Teaching
Fall 2024
I will not be teaching in Fall 2024.
Past Semesters
COMPSCI 546: Applied Information Retrieval
Offered: Spring 2024
COMPSCI 546 is a graduate level course intended to cover information retrieval and other information processing activities, from an applied perspective. There will be multiple programming projects, as well as short answer homeworks. It provides a richer technical follow on to COMPSCI 446 (Search Engines), for undergraduates interested in a deeper understanding of the technologies. It also provides a strong basis for continuing on with COMPSCI 646 (Information Retrieval), for those graduate students who are interested in a more complete theoretical coverage of the area. Topics will include: search engine construction (document acquisition, processing, indexing, and querying); learning to rank; neural information retrieval; information retrieval system performance evaluation; classification and clustering; other machine learning information processing tasks; and many more.
COMPSCI 791U: Advanced Topics in Information Retrieval (Seminar)
Co-Instructors: James Allan and Hamed Zamani
Offered: Spring 2024
COMPSCI 791U is a seminar in which students will read, present, and discuss research papers on recent and advanced topics in Information Retrieval (IR). Students are expected to lead one or more discussions throughout the semester. This seminar will cover the following main topics:
- Retrieval-Enhanced Machine Learning
- Large Language Models for IR
- Generative Information Retrieval
- Multi-Modal Information Retrieval
- Information Retrieval for the Common Good
COMPSCI 646: Information Retrieval
Offered: Fall 2023
COMPSCI 646 is a graduate-level course in Information Retrieval, the science and engineering of indexing, organizing, searching, and making sense of unstructured or mostly unstructured information, particularly text. The class focuses primarily on the underlying models used for effective search and organization, but includes some discussion of efficiency concerns. The course also covers current research problems and methodologies in the field of Information Retrieval.
COMPSCI 646: Information Retrieval
Offered: Fall 2022
COMPSCI 646 is a graduate-level course in Information Retrieval, the science and engineering of indexing, organizing, searching, and making sense of unstructured or mostly unstructured information, particularly text. The class focuses primarily on the underlying models used for effective search and organization, but includes some discussion of efficiency concerns. The course also covers current research problems and methodologies in the field of Information Retrieval.
COMPSCI 546: Applied Information Retrieval
Offered: Spring 2022
COMPSCI 546 is a graduate level course intended to cover information retrieval and other information processing activities, from an applied perspective. There will be multiple programming projects, as well as short answer homeworks. It provides a richer technical follow on to COMPSCI 446 (Search Engines), for undergraduates interested in a deeper understanding of the technologies. It also provides a strong basis for continuing on with COMPSCI 646 (Information Retrieval), for those graduate students who are interested in a more complete theoretical coverage of the area. Topics will include: search engine construction (document acquisition, processing, indexing, and querying); learning to rank; neural information retrieval; information retrieval system performance evaluation; classification and clustering; other machine learning information processing tasks; and many more.
COMPSCI 692F: Conversational Artificial Intelligence (Seminar)
Offered: Spring 2022
Conversational AI is a graduate level seminar intended to cover recent research progress on chat bots, task-oriented dialogue systems, conversational search and recommender systems, conversational question answering, multi-modal conversational systems, and related topics. Students are expected to read, present, and discuss research papers related to conversational AI systems. They will also get familiar with state-of-the-art tools and techniques for developing conversational systems.
COMPSCI 646: Information Retrieval
Offered: Fall 2021
COMPSCI 646 is a graduate-level course in Information Retrieval, the science and engineering of indexing, organizing, searching, and making sense of unstructured or mostly unstructured information, particularly text. The class focuses primarily on the underlying models used for effective search and organization, but includes some discussion of efficiency concerns. The course also covers current research problems and methodologies in the field of Information Retrieval.
COMPSCI 546: Applied Information Retrieval
Offered: Spring 2021
COMPSCI 546 is a graduate level course intended to cover information retrieval and other information processing activities, from an applied perspective. There will be multiple programming projects, as well as short answer homeworks. It provides a richer technical follow on to COMPSCI 446 (Search Engines), for undergraduates interested in a deeper understanding of the technologies. It also provides a strong basis for continuing on with COMPSCI 646 (Information Retrieval), for those graduate students who are interested in a more complete theoretical coverage of the area. Topics will include: search engine construction (document acquisition, processing, indexing, and querying); learning to rank; information retrieval system performance evaluation; classification and clustering; other machine learning information processing tasks; and many more.
COMPSCI 646: Information Retrieval
Offered: Fall 2018
COMPSCI 646 is a graduate-level course in Information Retrieval, the science and engineering of indexing, organizing, searching, and making sense of unstructured or mostly unstructured information, particularly text. The class focuses primarily on the underlying models used for effective search and organization, but includes some discussion of efficiency concerns. The course also covers current research problems and methodologies in the field of Information Retrieval.