Seminar and Conference News

Call for Participation: Big Data Summit 2017, Melbourne, 20-22 August

posted Jul 9, 2017, 8:31 PM by Yanchang Zhao   [ updated Jul 9, 2017, 8:31 PM ]

Call for Participation

Big Data Summit 2017

Co-located with IJCAI 2017

20-22 August 2017, Melbourne

 

Website: http://2017.bigdatasummit.co

Email: bds2017@bigdatasummit.co

 

This three-day event provides a unique, independent, cross-domain and non-commercial view for the advances, future, best practice and policies for artificial intelligence and data science-driven research, innovation, economy and society.

 

Link for and More Information about Online Registration   

http://203.170.84.89/~idawis33/wordpress/?page_id=990

 

20 Aug: AI/Data science Discipline Course

Discipline lecture series about the advances and future directions of major AI/data science areas, to be delivered by world leaders:

-       Mathematical modeling & bitcoin blockchain

Prof Peter Taylor, ARC Laureate Fello

University of Melbourne, Australia

-       Computer vision meets machine learning

Prof Dacheng Tao, ARC Laureate Fellow, IEEE Fellow

University of Sydney, Australia

-       Knowledge discovery & social analytics

      Prof Joao Gama, ACM Distinguish Speaker

University of Porto Porto, Portugal

-       Advances in machine learning

      Prof Qiang Yang, IEEE/AAAI Fellow, Head of Department

Hong Kong University of Sci & Tech

-       Advances in big graph/data processing

      Prof Xuemin Lin, IEEE Fellow

Univ. New South Wales, Australia

-       Advances in Internet of Things/Cloud computing

      Prof Michael Sheng, Head of Department, ARC Future Fellow

Macquarie University, Australia

-       Ethics in artificial intelligence

      Prof Toby Walsh, Fellow of Australian Academy of Science, Data61

UNSW, Australia

 

21 Aug: AI/Data science Big Data Forum

Keynote and invited speeches by industry, government and research leaders, plus two exciting panels:

-       Keynote speech

            Dr Usama Fayyad, ACM/IEEE Fellow, CEO, Open Insights

-       Invited distinguished speakers

            Prof James Bailey, Melbourne University

            Dr Paul Beinat, Director, Neuronworks

            Dr Fang Chen, Group Leader, Data61 | CSIRO

            Dr Frederic R Clarke, Director, Australian Bureau of Statistics

            Dr Warwick Graco, ATO

            Dr Kyusik Kim, Director, IP Australia

            Dr Dickson Lukose, Chief Data Scientist, GCS Agile

            Dr Paul Rybicki, Head of TV and Content, Optus

            Dr Amy Shi-nash, Head of Data Science, Commonwealth Bank of Australia

            Prof Yun Yang, Swinburne University of Technology

-       Panel: Data Science: Scientific Revolution?

-       Panel: Data/Intelligence: New Economy Engine?

            Moderator: Dr Warwick Graco, ATO

 

 22 Aug: AI/Data science Executive Workshop

Global best practice and real-life enterprise analytics case studies for data and business executives and managers to make informed and smarter decisions:

            Dr Usama Fayyad, CEO, Open Insights

            Prof Geoff Webb, Monash University

            Prof Longbing Cao, University of Tech Sydney

            Dr Paul Beinat, Director, Neuronworks

            

Seminar: End-to-end development and deployment of data science models with IBM Watson Data Platform, Canberra, Thursday 27 July 2017

posted Jul 2, 2017, 4:44 PM by Yanchang Zhao   [ updated Jul 2, 2017, 4:46 PM ]

Topic: End-to-end development and deployment of data science models with IBM Watson Data Platform 
Speakers: Ross Farrelly and Stuart Maclean, IBM 
Date and Time: 4:00-6:00pm Thursday 27 July 2017. Food and drinks will start at 4:00pm and talk will start at 4:30pm.  
Location: Canberra 
RSVP: https://www.meetup.com/CanberraDataSci/events/240649078/ 
Acknowledgement: Thanks to IBM for sponsoring venue, food and drinks.

