Classes that I am involved with
| Class | Description | Dates |
|---|---|---|
| DSAIT 4500: Responsible Data Science and AI Engineering |
The goal of this course is to support students in further developing a responsible attitude that will contribute to the role you play in your future career. Students will learn to make and reflect on choices related to Responsible Data Science and AI Engineering with an ethical and sustainable stance and act with integrity. They will engage with social, organizational, professional, and technical aspects of developing DSAIT, from both systems and human-centric perspectives. Topics discussed include human agency and oversight, algorithmic robustness and safety, privacy and data governance, transparency, non-discrimination, fairness, inclusivity, accessibility, and accountability. | Q3(24/25) |
| DSAIT 4210: Research in Web Data andd Information Management |
In this course, we discuss recent developments in the area of web information systems. We discuss this content while learning about the role of scientific communication and about the scientific methodologies and approaches for conducting research in the area. | Q1(22/23); Q1(23/24); Q4(24/25) |
| CSE 3000: Research Project |
Mentor and supervisor for this course, which comprises an individual research project on a selected topic within computer science, supervised by an active researcher in the field. It should result in a scientific paper describing the research question, results, conclusions, and reflection. | Q2(22/23); Q4(22/23); Q4(23/24); Q4(24/25) |
| DSAIT 4050: Information Retrieval |
The course provides students basic information retrieval concepts and more advanced techniques for efficient data processing, storage, and querying. Students are also provided with a rich and comprehensive catalog of information search tools that can be exploited in designing and implementing Web and Enterprise search engines. Topics covered include: Information Retrieval Models; Indexing Techniques; Web Search; Recommender Systems; Evaluation of information retrieval systems. | Q3(22/23); Q3(23/24); Q3(24/25) |
| CS 361: Introduction to the Theory of Computation |
Regular languages, finite automata, context-free languages, pushdown automata, Turing machines, decidability, introduction to reducibility and computational complexity. | Fall 2014, Fall 2015, Spring 2016, Summer 2016, Spring 2017, Spring 2018, Fall 2018, Spring 2019, Spring 2020, Fall 2020, Spring 2021, Spring 2022 |
| CS 481: CS Seminar |
Capstone experience designing, implementing, and testing an assigned software artifact. Students report progress via documentation, meetings and demos. Class concludes with a presentation and demonstration of the completed product to students, faculty and project sponsors. Topics include teamwork, communication, ethics, project management, tools, design, verification and validation. | Spring 2017, Fall 2018 |
| CS 437/537: Introduction to Information Retrieval |
An overview of Information Retrieval (IR): fundamental concepts and terminology related to IR; analyzing design methodologies and issues of IR applications; text processing, search, ranking, indexing, classification/clustering, fundamental IR models (e.g., Boolean, Vector Space, and Probabilistic models), and evaluation strategies | Fall 2016, Fall 2019, Fall 2021 |
| CS 637: Advanced Information Retrieval |
An exploration of diverse areas of study related to information retrieval. Topics include query suggestion, question answering, recommendation systems, and (social) web search. Emphasis on exploring state-of-the-art research and future trends via reading assignments and topic presentations. | Spring 2015, Fall 2017, Spring 2020, Spring 2022 |