Seminar and Conference News

PhD scholarship for Australian local students on deep behavior analytics

posted Jan 17, 2019, 3:18 AM by Yanchang Zhao   [ updated Jan 17, 2019, 3:18 AM ]

PhD scholarships are available for talented Australian local students to work on an exciting Australian Research Council discovery grant. The project will invent ground-breaking theories and methods for deep behavior analytics of individuals and groups, natural systems, and artificial systems such as interactions and networks in public services, transport systems, health/medical treatment services, financial and economic systems etc. The candidates must have solid background knowledge in statistics, data science and artificial intelligence (in particular machine learning, data mining and pattern recognition), a master by research qualification, and demonstrated research capabilities (through publications). The candidates will work at the Data Science Lab (www.datasciences.org) at UTS Advanced Analytics Institute, an active team with strong research culture and track record in quality and impact-driven research and engagement with many major local and international partners. The candidates may also be co-supervised by a world-leading investigator in the US. The scholarships will be available from 2019 for three years. Interested candidates are welcome to submit your CV with representative publications and a brief statement of your doctoral research plan to Prof Longbing Cao at LongBing.Cao@uts.edu.au. For inquiries, please contact Prof Cao and information at the Data Science Lab www.datasciences.org.


Additional opportunities for post-doctoral fellowship in data science are welcome.

An R and Data Mining Course

posted Dec 9, 2018, 3:23 PM by Yanchang Zhao   [ updated Dec 9, 2018, 3:23 PM ]

I will run an 8-hour course on R and Data Mining at Black Mountain, CSIRO, Australia on 10 & 13 December 2018.

The course materials, incl. slides, R scripts and datasets, are available at http://www.rdatamining.com/training/course.

Below is outline of the course.

Part I: Monday 10 Dec 2018, 1-5pm

  • R Programming 
    basics of R language and programming, parallel computing, and data import and export
  • Data Exploration and Visualisation
    summary, stats and various charts
  • Regression and Classification
    linear regression and logistic regression, decision trees and random forest
  • Data Clustering
  • k-means clustering, k-medoids clustering, hierarchical clustering and density-based clustering

Part II: Thursday 13 Dec 2018, 1-5pm

  • Time Series Analysis
    time series decomposition, forecasting, classification and clustering
  • Association Rule Mining 
    mining and selecting interesting association rules, redundancy removal, and rule visualisation
  • Text Mining
    text mining, word cloud, topic modelling, and sentiment analysis,
  • Network Analysis and Graph Mining
    graph construction, graph query, centrality measures, and graph visualisation
  • Big Data
    Hadoop, Spark and R

Vacancy of Research Scientist in Data Science

posted Nov 6, 2018, 8:57 PM by Yanchang Zhao   [ updated Nov 6, 2018, 8:58 PM ]

Research Scientist in Data Science - 2 Positions at Data61, CSIRO. 

Application close on 28 November 2018. 


See details at https://jobs.csiro.au/job/Melbourne%2C-VIC-Senior-Research-Scientist-in-Data-Science/493000300/


Seminar: Smart Data Analytics for Traffic Congestion Management

posted Nov 1, 2018, 5:51 PM by Yanchang Zhao   [ updated Nov 1, 2018, 5:51 PM ]

Seminar: Smart Data Analytics for Traffic Congestion Management, 

Speaker: Dr. Adriana-Simona Mihaita, Data61, CSIRO. 

Location: Black Mountain, Canberra, 

Time and Date: 2-4pm Friday 16 Nov

RSVP: https://www.meetup.com/en-AU/CanberraDataSci/events/256024965/

AusDM 2018 Program now available

posted Nov 1, 2018, 5:20 PM by Yanchang Zhao   [ updated Nov 1, 2018, 5:21 PM ]

AusDM 2018 Student Challenge on postcode grouping

posted Sep 17, 2018, 8:16 PM by Yanchang Zhao   [ updated Sep 17, 2018, 8:17 PM ]

AusDM 2018 Student Challenge on postcode grouping. Open to students with Australian universities. See details at http://ausdm18.ausdm.org/student-competition/

CFP: AusDM 2018 - final extension to 17 Aug

posted Aug 2, 2018, 4:04 PM by Yanchang Zhao   [ updated Aug 2, 2018, 4:06 PM ]

The 2018 Australasian Data Mining Conference (AusDM 2018) has extended its submission deadline to 17 August. This is the final chance to get in.

 

The conference proceedings will be published in Springers Communication in Computer and Information Science.

 

Conference URL: http://ausdm18.ausdm.org

AusDM 2018 submission deadline extended to 3 August

posted Jul 16, 2018, 10:35 PM by Yanchang Zhao   [ updated Jul 16, 2018, 10:35 PM ]

The 16th Australasian Data Mining Conference (AusDM 2018)
Bathurst, Australia,
28-30 November 2018 
URL: 
http://ausdm18.ausdm.org/

The Australasian Data Mining Conference has established itself as the premier Australasian meeting for both practitioners and researchers in data mining. It is devoted to the art and science of intelligent analysis of (usually big) data sets for meaningful (and previously unknown) insights. This conference will enable the sharing and learning of research and progress in the local context and new breakthroughs in data mining algorithms and their applications across all industries.

