington
      Achievements:

      Published a paper in the MIS Quarterly, which is the premier journal in the field of Information Systems.

Research and Expertise

  • Research Interests

    Dr. Nerur's research and teaching interests are in the areas of agile software development, issues related to dynamic IT capabilities, social networking, text analytics, Big Data analytics, network analysis,  cognitive aspects of programming, knowledge management, and software maintenance.

Publications

      Journal Article In-progress
      • Dissanayake, I., Zhang, J., Yasar, M. and Nerur, S. “"Strategic Effort Allocation in Online Innovation Tournaments,” conditionally accepted at Information & Management.

        {Journal Article }

      Poster Abstract 2016
      • Hamman, Baron, Kay-Yut Chen, Sridhar Nerur, Edmund Prater, Herbert Morley, LaraLee Hoggj, Syma Prince, James Edgerton. “Patient Mortality Effects on Surgeon’s Subsequent Performance.” Abstract published in Circulation, an American Heart Association Journal,  2016; 134:A17020 

        {Poster Abstract }

      Journal Article 2016
      • Bonner, N., Kulangara, N., Nerur, S., and Teng, J. “An Empirical Investigation of the Perceived Benefits of Agile Methodologies Using an Innovation-Theoretical model,” Journal of Database Management, 27(3), 2016, pp. 38-63

        {Journal Article }
      2016
      • Nerur, S., Rasheed, A., and Pandey, A. “Citation footprints on the sands of time: An analysis of idea migrations in strategic management,” Strategic Management Journal, Volume 37, Issue 6
        June 2016, Pages 1065–1084. 

        {Journal Article }

      Journal Article 2015
      • Balijepally, V., Nerur, S. and Mahapatra, R. "Task Mental Model and Software Developer’s            Performance: An Experimental Investigation," Communications of the AIS, Vol. 36, 2015

        {Journal Article }

      Journal Article 2014
      • Mangalaraj, G., Nerur, S., Mahapatra, R. and Price, K. “Distributed Cognition in Software Design: An Experimental Investigation of the Role of Design Patterns and Collaboration,” MIS Quarterly, Match 2014.

        {Journal Article }

      Journal Article 2012
      • Dingsøyr, Torgeir; Nerur, Sridhar; Balijepally, VenuGopal; and Moe, Nils Brede, “A decade of agile methodologies: Towards explaining agile software development.,” Journal of Systems & Software. Jun 2012, Vol. 85 Issue 6, p1213-1221 (editorial – Guest Editors’ – article)

        {Journal Article }

      Journal Article 2011
      • Sullivan, S. P. Nerur, Balijepally, V. G. Source or storer? IB's performance in a knowledge network. Journal of International Business Studies 2011, 42, 446-457.
        {Journal Article }

      Book Chapter 2010
      • Nerur, S., Cannon, A., Balijepally, V. and Bond, P. “Towards an Understanding of the Conceptual Underpinnings of Agile Development Methodologies,” Dingosoyr, T., Dyba, T. and Moe, N.B. (eds.,) in Agile Software Development: Current Research and Future Directions, Springer-Verlag Berlin Heidelberg, 2010, 15-29.
        {Book Chapter }

      Journal Article 2010
      • Raghupathi, W. and S. Nerur. "The Intellectual Structure of Health and Medical Informatics." International Journal of Healthcare Information Systems and Informatics 5, no 4 (2010): 20-34.
        {Journal Article }

      Book Chapter 2009
      • Sachdev, V., Nerur, S. and Teng, J. (2009). “Social Computing Interactivity: Interactivity redefined for the Social Web,” Hatzipanagos, S. and Warburton, S. (eds.) in Handbook of Research on Social Software and Developing Community Ontologies, IGI Global.
        {Book Chapter }

      Journal Article 2009
      • Mangalaraj, G., R. Mahapatra, and S. Nerur. "Acceptance of Software Process Innovations –The Case of Extreme Programming." European Journal of Information Systems 18, no 4 (2009): 344-354.
        {Journal Article }
      2009
      • Balijepally, V., R. Mahapatra, S. Nerur, and K. Price. "Are Two Heads Better Than One for Software Development? The Productivity Paradox of Pair Programming." MIS Quarterly 33, no 1 (2009): 91-118.
        {Journal Article }
      2009
      • Ramanujan, S. and S. Nerur. "An exploratory analysis of the state of software maintenance research: an author co-citation analysis." Journal of Systems and Information Technology 11, no 2 (2009): 117-130.
        {Journal Article }

