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Yinghui Wu Theodore L. and Dana J. Schroeder Associate Professor Department of Computer & Data Sciences Case School of Engineering Case Western Reserve University |
Olin 515 2101 Martin Luther King Jr Dr, Cleveland, OH 44106 Office: 216.368.8829 Email: yxw1650_at_case_dot_edu Homepage: https://yinghwu.github.io/ |
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Office Hours:
Spring 2026: Tu/Thu 11 am - noon, Olin 515 (Zoom details: see CWRU Google Calendar)
Academic advisees: you may propose a 10-15 minute appointment through Google Calendar.
Log in with your CWRU ID, search my name under "Meet with," and select from the available time slots.
Teaching
- (Spring '26) CSDS 234:
Structured & Unstructured Data [Canvas][Syllabus]
Tu/Thu 8:30 am - 9:45 am, Olin 305
TA: Yuhong Lu
This course introduces foundational and emerging data representations (relational tables, XML/RDF, vectors, text, images, and multimodal data), together with storage, indexing, and query processing techniques for modern data-intensive and AI/ML applications. The project-oriented course connects core data-system principles with relational and multimodal databases, vector databases, and knowledge bases that support applications such as search, question answering, recommendation, and AI systems.
For students: please access Canvas for course resources and materials.
- CSDS 433: Database Systems [Canvas][Syllabus]
Tu/Thu 8:30 am - 9:45 am, Olin 306
Fundamental and advanced
topics in modern data management systems: relational and
non-relational systems, semistructured data, data constraints,
approximate query processing, distributed and parallel data
processing, data cleaning and quality, and the interaction
between database systems and AI (DB4AI and AI4DB). The course
emphasizes how classical database principles extend to data
engineering and infrastructure for ML/AI workloads.
Recommended preparation: MATH 304 and CSDS 341. For students:
please access
Canvas for course resources and
materials.
- CSDS 341: Introduction
to Databases [Canvas][Syllabus]
Mon/Wed 3:20 pm - 4:35 pm, White 411
Foundations of database systems, including the relational and ER models, relational algebra and calculus, SQL, OBE, security and views, files and physical database structures, query processing and optimization, normalization, and concurrency control. The course emphasizes durable database principles that underpin modern data-driven and AI applications.
- Automata and Formal Languages (Fall 17-18)
- Big Data (Fall 15-18)
- Advanced Databases (Spring 17-19)
- Data Mining (Fall 13)
- Advanced Topics in Web Databases (2010-2011)
- Research Topics in
Distributed Databases (2011)