- I no longer have an office phone.
Use email, or if very timely, contact our Admin at 780 492-4828.
- To understand the difference between
Association Studies (common in biostatistics)
Prediction Studies (common in machine learning),
- Quoted in Toronto Star (9 May 2016):
artificial intelligence could transform the medical world
- PhD student, Junfeng Wen, awarded prestiguous AI-TF Fellowship, from 2016!
- Quoted in Faculty of Science news (1 Apr 2016):
Statisticians step up to aid neurological health research
- HQP Accomplishments (Dec 2015)
Junfeng Wen: selected as a runner-up for this year's CS department's ``Early
Achievement Award (MSc) 2015''
- Siamak Ravansbakhsh: selected as a runner-up to this year's CS
department's ``Outstanding Thesis Award (PhD) 2015''
- Felicity Allen: nominated for Best Thesis prize (PhD)
- Mina Gheiratmand: awarded a prestigious AIHS Fellowship!
Over 50 teams, from around the world, competed in the
Prostate Cancer DREAM
to predict the survival and toxicity of docetaxel treatment in patients with
metastatic castrate resistant prostate cancer.
Our team, PC LEARN, tied for 1st in one of the 3 subchallenges
-- see here.
Our recently-launched "Computational Psychiatry" direction was recently
presented on Global News (14 Oct 2015); see here.
Our fMRI project is included as an example of UofA's collaboration with IBM
in news release.
- Our team, led by PhD student Siamak Ravansbakhsh, developed the
for automatically identifying and quantifying metabolites using 1D 1H NMR spectra of
ultra-filtered plasma, serum or cerebrospinal fluid.
Our article is described on
and elsewhere (May,June 2015).
- PhD student Siamak Ravansbakhsh won a Best Thesis Prize (2015)
- PhD student Felicity Allen's CFM-ID system won the
CASMI [Critical Assessment of Small Molecule Identification]
competition (finding the chemical structure of an ESI-MS/MS spectrum)
- Press coverage of MITACS
- Press coverage of Accurately Predicting Estrogen Receptor Status
and H. Khosravi,
The IMAP Hybrid Method for Learning Gaussian Bayes Nets"
Best Paper Prize
2010 Canadian Conference on Artificial Intelligence.
Annual Professorship, 2007.
- Fellow of
(Association for the Advancement of
Artificial Intelligence), 2007
- Faculty Research Award, UofA CS (March 2007)
(to AICML) for
"Outstanding Leadership in Technology",
Int'l Conf. on Machine Learning (ICML'06)
Learning Coordinate Classifiers"
"Distinguished Paper" award
Int'l Conf. on Machine Learning (ICML'04)
"Learning a Model of a Web User's Interests"
2003 James Chen Best
Student Paper Award at
- J.Cheng and R. Greiner,
"Learning Bayesian Belief Network Classifiers: Algorithms and System"
was RunnerUp for Best Paper,
Fourteenth Canadian Conference on Artificial Intelligence (CSCSI'01)
I am interested in building algorithms that learn from experience, to be able to
perform their tasks better.
Some of my work has
These systems have been successfully used to address
a number of real-world challenges.
- an application pull
-- i.e., is motivated by very specific tasks;
a technology push -- typically extending standard learning algorithms and analyses, to produce more robust and more effective learning systems
For an overview of some medical application for machine learning, see the
Thought for the day:
First things first; second things never.
I plan to update this daily... but that is not the highest