I work in the
School of Computing
I am also an Adjunct Professor in the Mathematics and Computer Science Department of the Royal Military College.
My blog on adversarial analytics
Tips on Adversarial Analytics
RIP Ralph Stanton, 1923-2010, my Ph.D. supervisor, details here.
"Next year the number of [US] federally mandated categories of illness and injury for which hospitals may claim reimbursement will rise from 18,000 to 140,000. There are nine codes relating to injuries caused by parrots, and three relating to burns from flaming water-skis" Economist, Feb 18th 2012.
We haven't the money, so we've got to think -- Ernest Rutherford.
Latent structure is master of visible structure -- Heraclitus c500 B.C, evidently the father of data analytics.
The Feynman Problem Solving Algorithm:
1) Write down the problem.
2) Think very hard.
3) Write down the solution.
(In my experience, in North America Step 2 tends to be skipped. In Australia, curiously, it's often Step 3.)
My latest book "Social Networks with Rich Edge Semantics", with Quan Zheng, is available.
My book, Understanding High-Dimensional Spaces has been published by Springer. (Print, Online)
I was awarded the 2009 IEEE Intelligent Transportation Systems Society and IEEE Systems, Man and Cybernetics Society Technical Committee on Homeland Security Technical Achievement Award for outstanding and sustained technical contributions to the field of Intelligence and Security Informatics.
My book: Knowledge Discovery for Counterterrorism and Law Enforcement is available from Taylor and Francis and Amazon
My research is focused on adversarial knowledge discovery, building inductive models from data in settings where the interests of modellers and those being modelled are not aligned. This includes counterterrorism, law enforcement,and fraud; but also increasingly areas such as customer relationship modelling. I work with some TLAs and even some FLAs.
Although the datasets I work with tend to be intricate rather than large, some of what I do could be called "Big Data analytics".
I am on the Steering Committee of the IEEE International Conference on Intelligence and Security Informatics, 2007-- .
I am on the Steering Committee of the SIAM International Conference on Data Mining, 2007-- .
I am on the Program Committees of all of the usual data mining conferences and workshops, and also those related to security informatics.
I am an Associate Editor or on the Editorial Board of IEEE Intelligent Systems, IEEE Transactions on Computational Social Systems, Computational Intelligence, Journal of Universal Computer Science, Computational and Mathematical Organizational Theory, and Springer Security Informatics.
I supervise theses in topics in adversarial knowledge discovery, focusing on textual data and graph/relational data. I work with colleagues in Politics (radicalization, borders, political speech), Business (financial fraud), and Psychology (deception) so there are possibilities in interdisciplinary research in these directions as well.
My funding levels do not allow me to supervise international students unless they have funding from their own countries; this applies to summer students, graduate students, and postdocs. I am happy to consider students applying via CALDO or the Saudi Bureau.
My current graduate students:
Some of my recent graduate students:
Mind mapping, a nice way to organise material when you don't already know how it fits together. It's useful for preparing drafts of theses and papers.
Talking about your research.
Teaching and Learning
In 2020 I am teaching:
This course is about half students taking it as an elective, and half taking it as the first course of the data analytics certificate.
About a third of the students are from the sciences, about a third from engineering, and a third from commerce.
A course from the security focus for undergrads, and a core course in the NSERC CREATE cybersecurity program for grads.
I also supervise students in CISC499.
Here is some material on effective learning:
I am interested in hypermedia-based education.
Here are some of the interesting pathways via doctoral supervisors (there's more than one because some people had two supervisors; for example, Brauer was supervised by both Schur and Schmidt, and Dirichlet was supervised jointly by Poisson and Fourier, who were both students of Lagrange):
Skillicorn - Stanton - Brauer - Schur - Frobenius - Weierstrass - Guderman - Gauss
Skillicorn - Stanton - Brauer - Schmidt - Hilbert - Lindemann - Klein - Lipschitz - Dirichlet - Poisson/Fourier - Lagrange - Euler - Bernoulli
Erdos number 3: Skillicorn - Seberry - Szekeres - Erdos
Up to School of Computing
Up to Queen's University