I am honoured to have been recognised in The Australian's 2023 Research Magazine as Australia's top Bioinformatics and Computational Biology researcher. This is the third year in a row that The Australian has recognised my research in this way. This is a great recognition of the fantastic research of my bioinformatics collaborators, most especially Jiangning Song.
Category: Uncategorized
One of Australia’s Top 250 Researchers!
I am honoured to have been recognised by The Australian as Australia's leading Bioinformatics and Computational Biology researcher and one of Australia's top 250 researchers.
Mollie Holman Medal for Chang Wei Tan
I am very proud to have had the honour of supervising Chang Wei Tan's PhD. Chang Wei is the second of my many exceptional students to win this Monash University Award for best PhD.
Mollie Holman Medal for Jiangning Song
I am very proud to have had the honour of supervising Jiangning Song. His exceptional PhD has just been recognised with the 2018 Mollie Holman Medal.
Enhanced lower bound for Dynamic Time Warping
Our enhanced lower bound for Dynamic Time Warping is tighter than the widely used LB Keogh without any additional computational burden. This picture shows Bart Goethals as he realises the impact it is bound to have. For more details see our SDM-19 paper here.
Tutorial on Statistically Sound Pattern Discovery
There is much to be said for presenting keynotes at universities with viticulture degrees!
Thank you @AusDMConf and @CharlesStuartUniversity for the opportunity to present my group’s work on Concept Drift https://i.giwebb.com/research/concept-drift/. Thanks also for the lovely CSU wines. @MonashUni @@MonashInfoTech
Extremely Fast Decision Tree
We introduce a novel incremental decision tree learning algorithm, Hoeffding Anytime Tree, that is statistically more efficient than the current state-of-the-art, Hoeffding Tree. We demonstrate that an implementation of Hoeffding Anytime Tree–-"Extremely Fast Decision Tree", a minor modification to the MOA implementation of Hoeffding Tree–-obtains significantly superior prequential accuracy on most of the largest classification datasets from the UCI repository. Hoeffding Anytime Tree produces the asymptotic batch tree in the limit, is naturally resilient to concept drift, and can be used as a higher accuracy replacement for Hoeffding Tree in most scenarios, at a small additional computational cost.
Looking for Professor to lead Data Science research group
We are looking for a leading researcher to lead a group of data science faculty. This is a bit like a Departmental Chair position.
Details here.
Join us for Living with AI
The Living with AI discussion series will feature conversations about social and ethical implications of artificial intelligence. Join us for the first of these conversations, featuring AI expert Terry Cailli addressing the question "Can Computers Behave Ethically?"
Date and Time
Wed. 8 August 2018
5:30 pm – 7:00 pm AEST
Location
Deakin Downtown
Collins Square, Tower 2
Level 12, 727 Collins Street
Docklands, VIC 3008
Tickets
Click here.
SDM Best Research Paper Award
We are very honoured to have received the 2018 SIAM International Conference on Data Mining (SDM-18) Best Research Paper Award for
Efficient search of the best warping window for Dynamic Time Warping.
Tan, C. W., Herrmann, M., Forestier, G., Webb, G. I., & Petitjean, F.
Proceedings of the 2018 SIAM International Conference on Data Mining, 2018.
This paper presents algorithms that allow a critical hyper-parameter for time series classification, the warping window, to be efficiently tuned.
The paper can be downladed here: i.giwebb.com/wp-content/papercite-data/pdf/TanEtAl18.pdf.
The code can be downloaded here: https://t.co/acY3A3SYyQ.
Great Data Science Faculty Positions
We have three continuing (Australia's version of tenured) faculty positions in data science. Join a strong data science group in a top-100 university in the world's most livable city. Closing date 19 November 2017. More details including application process here.