Special Sessions & Tutorials

MOD 2017  Special Sessions and Tutorials


The MOD 2017 Organizing Committee invites proposals for Special Sessions and Tutorials.

Call for Special Sessions

Special session proposals are invited to the 3rd International Conference on Machine learning, Optimization and big Data (MOD) to be held in Volterra (Pisa) Tuscany, Italy on September 14-17, 2017.

A special session proposal should include the title, aim and scope of the proposed session, list of potential contributors, and the names, e-mail addresses, affiliations and short bios of the organizers.

Special session proposals will be evaluated based on the timeliness of the topic, its uniqueness, and qualifications of the proposers. The proposers are expected to have a PhD degree and have a good publication track record in the proposed area. A tentative accept/reject decision on the proposal will be sent to the proposers within a few weeks after its receipt by the Special Sessions Chair. Accepted special sessions will be listed on the website. However, it is likely that an accepted proposal will be combined with similar proposals to avoid multiple special sessions covering a similar topic. A final decision will be made two weeks after the special session proposal deadline (April 15, 2017).

Submissions of papers to special sessions should be done through the paper submission website of MOD 2017 where authors can choose a special session title as the main topic of their paper from a list of regular session topics and special session titles. All papers submitted to special sessions will be subject to the same peer-review review procedure as the regular papers. Special sessions having fewer than accepted papers will be cancelled and the accepted papers will be moved to regular sessions.

Special Session Proposals should be sent by email to:  modworkshop2017@gmail.com

All Special Session Proposals should be submitted by March 31, 2017

Call for Tutorials

The internal organization of the satellite tutorials is entirely left up to their respective organizers. MOD 2017 provides the onsite logistics (seminar rooms, projectors and coffee breaks).

Tutorials Information and/or submission proposals: modworkshop2017@gmail.com

Tutorial Proposals

MOD 2017 tutorials will be presented by domain experts to cover current topics relevant to Machine Learning, Optimization and/or Big Data researchers and practitioners. Each tutorial will be 2 hours, then we encourage to include into the tutorial also demos and interactive activities. Accepted tutorial’s slide sets will be published on MOD 2017 website.

Submission Process

Each tutorial proposal should include:

  1. title of the tutorial;
  2. name and affiliation of the lecturer, with relative contact details;
  3. a short CV of the lecturer;
  4. a brief description (half-page) of the tutorial topics.

All tutorial proposals must be sent to: modworkshop2017@gmail.com

Important Dates

  • Submission Tutorial proposals: February  15, 2017 
  • Notification: February 26, 2017
  • MOD 2017 Conference: September 14-17, 2017



Current List of Tutorial and Special Sessions (ver. 1.0 February 26, 2017)

Tutorial on Scalable Data Mining on Cloud Computing Systems

Domenico Talia
Dipartimento di Ingegneria Informatica, Modellistica, Elettronica e Sistemistica – Università della Calabria, Italy
Summary. The analysis of the massive and distributed data repositories is a challenging task and it requires the combined use of intelligent data analysis techniques, machine learning algorithms, and scalable architectures to find and extract useful information from them. Parallel computers, distributed systems and Cloud computing platforms offer an effective support for addressing both the computational and data storage needs of Big Data mining and parallel analytics applications. In fact, complex data mining tasks involve data- and compute-intensive algorithms that require large storage facilities together with high performance processors to get results in suitable times. In this tutorial we introduce the most relevant topics and the main research issues in high performance data mining including parallel data mining strategies, distributed analysis techniques, and Cloud-based data mining. We also present some data mining frameworks designed for developing distributed data analytics applications as workflows of services on Clouds. In these environment data sets, analysis tools, data mining algorithms and knowledge models are implemented as single services that are combined through a visual programming interface in distributed workflows. Application design and execution of data analysis use cases are discussed. Programming issues on exascale systems and applications will be also introduced.

Syllabus. Parallel data mining techniques, distributed data mining, Cloud-based data analytics workflows, exascale programming.

Day: TBA

Short CV of the lecturer: Domenico Talia is a full professor of computer engineering at the University of Calabria. He is a partner of two startups, Exeura and DtoK Lab. His research interests include parallel and distributed data mining, cloud computing, social data analysis, mobile computing, peer-to-peer systems, and parallel programming. Talia published ten books and more than 300 papers in archival journals such as CACM, Computer, IEEE TKDE, IEEE TSE, IEEE TSMC-B, IEEE Micro, ACM Computing Surveys, FGCS, Parallel Computing, IEEE Internet Computing and international conference proceedings. He is a member of the editorial boards of IEEE Transactions on Cloud Computing, the Future Generation Computer Systems journal, the International Journal on Web and Grid Services, the Scalable Computing: Practice and Experience journal, MultiAgent and Grid Systems: An International Journal, International Journal of Web and Grid Services, and the Web Intelligence and Agent Systems International journal. Talia has been a project for several international institutions such as the European Commission, Aeres in France, Austrian Science Fund, Croucher Foundation, and the Russian Federation Government. He served as a chair, organizer, or program committee member of several international conferences and gave many invited talks and seminars in conferences and schools. Talia is a member of the ACM and the IEEE Computer Society.



Industrial Session on Machine Learning, Optimization and Data Science for Real-World Applications

Day: TBA 

MOD 2017 Industrial Session aims to bring together participants from academia and industry in a venue that highlights practical and real-world studies of machine learning, optimization and data science. 

The ultimate goal of this event is to encourage mutually-beneficial exchange between scientific researchers and practitioners working to improve data science analytics. 

The session will consist of a series of invited presentations from leading experts in industry on selected topics in machine learning, optimization and data science from industry perspective and with a special focus on real-world applications. 

The session will then continue with a panel on the future research challenges and opportunities in the field. 

All participants will be encouraged to share and discuss novel ideas, controversial issues, open problems and comparisons of competing approaches. 

Experiences from practitioners will provide crucial input into future research directions.


Important Dates

  • Submission Special Session proposals: March 31, 2017 
  • Special Session Notification: April  15, 2017
  • MOD 2017 Conference: September 14-17, 2017