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Today's Topics:
1. CFP: COCOON16: International Computing and Combinatorics
Conference 2016 (AI, CHUNYU)
2. Two PhD studentships in Optimization (Strathclyde Business
School, UK) (Kerem Akartunali)
3. ECCO 2016 conference (Tamás Kis)
4. Winter School in Network Optimization - From 5th (2016) to
6th Edition (2017) (Luis Eduardo Neves Gouveia)
5. Assistant Professor Position in Data Analytics (Muller R (KE))
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Message: 1
Date: Fri, 15 Jan 2016 19:15:17 +0000
From: "AI, CHUNYU" <AIC@uscupstate.edu>
To: "dmanet@zpr.uni-koeln.de" <dmanet@zpr.uni-koeln.de>
Subject: [DMANET] CFP: COCOON16: International Computing and
Combinatorics Conference 2016
Message-ID: <D2BEAF71.D16F%aic@uscupstate.edu>
Content-Type: text/plain; charset="us-ascii"
=========================================
COCOON'16: The 22nd International Computing and Combinatorics Conference
August 2-4th, 2016, Ho Chi Minh city, Vietnam.
Submission deadline: Feb. 21, 2016
Web: http://optnetsci.cise.ufl.edu/cocoon16/index.html
=========================================
The 22nd International Computing and Combinatorics Conference (COCOON'16) will be held in Ho Chi Minh city, Vietnam during Aug. 2-4, 2016. Original research papers in the areas of algorithms, theory of computation, computational complexity, and combinatorics related to computing are solicited. In addition to theoretical results, we are particularly interested in submissions that report on experimental and applied research of general algorithmic interest. Special consideration will be given to research that is motivated by real-world problems. Experimental and applied papers are expected to show convincingly the usefulness and efficiency of the algorithms discussed in a practical setting.
All the papers will be published to the symposium in Springer-Verlag's Lecture Notes.
Papers of high quality will be invited to special issues of Theoretical Computer Science (TCS), and Journal of Combinatorial Optimization (JOCO), respectively.
THE TOPICS Of INTEREST (include but are not limited to):
Algorithms and Data Structures
Algorithmic Game Theory
Approximation Algorithms and Online Algorithms
Automata, Languages, Logic, and Computability
Complexity Theory
Computational Learning Theory and Knowledge Discovery
Cryptography, Reliability and Security, and Database Theory
Computational Biology and Bioinformatics
Computational Algebra, Geometry, and Number Theory
Graph Drawing and Information Visualization
Graph Theory, Communication Networks, and Optimization
Parallel and Distributed Computing
IMPORTANT DATES:
Paper submission due: Feb. 21, 2016 (Anywhere on Earth)
Notification of Acceptance: Apr. 18, 2015
Camera-ready and Registration: May 01, 2016
Conference Dates: Aug. 2-4, 2016
PC Co-Chairs
My T. Thai, University of Florida
Thang N. Dinh, Virginia Commonwealth University
-
Thang N. Dinh, Assistant professor,
Comp. Sci. Dept., Virginia Commonwealth Univ.
Richmond, VA 23284
Web: http://www.people.vcu.edu/~tndinh/
------------------------------
Message: 2
Date: Sun, 17 Jan 2016 09:22:59 +0000
From: Kerem Akartunali <kerem.akartunali@strath.ac.uk>
To: "dmanet@zpr.uni-koeln.de" <dmanet@zpr.uni-koeln.de>
Subject: [DMANET] Two PhD studentships in Optimization (Strathclyde
Business School, UK)
Message-ID: <mailman.114.1453126929.2355.dmanet@zpr.uni-koeln.de>
Content-Type: text/plain; charset="Windows-1252"
Two PhD studentshsips are available at the Dept. of Management Science, University of Strathclyde Business School, Glasgow, UK. Funding is available to cover 3 years of tuition fees plus a tax free stipend (currently higher than £14,000 per year). Both studentships are open to candidates from any nationality (UK/EU/international), and the project topics are:
1) Data Mining in Social Networks
2) Node Deletion and Edge Deletion Problems in Networks
More details about the projects, funding, expected skills and how to apply are provided below.