Abstract:  
Organisations need streamlined solutions to not only develop but also to deploy data science models. This presentation will walk through an end to end model development and deployment workflow using the cloud based Watson Data Platform suite of solutions. The Watson Data Platform features flexible, composable services, open source foundation and full support for today’s diverse data types, and its solution components include ingestion and transformation services, storage solutions, analytical engines, a deployment platform and governance tools for data lineage and quality. 

Biographies:

Ross Farrelly 
Ross Farrelly is the Cloud Strategy Leader for the Australia and New Zealand region. He works with companies throughout the region to develop and execute on their strategies to adopt and realize the benefit of cloud computing, focusing on the IBM Cloud Data Services technologies. He has a Master of Applied Statistics, a Masters of Applied Ethics, a first class honours degree in Pure Mathematics and is aiming to compete his PhD in Information Systems this year. 

Stuart Maclean 
Stuart has over twenty year’s experience architecting, managing and implementing technology solutions through the full development lifecycle across a broad spectrum of industry including telecommunications, utilities, insurance, finance and medical. His specific areas of expertise are in architecture consulting and solution delivery with an emphasis on assisting customers to develop and deliver business led technology solutions comprising custom application development, packaged application customization and application integration solutions.

Presentation Slides:

Slides of our previous seminars, including last week’s presentation on Apache NiFi, are now available on Google Drive at link below.https://drive.google.com/drive/folders/0B99OVZvM6G1XeHVsMlpsYWlrbUE?usp=sharing

The 2017 Big Data Summit, Melbourne, 20-22 August 2017

posted Jun 14, 2017, 4:10 AM by Yanchang Zhao   [ updated Jun 14, 2017, 4:11 AM ]

Invitation to

 

2017 Big Data Summit

20-22 August 2017, Collocated with IJCAI2017,

in Melbourne Convention & Exhibition Centre

2017.bigdatasummit.co

 

Early-bird online registrations are now open for significant discount.

We take this privilege opportunity to invite you to participate in the 2017 Big Data Summit (BDS’2017):

  • The 2017 Summit Theme: Artificial Intelligence & Data Science (AI/DS)
  • 20th - 22th Aug 2017: Three day event: 20/8: AI/DS Discipline Courses, 21/8: AI & Data Science Forum, and 22/8: AI/DS Executive Workshop, Melbourne Convention and Exhibition Centre
  • Co-located with IJCAI2017, the largest AI conference, first-time in Australia
  • World-class keynote and invited speakers from global academic, industry and government communities
  • The summit was established in 2012, a forum dedicated to big data, data science, analytics, AI 2.0, data economy and innovation
  • An independent, cross-disciplinary, and cross-domain platform for promoting the gap-bridging between data science research and practices
  • This annual event attracted participants largely from industry and government, BDS’2015 co-located with KDD2015 attracted 450 registrations.
  • BDS15 is proudly supported/sponsored by ACM SIGKDD Australian & NZ Chapter and other institutions and professional bodies

The theme of this year’s Big Data Summit is “Artificial Intelligence & Data Science”. 

Since the Summit’s inception in 2012, we have seen increasing interest and investment within both industry and government in data-led innovation and industralisation to deeply explore big data universe, invent data science, train data scientists and engineers, and develop the data economy.

This year’s event aims to provide data professionals, decision-makers and policy-makers with a global and regional perspective to outline the data science and AI advances, best practices, future directions, data economy and industrialization. The Summit will showcase global advancements and best practices, explore thought-provoking insights, and demonstrate global solutions and lessons learned across industry, government and academia by global AI and data science leaders.

AI/DS Discipline Courses, 20 Aug 2017

  • Seven carefully selected interdisciplinary discipline lectures on AI/DS latest advancements, and future scientific directions
  • Lecturers are all world-leading active professors in respective areas
  • Major topics: Data science, big data, mathematical modelling, artificial intelligence, machine learning, deep learning, data mining, computer vision, Internet/Web of Things, and AI ethics

Big Data Forum, 21 Aug 2017

  • Latest progress and experiences about AI/DS-driven innovation, transformation and best practices
  • Mixed global and regional perspectives, best practices, and experiences
  • All speakers are senior data professionals and leaders in major industry and government organizations
  • Addressing the latest AI/DS technologies, solutions, services, applications, and policies
  • Covering major areas and domains including banking, finance, insurance, telecommunications, government services, and corporate analytics
  • Panel on Data Science: Scientific Revolution?
  • Panel on Data/Intelligence: Future Economic Engine?