      Book Chapter 2008
      • Balijepally, V., Nerur, S., and Mahapatra, R. “IT Value of Software Development: A Multi-theoretic Perspective,” Siau, K. & Erickson, J. (Eds.) in Advanced Principles for Improving Database Design, Systems Modeling, and Software Development, IGI Global.
        {Book Chapter }

      Journal Article 2008
      • Raghupathi, W. and S. Nerur. "Research Themes and Trends in Health Information Systems." Methods of Information in Medicine 47, no 5 (2008): 435-442.
        {Journal Article }
      2008
      • Nerur, S., A. Rasheed, and V. Natarajan. "The Intellectual Structure of the Strategic Management Field: An Author Co-citation Analysis." Strategic Management Journal 29 (2008): 319-336.
        {Journal Article }
      2008
      • Song, S., S. Nerur, and J. Teng. "Understanding the Influence of Network Positions and Knowledge Processing Styles on the Success of Knowledge Management." Communications of the ACM 51, no 10 (2008): 123-126.
        {Journal Article }

      Journal Article 2007
      • Song, S., S. Nerur, and J. Teng. "An Exploratory Study on the Roles of Network Structure and Knowledge Processing Orientation in Work Unit Knowledge Management." The DATA BASE for Advances in Information Systems 38, no 2 (2007): 8-26.
        {Journal Article }
      2007
      • Nerur, S. and V. Balijepally. "Theoretical Reflections on Agile Development Methodologies." Communications of the ACM 50, no 3 (2007): 79-83.
        {Journal Article }

      Journal Article 2006
      • Balijepally, V., R. Mahapatra, and S. Nerur. "Assessing Personality Profiles of Software Developers in Agile Development Teams." Communications of the AIS 18 (2006).
        {Journal Article }
      2006
      • Vinekar, V., C. Slinkman, and S. Nerur. "Can Agile and Traditional Systems Development Approaches Co-exist? An Ambidextrous View." Information Systems Management Journal 23, no 3 (2006): 31-42.
        {Journal Article }

      Journal Article 2005
      • Mahapatra, R., S. Nerur, and C. Slinkman. "Teaching Systems Analysis and Design – A Case for the Object Oriented Approach." Communications of the AIS 16 (2005).
        {Journal Article }
      2005
      • Nerur, S., R. Sikora, G. Mangalaraj, and V. Balijepally. "Assessing the Relative Influence of Journals in a Citation Network." Communications of the ACM 48, no 11 (2005).
        {Journal Article }
      2005
      • Nerur, S., R. Mahapatra, and G Mangalaraj. "Challenges of Migrating to Agile Methodologies." Communications of the ACM 48, no 5 (2005): 72-78.
        {Journal Article }

Presentations

    • August  2013

      Dissanayake, I., Dantu, R., and Nerur, S. Knowledge Management in Software Development. To be presented at the Americas Conference on Information Systems (AMCIS), Chicago, August 2013.

Students Supervised

Courses

      • INSY 5378-001 Data Science: A Programming Approach

        The world is awash in data and companies are now trying to discern patterns and predict behaviors of both consumers and competitors to gain and sustain a competitive advantage. The unstructured nature of data as well as the myriad sources they come from make it particularly challenging for companies to systematically capture, cleanse, store, and analyze the data. Python is a simple yet powerful language that has a rich ecosystem to facilitate the analysis of such complex data. The aim of this course is to acquaint students with aspects of the Python language that are necessary to effectively function as a data scientist. Upon successful completion of the course, students will be familiar with data structures and programming constructs in the Python language, accessing data from files and databases, Market-Basket Analysis, Text Analytics, and Map-Reduce.

        Prerequisite: INSY 5336 (Python) and INSY 5339 (Data Mining)

        .