ABOUT THE PROJECTS
1) Data Mining in Social Networks: Social data from networks such as Twitter and Facebook can be represented as networks. Similarly, various data about city living obtained through City Observatory housed in the Technology & Innovation Centre (TIC) Future Cities theme can be represented in a similar structure, using individuals as nodes of such a network and their connections as edges of the network. The proposed project will design efficient algorithms to mine opinions and sentiments in such networks, in particular in real-time and when big data is present. The problem of sentiment and opinion analysis involves studying the negative and positive expressions opined in social media on a specific subject matter. We will work on such algorithms that volume and velocity of data accumulated in the context of social media is the most crucial design factor. This will also exploit some of the theoretical insights gained in an ongoing cross-faculty PhD project with Department of Mathematics & Statistics. The project aims to establish both theoretical and computational analysis, using various tools and techniques such as network optimization, design of algorithms and integer programming. As part of the computational work, we plan to use ARCHIE-WeSt, the high performance computing centre housed at University of Strathclyde.
2) Node Deletion and Edge Deletion Problems in Networks: In this project, we plan to develop efficient algorithms to study the node and edge deletion problems on networks. These problems stem from various important applications in energy networks (e.g., how to build a network that can survive failures on particular power lines), epidemic containment (e.g., how to ensure disconnectivity between various populations) and defense operations (e.g., where to focus attacks on enemy to ensure faster victory). The problem involves in effectively identifying a subset of nodes or edges of a network, which on deletion results in a subgraph with desirable properties. Some of the properties of interest include the connectivity in the graph, a restrictive size of the largest component, and denseness of the components formed. As part of the research, we plan to establish theoretical and empirical analysis for two specific network types. The theoretical work might include methods such as complexity analysis, analysis of the hardness of approximation and developing approximation algorithms and polyhedral analysis for the problems. The experimental work might involve designing and implementing exact computational integer programs and efficient heuristics that would be built upon the theoretical foundation.
FUNDING AND ELIGIBILITY
Funding is available to cover 3 years of tuition fees for a UK/EU/international student, plus a tax free stipend higher than £14,000 per year. The student will be given opportunities to attend a conference and/or specialized training every year.
These PhD projects require a highly numerate graduate with skills and interests in computational science. Candidates should have at least a strong Honours degree or equivalent (a strong 2:1 Honours degree, or a B.Sc. degree with 3.3 GPA in a 4.0 system), or preferably a Master's degree in a quantitative discipline such as industrial engineering, operations research, mathematics or computer science (amongst others). Experience in programming and fundamental knowledge in optimization (in particular integer programming) are not essential but highly desirable. Candidates who are not native English speakers will be required to provide evidence for their English skills (such as by IELTS or similar tests that are approved by UKVI, or a degree completed in an English speaking country)
Applications are admitted until 31st May, or until a suitable candidate is found thereafter.
HOW TO APPLY
All PhD applications are to be made online at http://pgr.strath.ac.uk/. All documents (including scans of original documents) can be uploaded during the online application process. Candidates are expected to submit a cover letter, a research proposal detailing their 3-year plan, CV, any university degree certificates and transcripts, English test results (if applicable), two recommendation letters (or contact details of two referees, if letters are not available to them), and any other supporting documents. In order to be considered for this studentship, candidates should specifically note the title of this project in their online application when prompted about funding and their source of finance, and they should notify Ms Alison Kerr for their intent for studentship application.
More information about the department can be found here: http://www.strath.ac.uk/business/managementscience/
Informal enquiries about the projects to Dr Kerem Akartunali (kerem.akartunali@strath.ac.uk) or Dr Ashwin Arulselvan (ashwin.arulselvan@strath.ac.uk).
Enquiries regarding applications to: Ms Alison Kerr (alison.kerr@strath.ac.uk)
------------------------------
Message: 3
Date: Sun, 17 Jan 2016 14:46:59 +0100
From: Tamás Kis <kis.tamas@sztaki.mta.hu>
To: dmanet@zpr.uni-koeln.de
Subject: [DMANET] ECCO 2016 conference
Message-ID: <569B9B53.2040201@sztaki.mta.hu>
Content-Type: text/plain; charset=iso-8859-2; format=flowed
EURO Working Group on Combinatorial Optimization
CALL FOR PAPERS
The 29th Conference of the European Chapter on Combinatorial Optimization
ECCO XXIX 2016
http://ecco2016.euro-online.org/
May 26-28, 2016.
