STAFF PROFILE
Professor Lawrence Cavedon
Lawrence Cavedon is a Professor in the School of Computing Technologies, and the Associate Dean and Discipline of Data Science.
His research interests include spoken dialogue and speech interfaces, biomedical and health analytics, and Artificial Intelligence in general.Professor Lawrence Cavedon's career has spanned academia and the IT industry as both researcher and software engineer, leaving him with a strong interest in industry-focused problems. Much of his recent and current research projects are performed in collaboration with industry and domain partners, including SEEK, Elsevier, IBM Research, Real Thing Entertainment, and health organisations Alfred Health, Melbourne Health, Peter MacCallum Cancer Centre, and Telstra Health.
While at Stanford, he collaborated on funded projects with NASA, Bosch Corp, VW America, and Boeing. He has also led software product teams at Verticalnet Inc in Silicon Valley.
Lawrence is the Discipline Head for Computer Science and IT.
His recent teaching activities have been focused on advanced Software Engineering courses, such as Software Engineering: Process and Tools (COSC2299) and Systems Architecture (ISYS1088/89). In 2020, he is teaching a new course: The Data Science Professional.
Lawrence has been Chief Investigator on 6 past or current ARC Linkage grants, including 2 as Lead CI, as well as other grants totaling approx. $3million since 2014. He is also a CI on a new ARC Industry Transformational Training Centre in conjunction with UniMelb and IBM Research, on Cognitive Computing for Medical Technologies.
See Lawrence's Google scholar page for a list of his publications.
- Ph.D. Cognitive Science, The University of Edinburgh (UK)
- M. Sc. Computer Science, The University of Melbourne
- B. Sc. (Honours), Computer Science, The University of Melbourne
Previous appointments
- 2005-2014: NICTA (National ICT Australia), Victoria Research Lab
- 2002-2005: Stanford University, Center for the Study of Language and Information
- 2000-2002: Verticalnet Inc. (California), Advanced Technologies Group
- 1987-1990: Australian Artificial Intelligence Institute
Lawrence has worked in the tech industry in both Australia and Silicon Valley in California.
In Silicon Valley, he was a Scientist and a Lead Engineer in the Advanced Technologies Group at Verticalnet Inc., the first Business-to-Business technology company to IPO. In Australia, he worked for the Australian Artificial Intelligence Institute, a contract R&D organisation applying AI techniques to industry problems.
Lawrence also collaborates extensively with industry in his research. At NICTA (National ICT Australia, Australia's Centre for ICT Research Excellence), he led projects on the topic of biomedical and health analytics, in collaboration with Alfred Health, Melbourne Health, Barwon Health and the Peter MacCallum Cancer Centre. At Stanford University, he collaborated closely on joint projects with Bosch Corp, VW America, Boeing, and NASA.
At RMIT, he has research projects with SEEK, IBM Research, Elsevier, Telstra Health, and other companies and organisations.
He also likes to engage industry in his teaching and regularly organises presenters from large corporations (e.g., IBM, Amazon Web Services), mid-sized innovative technology companies (Redbubble, Zendesk), and startups.
Commercial innovation
- Led team that developed first commercial Semantic Web Services platform
- NSW Engineering Excellence Award (R&D) for Thinking Head project
- Stanford CSLI dialogue system commercially licensed by major corporations
Patents
- F. Weng, L. Cavedon, et al: Method and system for interactive conversational dialogue for cognitively overloaded device users; US Patent 7,716,056.
- D. Mirkovic, L. Cavedon: Dialogue management using scripts; US Patent 8,041,570
- D. Mirkovic, L. Cavedon, et al: Dialogue management using scripts and combined confidence scores; US Patent 7,904,297.
- H. Cheng, L. Cavedon, et al: Method and system for adaptive navigation using a driver's route knowledge; US Patent 7,424,363
- Al Bahem, A.,Spina, D.,Scholer, F.,Cavedon, L. (2022). Component-based Analysis of Dynamic Search Performance In: ACM Transactions on Information Systems, 40, 1 - 47
- Sarwar, T.,Seifollahi, S.,Chan, J.,Zhang, X.,Aksakalli, V.,Hudson, I.,Verspoor, K.,Cavedon, L. (2022). The Secondary Use of Electronic Health Records for Data Mining: Data Characteristics and Challenges In: ACM Computing Surveys, 55, 1 - 36
- Schofield, P.,Gough, K.,Frydenberg, M.,Cavedon, L., et al, . (2021). Navigate: a study protocol for a randomised controlled trial of an online treatment decision aid for men with low-risk prostate cancer and their partners In: Trials, 22, 1 - 12
- He, E.,Albahem, A.,Cavedon, L.,Verspoor, K., et al, . (2021). ChEMU 2020: Natural Language Processing Methods Are Effective for Information Extraction From Chemical Patents In: Frontiers in Research Metrics and Analytics, 6, 1 - 28
- Vukovic, M.,Cavedon, L.,Thangarajah, J.,Rodriguez, S. (2021). Performance degrades less under increased workload with the addition of speech control in a dynamic environment In: Applied Ergonomics, 96, 1 - 12
- Trippas, J.,Spina, D.,Sanderson, M.,Cavedon, L. (2021). Accessing Media Via an Audio-only Communication Channel: A Log Analysis In: Proceedings of the 3rd Conference on Conversational User Interfaces (CUI 2021), Bilbao, Spain, 27-29 July 2021
- Steiner, M.,Spina, D.,Scholer, F.,Cavedon, L. (2021). Crowdsourcing Backstories for Complex Task-Based Search In: Proceedings of the 25th Australasian Document Computing Symposium (ADCS 2021), Virtual Event, Australia, 9 December 2021
- Fayek, H.,Cavedon, L.,Wu, H. (2020). Progressive learning: A deep learning framework for continual learning In: Neural Networks, 128, 345 - 357
- He, E.,Nguyen, D.,Akhondi, S.,Albahem, A.,Cavedon, L.,Verspoor, K., et al, . (2020). Overview of ChEMU 2020: Named Entity Recognition and Event Extraction of Chemical Reactions from Patents In: Proceedings of the 11th International Conference of the Cross-Language Evaluation Forum for European Languages (CLEF 2020), Thessaloniki, Greece, 22–25 September 2020
- He, J.,Nguyen, D.,Akhondi, S.,Druckenbrodt, C.,Albahem, A.,Cavedon, L.,Verspoor, C., et al, . (2020). An extended overview of the CLEF 2020 ChEMU Lab : information extraction of chemical reactions from patents In: Proceedings of the 11th Conference and Labs of the Evaluation Forum (CLEF 2020), Virtual Event, 22/09/2020 - 25/09/2020
- 53. Precinct level (or city level) energy use prediction using building data and other data sources. Funded by: Centre for New Energy Technologies (C4NET) from (2021 to 2023)
- Training intelligent virtual agents using human interaction data (phase 2). Funded by: DIIS - Innovations Connections - Competitive from (2020 to 2020)
- Real-time clinical decision support - Natural Language Processing Supporting Clinical Reasoning (Administered by University of Melbourne). Funded by: ARC Industrial Transformation Training Centre via other University Grant 2017 from (2020 to 2021)
- Training intelligent virtual agents using human interaction data. Funded by: DIIS - Innovations Connections - Competitive from (2019 to 2020)
- Biochemical text mining for advanced chemical and pharmaceutical knowledge (Administered by The University of Melbourne). Funded by: ARC Linkage Project Grant 2016 via other University from (2018 to 2022)
2 PhD Current Supervisions7 PhD Completions and 1 Masters by Research Completions