        Learning Objectives: The aim of this course is to acquaint students with aspects of the Python language that are necessary to effectively function as a “data scientist”. Upon successful completion of the course, students will be familiar with:

        a.         Data structures and programming constructs in the Python language. Specifically, students will have a good grasp of lists, tuples, dictionaries, classes, selection (e.g., if ..else), and iteration (e.g., while and for loops).

        b.         Accessing data from files (e.g., text, csv, JSON, etc.) and databases.

        c.         Market-Basket Analysis using R

        d.         Text Analytics in Python & R, including topic modeling and sentiment analysis

        e.         Machine learning algorithms using Scikit-learn.

        f.          Basics of Social Network Analysis using Networkx

        Fall - Regular Academic Session - 2018 Download Syllabus Contact info & Office Hours
      • INSY 6301-001 SEMINAR IN RESEARCH FOUNDATIONS

        This course introduces you to the world of IS & Analytics research.  The first and foremost objective of this course is to nurture you into a first-rate scholar for the IS field.  We will provide a stimulating environment for the first phase of your development and growth as a scholar.  We will foster the ability to critically think and constructively criticize research papers in the IS field, as well as begin to form the foundation for building your own schema for the field.  In addition, we will provide each student an opportunity to conduct a research study.  Our goal is to help you publish in top IS journals while still in the doctoral program.

        Specifically, this course will provide:

        An overview of key articles pertaining to the area of Information Systems and Business Analytics, and introduce key theoretical perspectives that allow IS phenomena to be examined from different vantage points.  The underlying theories include transaction cost economics, theory of reasoned action and planned behaviors, resource-based view of a firm, and distributed cognition theory, to name but a few.

        A broad survey of research studies related to IS/IT management that illustrate the applications of the various theoretical perspectives.  Topics for the course include, but may not be limited to:

        business analytics

        knowledge management

        IS use and success

        Business value of IT

        Agile software development

        IS strategy and management

        Business Analytics

        Social Networks

        A broad but in-depth coverage of the research methodologies and the current theoretical frontier in the IS field.

        Fall - Regular Academic Session - 2018 Download Syllabus Contact info & Office Hours
      • INSY 5380-001 SOCIAL NETWORK ANALYSIS

        The course covers a broad range of concepts and analytical techniques used in Social Network Analysis (SNA). Networks are engendered by relationships and/or connections between actors (such as humans, hospitals, and organizations). The proliferation of social media has increased the number and variety of networks. Organizations are increasingly relying on SNA and other analytical techniques to gain insights from such networks. This course will equip students with the skills necessary to help firms in their endeavor to compete on analytics.

      • INSY 5336-001 PYTHON PROGRAMMING

        An introductory programming course that teaches students how to solve business problems using the scripting language, Python. Students will be exposed to object-oriented programming concepts, file handling, database access, and graphical user interfaces. 

        Spring - Regular Academic Session - 2018 Download Syllabus Contact info & Office Hours
      • INSY 5376-001 Big Data Analytics

        This course addresses the concepts and principles of Big Data and how Big Data can be used in the Enterprise. The course starts with an overview of the fundamental principles of Big Data and its role in making better decisions and predictions in the organization. Following the Fundamentals of Big Data, we address the Technology, Infrastructure and Applications of Big Data. The Software and Application requirements of Big Data are discussed and a number of case studies of Big Data Applications are studied. 

        Spring - Regular Academic Session - 2018 Download Syllabus Contact info & Office Hours
      • INSY 5378-001 Data Science: A Programming Approach

        The world is awash in data and companies are now trying to discern patterns and predict behaviors of both consumers and competitors to gain and sustain a competitive advantage. The unstructured nature of data as well as the myriad sources they come from make it particularly challenging for companies to systematically capture, cleanse, store, and analyze the data. Python is a simple yet powerful language that has a rich ecosystem to facilitate the analysis of such complex data. The aim of this course is to acquaint students with aspects of the Python language that are necessary to effectively function as a data scientist. Upon successful completion of the course, students will be familiar with data structures and programming constructs in the Python language, accessing data from files and databases, Market-Basket Analysis, Text Analytics, and Map-Reduce. 

