• The University of Western Australia (M002), 35 Stirling Highway,

    6009 Perth

    Australia

  • 708 Citations
  • 15 h-Index
1985 …2023
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Personal profile

Roles and responsibilities

Head of School

Biography

Mark Reynolds obtained his Bachelors degree at The University of Western Australia (UWA) with honours in Pure Mathematics and Statistics, his PhD at Imperial College London (IC) in Computing and a Diploma in Education from UWA. After lecturing at Kings College London, he moved back to Perth and then to UWA as an Associate Professor. He is currently the head of the School of Physics, Mathematics and Computing. His research interests include AI, Machine Learning, Logic, Formal methods in Software Engineering and Optimisation.

Funding overview

Over $10M in funding over the last ten years for a variety of industry, ARC and CRC funded projects. Projects include the ARC Training Centre for Transforming Maintenance through Data Science, investigations of the use of AI and Video Analytics in Intelligent Transport Systems, Projects in the use of logic and formal methods for ensuring correctness of complex systems.

Teaching overview

 

Developed and taught courses in Software Engineering, Computational Modelling, Machine Learning, Human-Computer Interaction, Logic and Computation, Computational Geometry and Introductory Programming.

24 PhD Students (12 completed), 30 Masters students and 10 honour students

Keywords

  • Artificial intelligence
  • Automated reasoning
  • Formal methods in software
  • Formal specification and verification of concurrent systems
  • Logic
  • Logical foundations of computer science
  • Modal/temporal logic
  • Reasoning about agent interaction and collaboration
  • Software engineering
  • Verification of systems

Fingerprint Dive into the research topics where Mark Reynolds is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 1 Similar Profiles
Temporal logic Engineering & Materials Science
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Model checking Engineering & Materials Science
Electric power distribution Engineering & Materials Science
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Trajectories Engineering & Materials Science
Genetic algorithms Engineering & Materials Science
Theorem proving Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 1985 2019

Aleatoric dynamic epistemic logic for learning agents

French, T., Gozzard, A. & Reynolds, M., 1 Jan 2019, PRICAI 2019: Trends in Artificial Intelligence - 16th Pacific Rim International Conference on Artificial Intelligence, Proceedings. Nayak, A. C. & Sharma, A. (eds.). Springer-Verlag Berlin, p. 433-445 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11670 LNAI).

Research output: Chapter in Book/Conference paperConference paper

Epistemic Logic
Dynamic Logic
Proposition
Probability distributions
Probability Distribution
1 Citation (Scopus)

A modal aleatoric calculus for probabilistic reasoning

Gozzard, A., French, T. & Reynolds, M., 2019, Logic and its applications : 8th Indian Conference, ICLA 2019, Delhi, India, March 1-5, 2019, Proceedings. Aquil Khan, M. & Manuel, A. (eds.). Berlin: Springer, p. 52-63

Research output: Chapter in Book/Conference paperConference paper

Probabilistic Reasoning
Calculi
Possible Worlds
Sound
Multi-agent Systems

An Adaptive-Phasor Approach to PMU Measurement Rectification for LFOD Enhancement

Chau, T. K., Yu, S., Fernando, T. L., Iu, H. H. C., Small, M. & Reynolds, M., 1 Sep 2019, In : IEEE Transactions on Power Systems. 34, 5, p. 3941-3950 10 p., 8674594.

Research output: Contribution to journalArticle

Phasor measurement units
Damping
Recovery
Voltage regulators
Synchronous generators

A Novel Decentralized LTL Monitoring Framework Using Formula Progression Table

Bataineh, O., Rosenblum, D. S. & Reynolds, M., 1 Jan 2019, Model Checking Software - 26th International Symposium, SPIN 2019, Proceedings. Biondi, F., Given-Wilson, T. & Legay, A. (eds.). Springer, p. 38-55 18 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11636 LNCS).

Research output: Chapter in Book/Conference paperConference paper

Linear Temporal Logic
Temporal logic
Progression
Decentralized
Table
1 Citation (Scopus)

A quest for a one-size-fits-all neural network: Early prediction of students at risk in online courses

Monllao Olive, D., Huynh, D., Reynolds, M., Dougiamas, M. & Wiese, D., 15 Apr 2019, In : IEEE Transactions on Learning Technologies. p. 171-183 13 p.

Research output: Contribution to journalArticle

neural network
Students
Neural networks
student
learning

Projects 2004 2023