Projects per year
Personal profile
Biography
Ingrid works in the Faculty of Information Technology at Monash University as a Professor.
Research interests
- Natural language processing
- Discourse planning
- Spoken language understanding
- User modeling
- Plan recognition
Monash teaching commitment
Professor Ingrid Zukerman has experience as the Chief Examiner for the following units in the Faculty of IT:
- FIT3080 Intelligent systems
- FIT4009 Advanced topics in intelligent systems
- FIT5047 Intelligent systems
- FIT9005 Computer architecture and networks
Ingrid has experience as the Lecturer for the following units in the Faculty of IT:
- FIT3036 Computer science project
- FIT3080 Intelligent systems
- FIT4009 Advanced topics in intelligent systems
- FIT5047 Intelligent systems
- FIT9005 Computer architecture and networks
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
Computer Science, Doctor of Philosophy, University of California Los Angeles
Award Date: 20 Jun 1986
Operations Research, Master of Science, Technion - Israel Institute of Technology
Award Date: 23 Sep 1979
Industrial Engineering and Management, Bachelor of Science, Technion - Israel Institute of Technology
Award Date: 16 Jun 1976
Research area keywords
- Artificial intelligence
- Discourse Planning
- Multi-Media Interfaces
- Natural Language Processing
- Plan recognition
- User Modelling
Network
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Accessible Data Exploration and Analysis for Blind People
Marriott, K., Butler, M., Zukerman, I., Qu, L. & Lee, B.
Australian Research Council (ARC)
28/02/23 → 27/02/27
Project: Research
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Improving human reasoning with causal Bayes networks: a multimodal approach
Nicholson, A., Wybrow, M., Zukerman, I., Lagnado, D. & Hahn, U.
1/12/20 → 1/06/24
Project: Research
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Explaining the outcomes of complex models
Zukerman, I., Haffari, R. & Reiter, E.
1/07/19 → 31/10/22
Project: Research
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Explaining the outcomes of complex computational models (Explainable AI)
Situ, X., Zukerman, I., Haffari, R., Paris, C. & Xu, C.
1/07/18 → 18/03/22
Project: Research
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BARD: Bayesian ARgumentation via Delphi
Korb, K., Nicholson, A., Nyberg, E., Morris, S., Bolger, F., Rowe, G., Wright, G., Hahn, U., Lagnado, D., Fenton, N., Neil, M., Zukerman, I., Wybrow, M. & Lewis, B.
3/01/17 → 2/12/18
Project: Research
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Influence of device performance and agent advice on user trust and behaviour in a care-taking scenario
Zukerman, I., Partovi, A. & Hohwy, J., 30 Mar 2023, (Accepted/In press) In: User Modeling and User-Adapted Interaction. 49 p.Research output: Contribution to journal › Article › Research › peer-review
Open Access -
BARD: a structured technique for group elicitation of Bayesian networks to support analytic reasoning
Nyberg, E. P., Nicholson, A. E., Korb, K. B., Wybrow, M., Zukerman, I., Mascaro, S., Thakur, S., Oshni Alvandi, A., Riley, J., Pearson, R., Morris, S., Herrmann, M., Azad, A. K. M., Bolger, F., Hahn, U. & Lagnado, D., Jun 2022, In: Risk Analysis. 42, 6, p. 1155-1178 24 p.Research output: Contribution to journal › Article › Research › peer-review
Open AccessFile5 Citations (Scopus) -
Inductive biases for low data VQA: a data augmentation approach
Askarian, N., Abbasnejad, E., Zukerman, I., Buntine, W. & Haffari, G., 2022, Proceedings - 2022 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2022. Farrell, R., Zhao, C., Anand, S. & Souvenir, R. (eds.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 231-240 10 p. (Proceedings - 2022 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2022).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
1 Citation (Scopus) -
Curriculum learning effectively improves low data VQA
Askarian, N., Abbasnejad, E., Zukerman, I., Buntine, W. & Haffari, G., 2021, ALTA 2021: Proceedings of the 19th Workshop of the Australasian Language Technology Association. Rahimi, A., Lane, W. & Zuccon, G. (eds.). Stroudsburg PA USA: Association for Computational Linguistics (ACL), p. 22-33 12 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research
Open AccessFile -
Explaining Decision-Tree predictions by addressing potential conflicts between predictions and plausible expectations
Maruf, S., Zukerman, I., Reiter, E. & Haffari, R., 2021, The 14th International Conference on Natural Language Generation: Proceedings of the Conference 20-24. M. Howcroft, D. (ed.). Stroudsburg PA USA: Association for Computational Linguistics (ACL), p. 114–127 14 p. 12Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open AccessFile