        Fall - Regular Academic Session - 2017 Download Syllabus Contact info & Office Hours
      • INSY 5376-001 Big Data Analytics

        This course addresses the concepts and principles of Big Data and how Big Data can be used in the Enterprise. The course starts with an overview of the fundamental principles of Big Data and its role in making better decisions and predictions in the organization. Following the Fundamentals of Big Data, we address the Technology, Infrastructure and Applications of Big Data. The Software and Application requirements of Big Data are discussed and a number of case studies of Big Data Applications are studied. 

        Fall - Regular Academic Session - 2017 Download Syllabus Contact info & Office Hours
      • INSY 5380-001 SOCIAL NETWORK ANALYSIS

        The course covers a broad range of concepts and analytical techniques used in Social Network Analysis (SNA). Networks are engendered by relationships and/or connections between actors (such as humans, hospitals, and organizations). The proliferation of social media has increased the number and variety of networks. Organizations are increasingly relying on SNA and other analytical techniques to gain insights from such networks. This course will equip students with the skills necessary to help firms in their endeavor to compete on analytics.

      • INSY 5376-001 Big Data Analytics

        This course addresses the concepts and principles of Big Data and how Big Data can be used in the Enterprise. The course starts with an overview of the fundamental principles of Big Data and its role in making better decisions and predictions in the organization. Following the Fundamentals of Big Data, we address the Technology, Infrastructure and Applications of Big Data. The Software and Application requirements of Big Data are discussed and a number of case studies of Big Data Applications are studied. 

        Spring - Regular Academic Session - 2017 Download Syllabus Contact info & Office Hours
      • INSY 5375-001 Management of Information Technologies

        This course covers topics on the management of information technologies (IT) from the view point of senior managers. Subjects discussed include the strategic role of IT to gain competitive advantage, Internet-based business models, building a lean and agile organization through IT, managing IT security and reliability, evolving models of IT service delivery, such as cloud computing and open source, management of outsourcing, IT governance, and ethical issues in the digital era. In addition to classroom lectures, the course relies heavily on case analysis and discussion to provide a real world perspective of issues related to IT management.

        Spring - Regular Academic Session - 2017 Download Syllabus Contact info & Office Hours
      • INSY 5375-080 MANAGEMENT OF INFORMATION TECHNOLOGIES

        This course covers topics on the management of information technologies (IT) from the view point of senior managers. Subjects discussed include the strategic role of IT to gain competitive advantage, Internet-based business models, building a lean and agile organization through IT, managing IT security and reliability, evolving models of IT service delivery, such as cloud computing and open source, management of outsourcing, IT governance, and ethical issues in the digital era. In addition to classroom lectures, the course relies heavily on case analysis and discussion to provide a real world perspective of issues related to IT management.

        Spring - Regular Academic Session - 2017 Download Syllabus Contact info & Office Hours
      • INSY 5376-001 Big Data Analytics

        This course addresses the concepts and principles of Big Data and how Big Data can be used in the Enterprise. The course starts with an overview of the fundamental principles of Big Data and its role in making better decisions and predictions in the organization. Following the Fundamentals of Big Data, we address the Technology, Infrastructure and Applications of Big Data. The Software and Application requirements of Big Data are discussed and a number of case studies of Big Data Applications are studied. 

        Fall - Regular Academic Session - 2016 Download Syllabus Contact info & Office Hours
      • INSY 6301-001 SEMINAR IN RESEARCH FOUNDATIONS

        This course introduces you to the world of IS research.  The first and foremost objective of this course is to nurture you into a first-rate scholar for the IS field.  We will provide a stimulating environment for the first phase of your development and growth as a scholar.  We will foster the ability to critically think and constructively criticize research papers in the IS field, as well as begin to form the foundation for building your own schema for the field.  In addition, we will provide each student an opportunity to conduct a research study.  Our goal is to help you publish in top IS journals while still in the doctoral program. 

        Fall - Regular Academic Session - 2016 Download Syllabus Contact info & Office Hours
      • INSY 3300-003 Introduction to Programming

        An introductory programming course that teaches students how to solve business problems using the scripting language, Python. Students will be exposed to object-oriented programming concepts, file handling, database access, and graphical user interfaces. 

