<html><head><meta http-equiv="Content-Type" content="text/html charset=us-ascii"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div class=""><div class="">MOD 2017: The 3rd International Conference on Machine learning, Optimization & big Data</div><div class="">An Interdisciplinary Conference: Machine Learning, Optimization and Data Science without Borders</div><div class="">=======================================================</div><div class="">September 14 - 17, 2017</div><div class="">Volterra (Pisa) Tuscany, Italy</div><div class=""><br class=""></div><div class=""><a href="http://www.taosciences.it/mod/" class="">http://www.taosciences.it/mod/</a></div><div class=""><br class=""></div><div class=""><br class=""></div><div class="">Important dates</div><div class="">===============</div><div class="">* Full Paper Submissions: March 31, 2017</div><div class="">* Full Paper Notifications: May 1, 2017</div><div class="">* Special Session Proposals: March 31, 2017</div><div class="">* Special Session Notifications: April 15, 2017</div><div class="">* Workshop Proposals: March 31, 2017</div><div class="">* Workshop Notifications: April 15, 2017</div><div class="">* Conference: September 14 - 17, 2017</div><div class=""><br class=""></div><div class="">The International Conference on Machine learning, Optimization, and big Data (MOD) has established itself as a premier interdisciplinary conference in machine learning, computational optimization and data science. It provides an international forum for presentation of original multidisciplinary research results, as well as exchange and dissemination of innovative and practical development experiences. The MOD 2017 conference will consist of four days of conference sessions, tutorials, demo and special sessions. We invite submissions of papers, abstracts and posters on all topics related to Machine learning, Optimization and Big Data including real-world applications.</div><div class=""><br class=""></div><div class=""><br class=""></div><div class="">Topics of Interest</div><div class="">===============</div><div class="">Topics of interest include, but are not limited to:</div><div class="">* Foundations, algorithms, models and theory of data science, including big data mining.</div><div class="">* Machine learning and statistical methods for big data.</div><div class="">* Multi-objective optimization.</div><div class="">* Big data Mining from heterogeneous data sources, including text, semi-structured, spatio-temporal, streaming, graph, web, and multimedia data.</div><div class="">* Big Data mining systems and platforms, and their efficiency, scalability, security and privacy.</div><div class="">* Computational optimization. </div><div class="">* Optimization algorithms for Real World Applications. </div><div class="">* Optimization in Big Data.</div><div class="">* Optimization and Machine Learning.</div><div class="">* Big Data mining for modeling, visualization, personalization, and recommendation.</div><div class="">* Big Data mining for cyber-physical systems and complex, time-evolving networks.</div><div class="">* Applications in social sciences, physical sciences, engineering, life sciences, web, marketing, finance, precision medicine, health informatics, medicine and other domains.</div><div class="">* Industrial applications of Machine Learning, Optimization and Big Data.</div><div class=""><br class=""></div><div class="">We particularly encourage submissions in emerging topics of high importance such as data quality, deep learning, time-evolving networks, large multi-objective optimization, quantum optimization, big data mining and analytics, cyber-physical systems, and heterogeneous data integration and mining.</div><div class=""><br class=""></div><div class=""><br class=""></div><div class="">Submission Guidelines</div><div class="">===============</div><div class="">Paper submissions should be limited to a maximum of 12 pages, in the Springer LNCS format:</div><div class=""><a href="http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0" class="">http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0</a></div><div class="">including the bibliography and any possible appendices. </div><div class=""><br class=""></div><div class="">All submissions will be 6-blind reviewed by the Program Committee on the basis of technical quality, significance, multidisciplinary, relevance to scope of the conference, originality and clarity. </div><div class=""><br class=""></div><div class=""><a href="https://easychair.org/conferences/?conf=mod2017" class="">https://easychair.org/conferences/?conf=mod2017</a></div><div class=""><br class=""></div><div class=""><br class=""></div><div class="">Types of Submissions</div><div class="">===============</div><div class="">When submitting a paper to MOD 2017, authors are required to select </div><div class="">one of the following four types of papers:</div><div class="">+ Long paper: original novel and unpublished work (max. 12 pages in Springer LNCS format);</div><div class="">+ Short paper: an extended abstract of novel work (max. 4 pages);</div><div class="">+ Work for oral presentation only (no page restriction; any format). </div><div class="">For example, work already published elsewhere, which is relevant and which may solicit fruitful discussion at the conference;</div><div class="">+ Abstract for poster presentation only (max. 2 pages). The poster format for the presentation is A0 (118.9 cm high and 84.1 cm wide, respectively 46.8 x 33.1 inch). For research work which is relevant and which may solicit fruitful discussion at the conference.</div><div class=""><br class=""></div><div class="">Post-Proceedings</div><div class="">===============</div><div class="">All accepted long papers will be published in a volume of the series 'Lecture Notes in Computer Science' from Springer *after* the conference. Instructions for preparing and submitting the final versions (camera-ready papers) of all accepted papers will be available later on. All the other papers (short papers, abstracts of the oral presentations, abstracts for the poster presentations) will be published on the MOD 2017 web site.