Since AusDM02 the conference has showcased research in data mining, providing a forum for presenting and discussing the latest research and developments. Built on this tradition, AusDM18 will facilitate the cross-disciplinary exchange of ideas, experience and potential research directions. 

This year AusDM is proud to announce that conference proceedings will be published in Springers Communication in Computer and Information Science.


Publication and topics

We are calling for papers, both research and applications, and from both academia and industry, for presentation at the conference. Accepted papers will be published in the AusDM 2018 proceedings by Springer. Some selected papers will be invited for submission with extension in a special edition of a Springer journal. More details are available at our website.


Keynote speakers

Professor Junbin Gao, The University of Sydney
Professor Geoff Webb, Monash University


Important Dates

Paper Submission: extended to 3 August 2018
Authors Notified: Monday 1 October 2018
Camera Ready Submission: Monday 15 October 2018
Preliminary Program Available: Wednesday 31 October 2018
Early Bird Cut-Off Date for Authors: Friday 2 November 2018
Conference Dates: Wednesday 28 - Friday 30 November 2018


Join us on LinkedIn: 
https://www.linkedin.com/groups/4907891

Seminar: Real-Time Analytics and Petabyte-Scale Open Data Science, Canberra, Tuesday 26 June 2018

posted May 28, 2018, 4:47 PM by Yanchang Zhao   [ updated May 28, 2018, 4:47 PM ]

This is a joint event with the Statistical Society of Australia (SSA) Canberra Branch. There will be two talks starting at 5:45pm at the event. Each talk will be of 30m presentation plus 15m Q&A. There will also be pre-talk drinks and nibbles from 5pm to 5:45pm, kindly sponsored by M&T Resources.


RSVP: https://www.meetup.com/CanberraDataSci/events/251057018/

Date: Tuesday 26 June 2018
Venue: ANU campus
Agenda:
5:00-5:45pm Pre-talk drinks and nibbles, Allan Barton Forum, 2nd floor CBE Building, ANU
5:45-6:30pm Talk #1 - Solution for real-time analytics embedded in business process, by Richard Gao, Australian Government
6:30-7:15pm Talk #2 - Machine Learning and analytics using an open data science approach, by Rishu Saxena, Cloudera

Talk #1:

Topic: Solution for real-time analytics embedded in business process - Orchestra of elements to deliver real-time analytics as a critical part of business process
Speaker: Richard Gao, Australian Government
Abstract: The talk will presents three evolution stages of decision-making process: 1) time consuming non-automatic decision making process, including data collection, analysis, report and decision making, 2) automatic decision making process as part of general business process (e.g. Operational Decision Manager), and 3) modern data science-driven business process, including machine learning algorithm development and real-time algorithm deployment systems as new feature.
Bio: Mr. Richard Gao, is a lead data scientist in the Commonwealth Australia, previously worked as a data analyst and statistician across multiple Commonwealth Departments for over 10 years. Before that, he worked as an R&D manager with Huawei Technologies and Math teacher with a local Chinese university. He holds Master of Applied Statistics, MBA and Bachelor of Applied Mathematics.

Talk #2:

Topic: Machine Learning and analytics using an open data science approach
Speaker: Rishu Saxena, Cloudera
Abstract: Data Science in an enterprise environment with strong security restrictions, mean that leveraging the latest publicly available algorithms, libraries and approaches is difficult. In this talk we will propose an approach to leverage petabyte-scale open data science, while still maintaining security and resource controls.
Bio: Rishu is System Engineer with Cloudera focusing on helping customers to leverage machine learning. Rishu has previously worked with public, research and private sector organisations to help define the vision, strategy, technical solutions and delivery approach for big data hubs, advanced analytics and visualisation. Rishu is currently studying a Masters of Data Science at Sydney University.

Big Data Innovation Summit & Machine Learning Innovation Summit, San Francisco

posted Mar 15, 2018, 3:21 PM by Yanchang Zhao   [ updated Mar 15, 2018, 3:22 PM ]

Understand how you can articulate your current skills/responsibilities and take the career path that you want. Read this article from our expert Hugh Williams, ML Data Science Manager at Uber: http://bit.ly/2oLOued

 

Would you like to learn more about data, NLP, AI, Deep Learning?

 

Join two San Francisco events:

 

* Big Data Innovation Summit, April 12 & 13http://bit.ly/2oKPkYE 

> Visualize, explore data and generate insights to make better decisions

> Maximize your delivery of valuable insights with an effective Data Intelligence program

> Leverage AWS components to build and test multiple attribution models at scale and find AWS patterns

 

 

* Machine Learning Innovation Summit, May 9 & 10http://bit.ly/2HV92JX

> Master how advanced analytics can help you make better decisions on promotions

> Discover how ML can highlight the most relevant products and increase customer satisfaction

> Learn how ML can provide you with real-time recommendations using resources efficiently and operating on a massive scale

 

 

Enjoy an exclusive $200 off all two-day passes with the code RDM200 when you register! For more information on the events and group rates, please contact Lewis: Lewis@theiegroup.com  

 

PS: Learn more about NLP and how Uber is using it. Know how to adopt ML by reading this 

interview with Hugh Williams, ML Data Science Manager at Uber: http://bit.ly/2IsBlj8

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