        Spring - Regular Academic Session - 2016 Download Syllabus Contact info & Office Hours
      • INSY 5378-001 Data Science: A Programming Approach

        The world is awash in data and companies are now trying to discern patterns and predict behaviors of both consumers and competitors to gain and sustain a competitive advantage. The unstructured nature of data as well as the myriad sources they come from make it particularly challenging for companies to systematically capture, cleanse, store, and analyze the data. Python is a simple yet powerful language that has a rich ecosystem to facilitate the analysis of such complex data. The aim of this course is to acquaint students with aspects of the Python language that are necessary to effectively function as a data scientist. Upon successful completion of the course, students will be familiar with data structures and programming constructs in the Python language, accessing data from files and databases, Market-Basket Analysis, Text Analytics, and Map-Reduce. 

        Spring - Regular Academic Session - 2016 Download Syllabus Contact info & Office Hours
      • INSY 3300-001 OBJECT-ORIENTED PROGRAMMING

        An introductory programming course that teaches students how to solve business problems using the scripting language, Python. Students will be exposed to object-oriented programming concepts, file handling, database access, and graphical user interfaces.

        Fall - Regular Academic Session - 2015 Download Syllabus Contact info & Office Hours
      • INSY 3300-002 OBJECT-ORIENTED PROGRAMMING

        An introductory programming course that teaches students how to solve business problems using the scripting language, Python. Students will be exposed to object-oriented programming concepts, file handling, database access, and graphical user interfaces.

        Fall - Regular Academic Session - 2015 Download Syllabus Contact info & Office Hours
      • INSY 5373-001 INFORMATION SYSTEMS PROJECT MANAGEMENT

        This course introduces students to the concepts and practices of project management and their importance to improving the success of information technology projects. Distinct aspects or characteristics of IT projects which cause these projects to behave differently in the corporate world than do other, non-technical, projects will be discussed.

        Fall - Regular Academic Session - 2015 Download Syllabus Contact info & Office Hours
      • INSY 6392-001 Special Topics in Information Systems

        The primary objective of this course is to expose students to research issues in software development, including object-oriented analysis & design and agile methodologies. The articles used in the course are drawn from premier publication outlets such as MISQ, ISR, and IEEE Transactions on Software Engineering. In addition, the readings include a number of articles from small-group research that deal with group dynamics, team cognition/mental models, transactive memories and creativity in teams.  Research in the nascent area of analytics will be introduced as well.

        Fall - Regular Academic Session - 2014 Download Syllabus Contact info & Office Hours
      • INSY 5373-001 Project Management

        This course introduces students to the concepts and practices of project management and their importance to improving the success of information technology projects. Distinct aspects or characteristics of IT projects which cause these projects to behave differently in the corporate world than do other, non-technical, projects will be discussed.

        Fall - Regular Academic Session - 2014 Download Syllabus Contact info & Office Hours
      • OPMA 5364-001 Project Management

        This course studies the concepts, issues and approaches important in effectively managing projects.  Topics include project selection, organizational structures, project planning, estimation, scheduling, resource allocation, risk management, crashing, earned value analysis and agile project management.  Topics are viewed from a managerial perspective.

        Fall - Regular Academic Session - 2014 Download Syllabus Contact info & Office Hours
      • INSY 5341-001 Systems Analysis & Design

        This course covers concepts, tools, and technologies associated with the analysis and design of information systems using the object-oriented (OO) paradigm.  OO concepts are discussed and OO systems development life cycle is introduced.  OO analysis and design techniques using the UML (Unified Modeling Language) are discussed.  Students get hands on training in analysis and design through a group project. 

      • INSY 5373-001 Information Systems Project Management

        This course studies the concepts, issues and approaches important in effectively managing projects.  Topics include project selection, organizational structures, project planning, estimation, scheduling, resource allocation, risk management, crashing, earned value analysis and agile project management.  Topics are viewed from a managerial perspective.