</div><div class=""><br class=""></div><div class=""><br class=""></div><div class="">Presentation</div><div class="">===============</div><div class="">MOD uses the single session formula of 30 minutes presentations for fruitful exchanges between authors and participants.</div><div class=""><br class=""></div><div class=""><br class=""></div><div class="">Best Paper Awards</div><div class="">===============</div><div class="">Springer sponsors the MOD 2017 Best Paper Award with a cash prize of EUR 1,000.</div><div class="">The Award will be conferred at the conference on the authors of the best paper award.</div><div class=""><br class=""></div><div class=""><br class=""></div><div class="">Attendance</div><div class="">===============</div><div class="">MOD is a premier forum for presenting and discussing current research in machine learning, optimization and big data. Therefore, at least one author of each accepted paper must complete the conference registration and present the paper at the conference, in order for the paper to be included in the proceedings and conference program.</div><div class=""><br class=""></div><div class=""><br class=""></div><div class="">Keynote Speakers</div><div class="">===============</div><div class="">+ Ruslan Salakhutdinov, Machine Learning Department, School of Computer Science at Carnegie Mellon University, USA. </div><div class=""> Director of AI Research at Apple.</div><div class=""><br class=""></div><div class="">+ Jun Pei, Hefei University of Technology, China</div><div class=""><br class=""></div><div class="">Other speakers will be announced soon!</div><div class=""><br class=""></div><div class=""><br class=""></div><div class=""><br class=""></div><div class="">Organization</div><div class="">===============</div><div class="">General Chair:</div><div class="">Renato Umeton, Harvard University, USA</div><div class=""><br class=""></div><div class="">Program Co-Chairs:</div><div class="">Giovanni Giuffrida, University of Catania, Italy & Neodata Group</div><div class="">Giuseppe Nicosia, University of Catania, Italy</div><div class="">Panos Pardalos, University of Florida, USA</div><div class=""><br class=""></div><div class="">Special Session Co-Chairs:</div><div class="">Giuseppe Narzisi, New York University Tandon School of Engineering & New York Genome Center, New York, USA</div><div class=""><br class=""></div><div class="">Workshop Co-Chair:</div><div class="">Piero Conca, CNR, Italy</div><div class=""><br class=""></div><div class="">Industrial Panel Chairs:</div><div class="">Ilaria Bordino, Marco Firrincieli, Fabio Fumarola, and Francesco Gullo, UniCredit R&D</div><div class=""><br class=""></div><div class="">Publicity Chair:</div><div class="">Giovanni Murabito, DiGi Apps Inc.</div><div class="">Giulia Santarelli, DiGi TaoSc</div><div class=""><br class=""></div><div class="">W: <a href="http://www.taosciences.it/mod/" class="">http://www.taosciences.it/mod/</a></div><div class="">E: <a href="mailto:modworkshop2017@gmail.com" class="">modworkshop2017@gmail.com</a></div></div><div class=""><br class=""></div><div class=""><br class=""></div><div class=""><br class=""></div><br class=""><div class="">
<div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div style="color: rgb(0, 0, 0); letter-spacing: normal; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">-- <br class="">Giuseppe Nicosia, Ph.D.<br class="">Associate Professor of Computer Science<br class="">Dept of Mathematics & Computer Science <br class="">University of Catania <br class="">Viale A. Doria, 6 - 95125 Catania, Italy <br class="">P +39 095 7383048<br class=""><a href="mailto:nicosia@dmi.unict.it" class="">nicosia@dmi.unict.it</a> <br class=""><a href="http://www.dmi.unict.it/nicosia" class="">http://www.dmi.unict.it/nicosia</a></div><div style="color: rgb(0, 0, 0); letter-spacing: normal; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">==================================================================<br class="">4th International Synthetic & Systems Biology Summer School - SSBSS 2017<br class="">* Biology meets Computer Science & Engineering *<br class="">July 17-21, 2017 - University of Cambridge, Robinson College, UK </div><div style="color: rgb(0, 0, 0); letter-spacing: normal; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><a href="http://www.taosciences.it/ssbss/" class="">http://www.taosciences.it/ssbss/</a> </div><div style="color: rgb(0, 0, 0); letter-spacing: normal; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">Contact Email: <a href="mailto:ssbss.school@gmail.com" class="">ssbss.school@gmail.com</a><br class=""><br class="">FB: <a href="https://www.facebook.com/ssbss.school/" class="">https://www.facebook.com/ssbss.school/</a><br class=""><br class="">SSBSS - Synthetic & Systems Biology Summer School Group: <a href="https://www.facebook.com/groups/238417586492061/" class="">https://www.facebook.com/groups/238417586492061/</a><br class=""><br class="">Computational Synthetic Biology Group: <a href="https://www.facebook.com/groups/1014624245288596/" class="">https://www.facebook.com/groups/1014624245288596/</a><br class=""></div><div style="color: rgb(0, 0, 0); letter-spacing: normal; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">==================================================================</div><div style="color: rgb(0, 0, 0); letter-spacing: normal; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">3rd International Conference on Machine learning, Optimization & big Data - MOD 2017<br class="">September 14-17, 2017 - Volterra (Pisa), Tuscany, Italy<br class=""><a href="mailto:modworkshop2017@gmail.com" class="">modworkshop2017@gmail.com</a></div><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><a href="http://www.taosciences.it/mod/" class="">http://www.taosciences.it/mod/</a><br class="">==================================================================</div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>
</div>
<br class=""></body></html>