Data Management & Analytics
This course studies the theory, design and implementation of data management and information retrieval systems. The data management portion covers indexing, query processing, transaction management, and XML. The information retrieval component of the course includes important retrieval models (Boolean, vector space, probabilistic), relevance feedback, and web search engines.
This course delves into research and survey papers in database and information retrieval, with an emphasis on system and application issues. Topics to be covered include spatial database, data integrity and privacy, indexing, information retrieval models, relevance feedback, and multimedia information retrieval. The course is intended to prepare graduate students for research in data management and information retrieval.
Prerequisites: IS701 Information Storage and Retrieval
Information Security & Trust
This course studies the key facets of information security, from theory to applications in a networked environment. Topics to be covered include symmetric key cryptosystems, number-theoretical foundations, public key cryptosystems, authentication, key exchange, access control, Internet security architecture, and emerging security standards.
This course introduces graduate students to advanced information security techniques, standards and applications. The course takes a practical approach to information security by focusing on real-world examples. While not sidestepping the theory, the emphasis is on developing the skills and knowledge that graduate students need in applying information security techniques in their research on information systems and applications. Topics to be covered are organized around four major themes: network security (real-time communication security, SSL, IPSec and VPN), web security (advanced user authentication, web client security and web server security), application security (trusted third party services, user privacy, multimedia security and electronic payment solutions), and emerging technologies (such as trusted computing platforms).
Information Systems & Management
The course aims to offer graduate students an overview of fundamental research methodologies in information systems and management. It covers concepts from various areas such as microeconomics, econometrics, optimization, stochastic process, and game theory. Students will be exposed to topics such as the strategic role of IT, business value of IT, strategic alignment of IT, IT outsourcing, IS capabilities, competencies and leadership. With the knowledge acquired during this course, students will be able to identify, formulate, and analyze their interested ISM research question.
Intelligent Systems & Interaction
This course provides methodological foundations of intelligent decision support systems. It covers:
- Classical algorithmic paradigms - Divide/Conquer Greedy, Dynamic Programming
- Graphs and Networks Models and Algorithms
- Mathematical and Constraint Modeling
- Local Search and Advanced Heuristics
Throughout the course, we will present a wide range of problems in supply chains, from strategic issues such as network design, to tactical issues such as procurement & sourcing, to operational issues such as real-time supply chain optimization. The course aims to equip students for decision support and optimization research, particularly in supply chain systems design and analysis.
This course explores recent advances in intelligent decision support methodologies. We will be studying survey and research papers from the following 3 topics:
- Optimized Decision Making (Meta-heuristics Search)
- Cooperative Decision Making (Distributed Problem Solving, Planning and Scheduling, Auctions)
- Non-Cooperative Decision Making (Game-theoretic Approaches, Agent Negotiation
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