      • OPMA 3310-001 Project Management

        This course studies the concepts, issues and approaches important in effectively managing projects.  Topics include project selection, organizational structures, project planning, estimation, scheduling, resource allocation, risk management, crashing, earned value analysis and agile project management.  Topics are viewed from a managerial perspective.

      • OPMA 5364-001 Project Management

        This course studies the concepts, issues and approaches important in effectively managing projects.  Topics include project selection, organizational structures, project planning, estimation, scheduling, resource allocation, risk management, crashing, earned value analysis and agile project management.  Topics are viewed from a managerial perspective.

      • INSY 3309-001 Python Programming

        The world is awash in data and companies are now trying to discern patterns and predict behaviors – of both consumers and competitors – to gain and sustain a competitive advantage. The unstructured nature of data as well as the myriad sources they come from make it particularly challenging for companies to systematically capture, cleanse, store, and analyze the data. Python is a simple yet powerful language that has a rich ecosystem to facilitate the analysis of such complex data. The aim of this course is to acquaint students with aspects of the Python language that are necessary to effectively function as a “data scientist”. Upon successful completion of the course, students will be familiar with:

        a.         Data structures and programming constructs in the Python language. Specifically, students will have a good grasp of lists, tuples, dictionaries, classes, selection (e.g., if ..else), and iteration (e.g., while and for loops).

        b.         Accessing data from files (e.g., text, csv, JSON, etc.) and databases. Students will also be exposed to the fundamentals of SQL.

        c.         Map-Reduce, the abstraction from Google that inspired Hadoop. Specifically, we will use a lightweight Python implementation of map-reduce.

        d.         Social Network analysis using the Networkx module.

        e.         Machine learning algorithms using Scikit-learn.

        f.          Basics of Python-R interface.

        Spring - Regular Academic Session - 2014 Download Syllabus Contact info & Office Hours
      • INSY 5392-002 Seminar in Information Systems - Python Programming

        The world is awash in data and companies are now trying to discern patterns and predict behaviors – of both consumers and competitors – to gain and sustain a competitive advantage. The unstructured nature of data as well as the myriad sources they come from make it particularly challenging for companies to systematically capture, cleanse, store, and analyze the data. Python is a simple yet powerful language that has a rich ecosystem to facilitate the analysis of such complex data. The aim of this course is to acquaint students with aspects of the Python language that are necessary to effectively function as a “data scientist”. Upon successful completion of the course, students will be familiar with:

        a.         Data structures and programming constructs in the Python language. Specifically, students will have a good grasp of lists, tuples, dictionaries, classes, selection (e.g., if ..else), and iteration (e.g., while and for loops).

        b.         Accessing data from files (e.g., text, csv, JSON, etc.) and databases. Students will also be exposed to the fundamentals of SQL.

        c.         Map-Reduce, the abstraction from Google that inspired Hadoop. Specifically, we will use a lightweight Python implementation of map-reduce.

        d.         Social Network analysis using the Networkx module.

        e.         Machine learning algorithms using Scikit-learn.

        f.          Basics of Python-R interface.

        Spring - Regular Academic Session - 2014 Download Syllabus Contact info & Office Hours
      • INSY 5375-020 Management Information Systems

        The course is designed to provide a broad managerial view of management and deployment of IT resources.  Information technology (IT) has dramatically altered the way organizations conduct business and compete in a global marketplace.  The commercialization of the Internet has created new electronic market places, and new channels of supply and distribution.  New business models are continuing to emerge and challenge our notion of how best to organize a business.  This course aims to discuss the challenges of managing a business in a global networked economy.  It provides an understanding of the influence of IT on business decisions from a senior management perspective.  The implications of emerging trends such as cloud computing, social media, mobile computing, and business analytics will also be discussed.

      • INSY 3305-001 Analysis and Design

        Analysis and design phase of systems development life cycle. Topics include systems survey, functional specification, interface specification, data design, program design, system testing, and implementation. 

        This course provides a solid treatment of foundation principles but in the context of all the new tools, technologies, and approaches to systems development.

        Fall - Regular Academic Session - 2013 Download Syllabus Contact info & Office Hours
      • INSY 5341-001 Analysis and Design

        Analysis and design phase of systems development life cycle. Topics include systems survey, functional specification, interface specification, data design, program design, system testing, and implementation. 