Eötvös Loránd University, Budapest, Hungary
PAPER SUBMISSION DEADLINE: March 1st, 2016.
PAPER SUBMISSION IS OPEN!
The 29th Conference of the European Chapter on Combinatorial Optimization will be jointly organized by the Institute of Computer Science and Control of the Hungarian Academy of Sciences, and the Eötvös Loránd University in Budapest, Hungary on May 26 - 28, 2016. ECCO (European Chapter on Combinatorial Optimization) is a working group of EURO (Association of European Operational Research Societies) that provides an excellent opportunity to discuss recent and important issues in Combinatorial Optimization and its applications.
The ECCO annual meetings aim to bring together researchers in the field of Combinatorial Optimization to present their work, share experiences, and discuss recent advances in theory and applications. The primary objectives are:
*exchanging results and experiences in solving real-world combinatorial optimization problems
*reporting on development and implementation of appropriate models and efficient solution methods for combinatorial optimization problems
*establishing networking contacts between individuals and research groups working on related topics
*promoting the work on combinatorial optimization (theory and applications) to the broader scientific community
*identifying challenging research problems for the field, as well as promising research outlets (both in theory and applications)
*promoting interactions with researchers in other related fields
We seek submissions in all areas of combinatorial optimization from theory through applications.
The submission is limited to a half to one page abstract.
Confirmed Plenary Speakers
András Frank, Eötvös University, Hungary.
David Pisinger, Technical University of Denmark.
Leo Liberti, CNRS LIX, École Polytechnique, France.
Andrej Brodnik, University of Ljubljana, Slovenia.
Program committee
Jacek Blazewicz, Polish Academy of Sciences Poznán, Poland.
Van-Dat Cung, Grenoble INP, France.
János Csirik, University of Szeged, Hungary,
Gábor Galambos, University of Szeged, Hungary.
Alain Hertz, École Polytechnique Montréal, Canada.
Tibor Jordán, Eötvös Loránd University, Hungary.
Tamás Kis, Institute for Computer Science and Control, Hungary (Chairperson).
Silvano Martello, University of Bologna, Italy.
Paolo Toth, University of Bologna, Italy.
Important Dates
December 1st, 2015: abstract submission starts
March 1st, 2016: deadline for abstract submission
March 17th, 2016: notification of acceptance
April 1st, 2016: deadline for early registration
May 26th-28th, 2016: ECCO XXIX 2016 Conference in Budapest
------------------------------
Message: 4
Date: Sun, 17 Jan 2016 18:39:14 +0000
From: Luis Eduardo Neves Gouveia <legouveia@fc.ul.pt>
To: "dmanet@zpr.uni-koeln.de" <dmanet@zpr.uni-koeln.de>
Subject: [DMANET] Winter School in Network Optimization - From 5th
(2016) to 6th Edition (2017)
Message-ID: <1453055954105.4314@fc.ul.pt>
Content-Type: text/plain; charset="iso-8859-1"
The 5th edition of the Winter School on Network Optimization (see http://NetOpt2016.fc.ul.pt<http://netopt2016.fc.ul.pt/>) took place in the Hotel Sana, Estoril, from the 11th to the 15th of January 2016. The school had 41 students of several nationalities and coming from different Universities, Laboratories and Institutes, 2 from Austria, 5 from Belgium, 1 from Canada, 4 from Denmark, 4 from France, 8 from Germany, 9 from Italy, 1 from Mexico, 1 from Norway, 2 from Portugal, 1 from Spain, 2 from The Netherlands and 1 from Turkey.
Five courses were given by well known researchers of the area: Tolga Bektas (Univ of Southampton), Elena Fernandez (UPC), Martine Labbé (ULB), Karen Aardal (Delft Univ.) and Ivana Ljubic (ESSEC).
We have the pleasure to announce that the 6th Winter School on Network Optimization is scheduled for January 2017.