AI/DS Executive Workshop, 22 Aug 2017

  • Designed for enterprise executives who lead AI/DS strategies and portfolio
  • The big value, trends, and potential of data to economy and smart decision
  • The global perspectives, experiences, and best practices of data and intelligence economy
  • Informed decisions on enterprise-wide data decisions, solutions, practices and competency
  • Real problem-based deep analysis of enterprise transformation gaps, strategies and opportunities
  • Interactive and personalized mentoring, teamwork, case studies, arguments, and collaborations
  • World top industry and research leaders in AI and DS as mentors and collaborators
  • Collaborative work with senior peers from different domains and backgrounds

What Will be Highlighted in the 2017 Summit?

  • Global advances in scientific development in data and analytics science and AI 2.0
  • Global best practices in data economy and industrial transformation
  • Global perspective of AI & data science trends and directions by leading data/AI scientists from international communities
  • The progress and future of AI & data science in Australia and New Zealand
  • Meeting global research and business leaders in data science & AI
  • Thought and operations leadership and experience in leading data science 
  • Competency, practices, policies and processes in managing data science projects
  • High utility and impact data science case studies and showcases

 

Who Should Attend?

  • Data executives, such as Chief Data Scientists and Chief Data/Analytics Officer
  • Data scientists and data engineers
  • Data modellers, business analysts and business intelligence operators
  • Data & analytics professionals
  • Business decision makers
  • Policy executives
  • Government data analysts and policy-makers
  • Academics (including research students and early career researchers)

Why Should You Attend?

Started in 2012, the annual Summit attracted hundreds of participants from industry, government and academia. The Summit is the premier and unique forum for bridging the gaps between academia, industry and government, and sharing independent insights on the advancement, best practices, trends and controversies about data science, big data, artificial intelligence, and data economy.

With very prestigious speakers across academic, industry and government from the global communities, the 2017 Summit will cover a broad spectrum of data science and AI aspects and domains. The three-day program will substantially lift your

·       vision, knowledge and capabilities in advancement through the AI/DS Discipline Courses,

·       innovation and best practices by the AI/DS Forum, and

·       leadership and strategic decision-making via the AI/DS Executive Workshop.

This unique program to establish a big picture and hands-on grasp of AI & Data Science thought leadership, innovation, services, education and economy.

Co-located with IJCAI2017, BDS’2017 attracts global interest, will mark a unique and high quality opportunity for you and your organization to grasp the cutting-edge and thought-leading progress, network with peers and thought leaders, and most importantly, dig out more insights and value from your big data and lift your personal and organization competency in AI & Data Science in the increasingly competitive and challenging profession, economy and environment.

For More Information

For more details about the Summit, please visit the Website (www.bigdatasummit.co).

For registration to BDS’2017, please Check and Register Here.

For any other inquiries about the 2017 Summit, please feel free to
Contact us.

Tutorials on Machine Learning with Rattle and R, Melbourne, 1 June 2017

posted May 21, 2017, 4:46 PM by Yanchang Zhao   [ updated Jun 5, 2017, 10:55 PM ]

Dr. Graham Williams and myself will run tutorials on Machine Learning with Rattle and R – Decision Trees, Ensemble Models, Association Rules, Text Mining and Social Network Analysis, at the Melbourne Data Science Week, 1 June 2017. Only 3 spots left.

See tutorial details at 

http://www.datasciencemelbourne.com/medascin2017/session/datamining-applications-with-r/

and

http://www.datasciencemelbourne.com/medascin2017/session/data-mining-with-r/

 

Download tutorial materials (incl. PDF slides and R scripts) at MLwR.zip

AusDM 2017: submission deadline extended to 22 May

posted May 7, 2017, 4:49 PM by Yanchang Zhao   [ updated May 7, 2017, 4:50 PM ]

AusDM 2017 will be a special event this year being held in conjunction with IJCAI in Melbourne. This is a tremendous opportunity to present data mining research from Australia to a wider audience, with collaborative arrangements with IJCAI to invite wider participation.