        This course provides a solid treatment of foundation principles but in the context of all the new tools, technologies, and approaches to systems development.

        Fall - Regular Academic Session - 2013 Download Syllabus Contact info & Office Hours
      • INSY 4325-001 Information Resource Management

        The course is designed to provide INSY majors, who already have a strong technical background, a broad managerial view of deployment and management of IT resources.  Information technology (IT) has dramatically altered the way organizations conduct business and compete in a global marketplace.  The commercialization of the Internet has created new electronic market places, and new channels of supply and distribution.  New business models are continuing to emerge and challenge our notion of how best to organize a business.  This course aims to discuss the challenges of managing a business in a global networked economy.  It provides an understanding of the influence of IT on business decisions from a senior management perspective.  

        Fall - Regular Academic Session - 2013 Download Syllabus Contact info & Office Hours
      • INSY 5373-001 INFORMATION SYSTEMS PROJECT MANAGEMENT
        This course studies the concepts, issues and approaches important in effectively managing projects. Topics include project selection, project planning, negotiation, budgeting, scheduling, resource allocation, project control, project auditing, and project termination. Topics are viewed from a managerial perspective.
        Summer - Regular Academic Session - 2013 Download Syllabus 1 Link
      • OPMA 3310-001 PROJECT MANAGEMENT
        This course studies the concepts, issues and approaches important in effectively managing projects. Topics include project selection, project planning, negotiation, budgeting, scheduling, resource allocation, project control, project auditing, and project termination. Topics are viewed from a managerial perspective.
        Summer - Regular Academic Session - 2013 Download Syllabus 1 Link
      • OPMA 5364-001 PROJECT MANAGEMENT
        This course studies the concepts, issues and approaches important in effectively managing projects. Topics include project selection, project planning, negotiation, budgeting, scheduling, resource allocation, project control, project auditing, and project termination. Topics are viewed from a managerial perspective.
        Summer - Regular Academic Session - 2013 Download Syllabus 1 Link
      • INSY 3300-002 OBJECT-ORIENTED PROGRAMMING
        Topics include object-based and object-oriented program design and processing, language fundamentals and applications involving business problems.
        Spring - Regular Academic Session - 2013 Download Syllabus 1 Link
      • INSY 5309-001 OBJECT-ORIENTED BUSINESS PROGRAMMING
        Topics include object-based and object-oriented program design and processing, language fundamentals and applications involving business problems.
        Spring - Regular Academic Session - 2013 Download Syllabus 1 Link
      • INSY 4325-001 Information Resource Management
        The course is designed to provide INSY majors, who already have a strong technical background, a broad managerial view of deployment and management of IT resources. Information technology (IT) has dramatically altered the way organizations conduct business and compete in a global marketplace. The commercialization of the Internet has created new electronic market places, and new channels of supply and distribution. New business models are continuing to emerge and challenge our notion of how best to organize a business. This course aims to discuss the challenges of managing a business in a global networked economy. It provides an understanding of the influence of IT on business decisions from a senior management perspective.
        Spring - Regular Academic Session - 2013 Download Syllabus 1 Link
      • INSY 4331-001 SEMINAR IN INFORMATION SYSTEMS
        This is a special topics course on Python programming. Python is a scripting language that is at once powerful and easy to learn. The language has found favor among web developers and game programmers, and is being used as an introductory programming language in many schools.
        Spring - Regular Academic Session - 2013 Download Syllabus 1 Link
      • INSY 5392-001 SELECTED TOPICS IN INFORMATION SYSTEMS
        This is a special topics course on Python programming. Python is a scripting language that is at once powerful and easy to learn. The language has found favor among web developers and game programmers, and is being used as an introductory programming language in many schools.
        Spring - Regular Academic Session - 2013 Download Syllabus 1 Link
      • OPMA 3310-001 PROJECT MANAGEMENT
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        This course studies the concepts, issues and approaches important in effectively managing projects.Topics include project selection, project planning, negotiation, budgeting, scheduling, resource allocation, project control, project auditing, and project termination.Topics are viewed from a managerial perspective.

