Return to: Graduate Programs

VANDANA JANEJA, Chair
ZHIYUAN CHEN, Associate Chair for Academic Affairs
GEORGE KARABATIS, Liaison for Programmatic Innovations
MICHAEL BROWN, Graduate Program Director, ISO
SHIMEI PAN, Graduate Program Director, IS
ANDREA KLEINSMITH, Graduate Program Director, HCC
ERIN VAN DYKE, Graduate Program Director, HIT

Degrees Offered

M.S., Ph.D. (Degree Types )

Faculty

Professors

CHEN, ZHIYUAN, Ph.D., Cornell University; database systems and data mining, including privacy preserving data mining, data exploration and navigation, data integration, XML, automatic database administration, and database compression
GANGOPADHYAY, ARYYA, Ph.D., , Rutgers University; privacy preserving data mining, knowledge discovery in structured and unstructured data, health information systems
KARABATIS, GEORGE, Ph.D., University of Houston; database systems, cyber-security, semantic integration of enterprise systems, data integration, mobile data management
KORU, A. GUNES, Ph.D., Southern Methodist University; health information technology, privacy, data mining, measurement, quality improvement, project management, and open source systems
JANEJA, VANDANA, Ph.D., Chair, Rutgers University; spatial data mining, anomaly detection, disease informatics, data mining for e-government and homeland security applications
MENTIS, HELENA, Ph.D., Penn State University; human-computer interaction, computer supported cooperative work, and biomedical informatics.  I specifically focus on engaging in a translational research approach to align coordinated clinical practices with information technology such as gestural interaction in the OR, informal data sharing in the emergency room, and health information sharing 
SEAMAN, CAROLYN, Ph.D., University of Maryland, College Park; software engineering, software maintenance, knowledge management, software development organizations, qualitative research methods

Associate Professors

JOSHI, KARUNA P., Ph.D., UMBC; Data Science, Cloud Computing, Services Science and Healthcare IT systems. Her research is supported by ONR, NSF, DoD, IBM, GE and Cisco.
KLEINSMITH, ANDREA, Ph.D., University College London, UK; Human-Computer Interaction and Affective Computing and focus on measuring and modeling body expressions in real world training situations.
KOMLODI, ANITA, Ph.D., University of Maryland, College Park; human-centered computing, information storage and retrieval, computer supported cooperative work
KUBER, RAVI, Ph.D., Queen’s University Belfast, Northern Ireland; human-centered computing, universal access to technology, haptic and multimodal interface design and evaluation
OZOK, A. ANT, Ph.D., Purdue University; School of Industrial Engineering; human-centered computing, human-technology interaction in health care, human factors in patient safety, user aspects of e-commerce, survey design and implementation, usability design evaluation methodologies, multiple-method approaches in human factors
PAN, SHIMEI, Ph.D., Columbia University; natural language processing, intelligent user interfaces and user modeling, interactive machine learning and data mining
RAHNEMOONFAR, MARYAM, PhD., University of Salford Manchester; Deep Learning, Computer Vision, Data Science, AI for Social Good, Remote Sensing, and Document Image Analysis, developing novel machine learning and computer vision algorithms for heterogenous sensors such as Radar, Sonar, Multi-spectral, and Optical
ROY, NIRMALYA, Ph.D, University of Texas at Arlington;  pervasive healthcare, sensor-driven health and green technologies, design and modeling of smart environments, and mobile and pervasive systems
SAMPATH, SREEDEVI, Ph.D., University of Delaware; software engineering, software testing, testing web applications, software maintenance, program analysis

Assistant Professors

CHEN, LUJIE (KAREN), Ph.D., Carnegie Mellon; applied machine learning and data science researcher, education and healthcare research aiming to promote lifelong and lifewide learning and well-being, design of effective and inclusive interventions for a diverse population, especially those traditionally with limited voices in technology development.
FOULDS, JAMES, Ph.D., University of California, Irvine; applied and foundational machine learning, focusing on probabilistic latent variable models and the inference algorithms to learn them from data. His work aims to promote the practice of latent variable modeling for multidisciplinary research in areas including computational social science and the digital humanities.
GANI, MD OSMAN, PhD., Marquette University; artificial intelligence, causal inference, and machine learning with an interest in contributing to a deeper understanding of cause and context, explainable artificial intelligence, ubiquitous computing, indoor localization, healthcare, and human activity recognition
HAMIDI, FOAD, PhD, York University; research is focused on the participatory design and evaluation of emerging systems, including digital living media systems and adaptive systems, for different users including children and adults with and without disabilities, 
MASSEY, AARON, Ph.D., North Carolina State University; computer security, privacy, software engineering, and regulatory compliance in software systems.
PURUSHOTHAM, SANJAY,  Ph.D., University of Southern California; machine learning, data science, computer vision and its applications to healthcare & bio-informatics, social network analysis, and multimedia data mining. His current work involves developing novel deep learning models for data-driven analysis of healthcare time series data and building machine learning models for mathematical oncology.
WANG, JIANWU, PhD, Institute of Computing Technology, Chinese Academy of Sciences; Big Data, Scientific Workflow, Distributed Computing, Service-Oriented Computing and End-User Programming.
YAO, YAXING, PhD., Syracuse University; research lies in the intersection of Human-Computer Interaction (HCI), Usable Privacy, and Design. develop novel privacy-enhancing technologies to address the privacy needs of multiple stakeholders in shared systems such as the IoT, Smart Homes, and Smart Cities