 Submissions are required by 5pm Monday 22 May 2017. Visit http://ausdm17.ausdm.org for details.

Melbourne Data Science Week

posted Apr 20, 2017, 5:22 AM by Yanchang Zhao   [ updated Apr 20, 2017, 5:27 AM ]

Melbourne Data Science Week
29 May - 2 June 2017

Two sold out events from 2016 are combining in 2017 to create what will hopefully be a great Data Science-palooza for Melbourne. Learn about applications, data, ideas and the latest tools for data science. Participate in panel sessions and break-time discussions with your colleagues from industry, academia and government. Hear from the datathon winners about how they did it.
 
For those who want hands on Data Science training there will be 8 full day tutorials from Mon-Thu.

I will run a tutorial on Machine Learning with R on 1 June, covering association rules, text mining and social network analysis. See details of the tutorial at http://www.datasciencemelbourne.com/medascin2017/session/datamining-applications-with-r/.

The tutorials are 80% full and will shortly sell out, so reserve your place now at  http://www.datasciencemelbourne.com/medascin2017/.

Seminar: Scalable Machine Learning for R, by Joseph Blue, Director Global Data Science, MapR

posted Dec 10, 2016, 11:36 AM by Yanchang Zhao   [ updated Dec 10, 2016, 11:38 AM ]

Title: Scalable Machine Learning for R with MapR
Speaker: Joseph Blue, Director of Global Data Science for MapR
Time and Date: 4:30-6:30pm, Thursday, 15 December 2016
Location: 6C35 (building 6, room C35), University of Canberra
RSVP: https://www.meetup.com/CanberraDataSci/events/235809129/

Abstract:
In this discussion, we will review some of the popular libraries that allow R users to interact with large-scale and unstructured data sets through the use of a distributed environment. After a brief intro to deep learning concepts, a demo will be shown that leverages H2O from R to detect anomalies in recent Australian stock prices. The RMarkdown notebook and other resources will be provided to attendees. Additionally, any questions from the audience involving the use of R in distributed environments can be addressed.

Bio:
Joe is the Director of Global Data Science for MapR, where he has focused on collaborating with customers to explore large, unstructured data sources and derive real business value for the past 3 years. He has deployed solutions in financial, healthcare, advertising, manufacturing, retail and media markets.

Prior to joining MapR, Joe developed predictive models in health care for Optum (a division of UnitedHealth) as Chief Scientist. He was the first Fellow for Optum's start-up, Optum Labs and has several patents pending.

Before his time at Optum, Joe accumulated over 10 years of data science experience at Fair Isaac, Lexis Nexis, HNC Software and ID Analytics (now LifeLock) specializing in business problems such as fraud & anomaly detection, which yielded a patent for identity theft detection.

Seminar: Social Network 2.0 – from sharing experiences to sharing values, Prof Xue Li, Canberra, Tuesday 6 Dec

posted Nov 21, 2016, 4:11 AM by Yanchang Zhao   [ updated Nov 21, 2016, 4:12 AM ]

Topic: Social Network 2.0 – from sharing experiences to sharing values
Speaker: Prof. Xue Li, University of Queensland
Date and time: 4:30-5:30pm, Tuesday 6 Dec 2016
Location: 6C34 (Building 6, room C34), University of Canberra
RSVP: http://www.meetup.com/CanberraDataSci/events/234885033/

Abstract:
In current social networks, people share their information, feelings, and experiences with or without their true online identities. For the last 10 years, we have experienced many problems such as spamming, cyberbullying, and misusage of social media for causing problems such as London Riots. One key question is about whether we are OK to associate our true identity with the cyber identity. In social network connected services such as Uber and Airbnb, people are using there traceable identities in the cyberspace, where all transactions are protected by insurance companies or by law. So the question is: if people are willing to use their true identity online in order to share services and values, how can we make social networks a trust-worthy place? In this talk, we discuss the concept of Social Network 2.0 as an emerging type of social networks where people are OK to use their true identities to come together in order to share the services and values. We will present our understanding on the problems on this type of new generation social networks and some of our research initiatives.