        Fall - Regular Academic Session - 2012 Download Syllabus 1 Link
      • INSY 4325-001 Information Resource Management
        The course is designed to provide INSY majors, who already have a strong technical background, a broad managerial view of deployment and management of IT resources. Information technology (IT) has dramatically altered the way organizations conduct business and compete in a global marketplace. The commercialization of the Internet has created new electronic market places, and new channels of supply and distribution. New business models are continuing to emerge and challenge our notion of how best to organize a business. This course aims to discuss the challenges of managing a business in a global networked economy. It provides an understanding of the influence of IT on business decisions from a senior management perspective. The objectives of the course are to: 1. Provide a process-oriented view of organizations. 2. Provide an understanding of how end-to-end business processes work in organizations. 3. Facilitate an understanding of the role of ERP (enterprise resource planning) systems. 4. Give students a hands-on experience with a real-world ERP system. 5. Expose students to emerging trends in enterprise software development/deployment/architectures, including SOA (service-oriented architecture), cloud-computing, and business intelligence.
        Fall - Regular Academic Session - 2012 Download Syllabus 1 Link
      • OPMA 5364-001 PROJECT MANAGEMENT
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        This course studies the concepts, issues and approaches important in effectively managing projects.Topics include project selection, project planning, negotiation, budgeting, scheduling, resource allocation, project control, project auditing, and project termination.Topics are viewed from a managerial perspective.

        Fall - Regular Academic Session - 2012 Download Syllabus 1 Link
      • INSY 4325-001 Information Resource Management

        The course is designed to provide INSY majors, who already have a strong technical background, a broad managerial view of deployment and management of IT resources.Information technology (IT) has dramatically altered the way organizations conduct business and compete in a global marketplace.The commercialization of the Internet has created new electronic market places, and new channels of supply and distribution.New business models are continuing to emerge and challenge our notion of how best to organize a business.This course aims to discuss the challenges of managing a business in a global networked economy.It provides an understanding of the influence of IT on business decisions from a senior management perspective.

        The objectives of the course are to:

        1.Provide a process-oriented view of organizations.

        2.Provide an understanding of how end-to-end business processes work in organizations.

        3.Facilitate an understanding of the role of ERP (enterprise resource planning) systems.

        4.Give students a hands-on experience with a real-world ERP system.

        5.Expose students to emerging trends in enterprise software development/deployment/architectures, including SOA (service-oriented architecture), cloud-computing, and business intelligence.

        Summer - Regular Academic Session - 2012 Download Syllabus 1 Link
      • INSY 3305-001 Information Systems Analysis and Design
        his is a survey of the concepts and methods of information systems analysis and design, system development life cycle (SDLC) and methodologies associated with the SDLC. Course covers feasibility analysis, requirements definition, systems design, data design, coding design, programming, and implementation. Prerequisite: INSY 3304
        Spring - Regular Academic Session - 20071 Link

Other Teaching Activities

  • 2013
    • OPMA 5364
      • Oct 2013 Project Management

        Taught an EMBA class in Shanghai, China

      • Mar 2013 Project Management

        Taught an EMBA class in Taipei, Taiwan

      • Jan 2013 Project Management

        Taught an EMBA class in Shenzhen, China

Service to the Profession

  • Volunteered
    • Mar 2013 to  Present Reviewer

      Ad hoc reviewer for MIS Quarterly, Information Systems Research,  and the Canadian Journal of Administrative Sciences. 

Service to the University

  • Volunteered
    • Sept 2007 to  Present Committee on Student Organizations

      This is a university-wide committee.

  • Elected
    • Oct 2016 to  Present Research Advisory Committee for IT Governance

      University-wide committee to identify key concepts, suggest ways to prioritize, select and implement concepts, and also provide inputs on various aspects of IT Governance.

Other Service Activities

  • College and Department Committees
    • Aug 2013 Various department and college committees
      • Department curriculum committee: 2002 – present
      • College strategic planning committee; 2013
      • College teaching awards committee: 2012 and 2013
      • Research Centers Committee: 2013 - present
      • Research colloquia expansion committee: 2013 - present
      • MS Analytics Task Force: 2013 - present