Program Description

The Information Systems Department offers MS and PhD degrees in Information Systems (IS), Human-Centered Computing (HCC), and an M.P.S. in Health Information Technology (HIT). Prospective MS students can choose from three campus-based MS degrees (IS, HIT and HCC) or one completely online MS degree (IS only). All programs are designed for students who wish to further their knowledge and experience in the area of Information Systems, Health Information Technology or Human-Centered Computing. These programs may also be of interest to individuals whose undergraduate academic backgrounds are not in a computer or information systems discipline but who meet the department’s admission requirements.

The IS department offers two Ph.D. programs. They are research oriented and intended for graduate students who desire to make research contributions to the field of Information Systems (IS) or Human-Centered Computing (HCC).

The MS programs in IS (campus-based or online) focus on using computer technologies to provide methods, practices, and algorithms that transform data into information and knowledge desired by, and useful for, individual and group users in organizations.

Research Areas

The department’s faculty and programs have a broad view of information systems. Research areas include, but are not limited to:
•    Artificial Intelligence/Knowledge Management
•    Database/Data Mining
•    Health Informatics
•    Human-Centered Computing
•    Systems and Software

Program Admission Requirements

Admissions decisions are based on the following criteria:

• Bachelor’s degree: A four-year bachelor’s degree from a regionally accredited college or university or an equivalent degree from a comparable foreign institution.
• Language requirements: All applicants are expected to read, speak, write and understand English fluently upon entering the program. A TOEFL (Test of English as a Foreign Language) or an IELTS test is required for students who have earned an undergraduate degree from a non-English-speaking college or university. Applicants whose native language is not English, but who have a post-secondary degree from an Englishspeaking institution will not be required to take the TOEFL or IELTS. The minimum acceptable TOEFL score established for admission into the program is 550 (written), 213 (computerized), or 80 (iBT). The minimum acceptable IELTS score is 6.5. TOEFL information and applications are available from Educational Testing Service (ETS) at TOEFL, Educational Testing Service, P.O. Box 6151, Princeton, NJ
• 08541-6151, Phone: 609-771-7100 or online at www.toefl.org. IELTS information can be obtained from www.ielts.org.
• GRE scores are not required for any of the MS programs and the Human-Centered Computing Ph.D. program. Applicants for the Information Systems Ph.D. program must submit their GRE Aptitude Test scores before the application deadline.
• The majority of successful applicants have an undergraduate GPA well above 3.0 (on a 4.0 scale). Applicants with GPA slightly under 3.0 may be granted for conditional acceptance, depending on their past working experience and other evidence that shows applicants’ potential in succeeding in the M.S. program.
• The application deadline dates for the programs are as follows:
  • Domestic Application Deadlines:
    • M.S.: May 1 and October 1                    
    • Ph.D.: February 1 and September 1
  • International Application Deadlines:
    • January 1 and June 1

Note: All original application documents for the Campus Based Programs must be sent directly to the Graduate School, rather than to the graduate program. UMBC’s assigned TOEFL code is 005835. TOEFL test must have been within 2 years of matriculation to be valid.

For details on all of our graduate level programs, please visit the department’s website at www.is.umbc.edu.

Financial Assistance

A limited number of graduate teaching assistantships are available to students enrolled in the Information Systems and Human-Centered Computing Ph.D. programs. Interested students are asked to apply the semester before.

For More Information

Visit:
www.is.umbc.edu

Contact:

Shimei Pan
Graduate Program Director for IS Program
shimei@umbc.edu

Ravi Kuber
Graduate Program Director for HCC Programs
kuber@umbc.edu

Anita Komlodi
Graduate Program Director, IS Online
komlodi2umbc.edu

Shannon Keegan
Graduate Program Manager
410-455-2650
keegan@umbc.edu

Erin Van Dyke
Graduate Program Director, HIT
Evandyke1@umbc.edu

UMBC Graduate School
1000 Hilltop Circle
Baltimore, MD 21250
410-455-2537
www.umbc.edu/gradschool/
umbcgrad@umbc.edu

Programs

• Information Systems, M.S.
• Information Systems, Online, M.S.