About the speaker:
Dr Xue Li is a Professor in DKE (Data and Knowledge Engineering) Division, School of Information Technology, the University of Queensland in Australia. He obtained a BSc in Computer Science in Chongqing University, China in 1982, a MSc in the University of Queensland in 1989, and a PhD in Information Systems in QUT 1997. His research interests are in data mining, intelligent information systems, and social computing. He has over 160 publications as monograph, edited books, book chapters, and journal and conference papers. He was recognized as one of the Top-50 “Most Powerful People in Australia” in 2015 by Australian Financial Review. He has successfully supervised 17 PhD candidates to completion as their Principal Supervisor. He is currently a Chief Investigator for three ARC (Australian Research Council) Funding Projects. He is an Associate Editor of Journal of Advanced Internet of Things.
Homepage: http://staff.itee.uq.edu.au/xue/

Seminar: Exploring causal relationships in observational data, Prof. Jiuyong Li. Canberra, 4:15pm Wed 16 Nov 2016

posted Nov 1, 2016, 5:45 PM by Yanchang Zhao   [ updated Nov 1, 2016, 5:46 PM ]

Topic: Exploring causal relationships in observational data
Speaker: Prof. Jiuyong Li, University of South Australia
Date and time: 4:15-5:15pm, Wednesday 16 Nov 2016
Location: Visitor Centre theatre, AIS, Bruce, Canberra
RSVP: http://www.meetup.com/CanberraDataSci/events/234884945/

Abstract:
Association analysis is an important technology in data mining, and has been widely used in many application areas. However, associations in data can be spurious and they do not indicate causal-effect relationships that are ultimate goals for many scientific explorations and social studies.  While the techniques for association discovery become mature, the problem for identifying non-spurious associations becomes prominent. In this talk, I will discuss some current methods for causal relationship discovery and our research work in this direction.

About the speaker:
Dr Jiuyong Li is a Professor and an Associate Head of School at the School of Information Technology and Mathematical Sciences of University of South Australia. He leads the Data Analytics Group in the School.  His main research interests are in data mining, bioinformatics, and data privacy. He has led five Australian Research Council Discovery projects and leads a Data to Decision CRC project. He has published more than 100 papers, mostly in leading journals and conferences in the areas. His software tools have been used in several real world projects. He has been a chair (or a PC chair) of multiple Australasian data mining and artificial intelligence conferences and international causal discovery workshops. He has received senior visiting fellowships from Nokia Foundation, the Australian Academy of Science, and Japan Society of Promotion of Science.
Homepage: http://people.unisa.edu.au/jiuyong.li

Free Short Course on R and Data Mining, University of Canberra, Fri 7 Oct 2016

posted Sep 20, 2016, 4:04 AM by Yanchang Zhao   [ updated Sep 22, 2016, 4:55 AM ]

Short Course on R and Data Mining

Information Technology and Engineering, University of Canberra

Target Audience: IT&E Project students (ICTP students, Technology Project students, ISES students), IT&E HDR students and Staff, members of the Canberra Data Scientists Group

Fees: There is no fees for the short course but seats are limited to 60 – so register early through http://www.meetup.com/CanberraDataSci/events/234168862/

Presenters: Dr Yanchang Zhao (Adjunct Professor, UC), Professor Dharmendra Sharma

Time: 9:30am – 12:30pm, Fri 7 Oct 2016

Room: 2B7 (Building 2, room B7, University of Canberra)

Map and Parking:

http://www.canberra.edu.au/maps/pdf-maps/PARKING-Casual.pdf

Course Outline:

The course will cover R programming, data exploration and visualisation, and data mining with R. It will cover four topics below in two sessions. Each 1.5-hour session will consist of presentations on two topics, followed by lab for students to do exercises.

- R Programming and Data Exploration and Visualisation with R

- Regression and Classification with R

- Association Rule Mining with R

- Text Mining with R -- an Analysis of Twitter Data

Instructions, prerequisites and slides for the course are or will be available at http://www.rdatamining.com/training/uc.

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