• Information Systems, Ph.D.

Courses

• IS 503 - Information and Communications Technology
• IS 600 - Introduction to Object-Oriented Programming Concepts
• IS 601 - Management Information Systems
• IS 602 - Data Communications and Networks
• IS 603 - Decision Technology Systems
• IS 605 - Information Systems Fundamentals I
• IS 606 - Informations Systems Fundamentals II
• IS 607 - Introduction to Information Systems
• IS 610 - Database Program Development
• IS 613 - Graphical User Interface Design & Implementation
• IS 620 - Advanced Database Projects
• IS 625 - Decision Support Systems
• IS 630 - Information Resources Management
• IS 631 - Management Information Systems
• IS 631F - Management Information Systems
• IS 632 - Networks
• IS 632F - Networking Infrastructure
• IS 633 - Database Management Systems
• IS 634 - Structured Systems Analysis & Design
• IS 634F - Modern Systems Analysis and Design
• IS 636 - Structured Systems Analysis and Design
• IS 642 - Information System Analysis
• IS 643 - Electronic Government
• IS 648 - Markup and Scripting Languages
• IS 650 - Data Communications and Networks
• IS 651 - Distributed Systems
• IS 651M - LAN Management Using Microsoft NT
• IS 651N - LAN Management Using NOVELL Netware
• IS 651U - LAN Management Using UNIX
• IS 651W - Server-Side Web Systems
• IS 652 - Internetworking
• IS 652C - Local Area Network Management II
• IS 654 - Survey of Telecommunications
• IS 655 - Neural Networks for Information Processing
• IS 659 - Principles of Cybersecurity
• IS 660 - Health Care Informatics I
• IS 661 - Biomedical Informatics Applications
• IS 664 - Telemedicine in Trauma Care
• IS 667 - Interaction Design
• IS 667F - E-Commerce
• IS 668 - Enterprise-Wide Computing
• IS 668F - Enterprise-Wide Computing
• IS 669 - Project Management Operations
• IS 670 - Health Informatics
• IS 671 - Electronic Commerce
• IS 672 - Computer and Network Security
• IS 673 - Readings in Human-Centered Computing Research
• IS 674 - Information Architecture for the Web
• IS 675 - Data Science
• IS 676 - Information Integration
• IS 677 - Deep Learning
• IS 678 - Data Analytics in Cybersecurity
• IS 679 - Social Media Application and Analytics
• IS 680 - Readings in Systems Design
• IS 698 - Special Topics in Information Systems
• IS 698C - Topics In Information Systems
• IS 699 - Capstone Project
• IS 700 - Independent Study in Information Systems
• IS 701 - Independent Study for IFSU
• IS 705 - Simulation and Visualization
• IS 706 - Interfaces For Info. Visualization & Retrieval
• IS 707 - Applications of Intelligent Technologies
• IS 708 - Knowledge Management and Knowledge Organizations
• IS 709 - Computational Methods for IS Research
• IS 720 - Mobile Data Management
• IS 721 - Semi-Structured Data Management
• IS 722 - Systems and Information Integration
• IS 725 - Information Extraction
• IS 727 - Computer-Supported Cooperative Work
• IS 728 - Online Communities
• IS 730 - Decision Sciences
• IS 731 - Electronic Commerce
• IS 732 - Decision Systems Integration
• IS 733 - Data Mining
• IS 734 - Data Analytics for Cybersecurity
• IS 740 - Fundamentals of Software Testing
• IS 755 - Advanced Artificial Intelligence
• IS 757 - Deep Learning
• IS 760 - Human-Computer Interaction
• IS 764 - Advanced Systems Design
• IS 765 - Project Management
• IS 766 - Office Automation Systems
• IS 777 - Data Analytics for Statistical Learning
• IS 789 - Big Data Fundamentals and Techniques
• IS 799 - Master’s Thesis Research
• IS 800 - Special Topics in Information Systems
• IS 800G - Special Topics In Information Systems: Gateway Seminar
• IS 801 - Independent Study in Information Systems
• IS 802 - Gateway Seminar for Doctoral Seminar Students II
• IS 803 - Gateway Seminar for Doctoral Students 1
• IS 804 - Advanced Quantitative Methods in IS Research
• IS 805 - Advanced Field Research Methods
• IS 809 - Computational Methods for IS Research
• IS 898 - Pre-Candidacy Doctoral Research
• IS 899 - Doctoral Dissertation Research
• IS 8800 - Doctoral Special Study

Return to: Graduate Programs