The first formal announcement will be made in June/July of 2016.
Available information, including list of speakers and dates is given below
6th Edition of Winter School on Network Optimization (netopt2017)
The 6th edition of the Winter School on Network Optimization will take place at the Hotel Sana, Estoril, from the 16th to the 20th of January 2017. Its main objective is to provide an opportunity for PhD students to get together and attend high level courses in the field of Network Optimization. Non-PhD students are welcome to attend the school, but the number of participants is limited and priority will be given to PhD students. In this edition of the school, the lecturers and subjects to be addressed are:
Angel Corberan (Univ. Valencia): Arc routing problems with profits
Arie Koster (RWTH Aachen Univ.): Robust optimization for network design and energy supply problems
Gerhard Reinelt (Univ. Heidelberg): Ordering problems
Giovanni Rinaldi (IASI): Maximum weight cuts in graphs and extensions
Jose Valerio de Carvalho (Univ. Minho): Dual feasible functions to construct fast lower bounds
Since the first edition in 2009, the school has been part of the activities of the CIO (Centro de Investigação Operacional) University of Lisbon as well as of the ENOG (European Network Optimization Group).
CIO has been merged with the Centro de Matemática e Aplicações Fundamentais (CMAF). Since the 5th edition the event is part of the activities of the new CMAFCIO and is also endorsed by the EURO (the Association of European Societies) and APDIO (the Portuguese OR society).
Webpage and Information about how to apply will be given in June 2016 (http://NetOpt2017.fc.ul.pt<http://netopt2016.fc.ul.pt/> )
------------------------------
Message: 5
Date: Sun, 17 Jan 2016 21:26:56 +0000
From: "Muller R (KE)" <r.muller@maastrichtuniversity.nl>
To: "dmanet@zpr.uni-koeln.de" <dmanet@zpr.uni-koeln.de>
Subject: [DMANET] Assistant Professor Position in Data Analytics
Message-ID: <77c1b8a26d5f496ea7703bee43e30b61@UM-MAIL3218.unimaas.nl>
Content-Type: text/plain; charset="iso-8859-1"
(Tenure track) Assistant Professor Position in Data Analytics
The Department Quantitative Economics of Maastricht University School of Business and Economics (SBE) and the Business Intelligence and Smart Services Institute offer a tenure track assistant professorship in Data Analytics.
The newly established Business Intelligence and Smart Services Institute (www.biss-institute.nl<http://www.biss-institute.nl>) is a joint initiative by Maastricht University, Open University, and University of Applied Sciences Zuyd. At the institute, an interdisciplinary research team will perform applied and fundamental research on technological, business and societal aspects of data driven smart services. It will also host educational labs in which students from all three universities work on applied projects on business intelligence and big data in a diversity of functional areas such as Finance, Accounting, Marketing, Health Care and Smart Cities.
The BISS institute is located at the Smart Services Campus (SSC) in Heerlen. The campus is an eco-system in which large enterprises (e.g. APG, Accenture, Conclusion) and SMEs collaborate with researchers and students on technological, business and social innovation.
The assistant professor data analytics will be a member of the BISS institute (4 days/week) and affiliated to the department of Quantitative Economics at Maastricht University (1 day/week). He/she will be working in a cooperative environment where researchers from related fields, e.g. from econometrics, statistics, data mining, operations research, machine learning and computer science will have an opportunity to cooperate with each other.
The data analyst will have a set of tasks related to research, education, and business development. Scientific research in high-dimensional statistics or econometrics for big data, predictive and prescriptive analytics will be some of the main tasks for this position. Experts in the following research areas are especially encouraged to apply:
· Econometric and statistical methods for high-dimensional data sets; preferably with a focus on methodology or theory;
· Intersection of machine learning and statistics/econometrics;
· Intersection of data mining, artificial intelligence and statistics.
The BISS institute is also involved in educational activities in data analytics, business informatics, and business development. Therefore, we ask for experience in teaching related to data analytics in the broad sense. A proof of excellence in teaching is definitely a "pro".
Finally, the data analyst will participate in industrial projects by means of gathering and analyzing data to solve specific business problems. He/she should be able to evaluate possible scenarios, to make predictions on future outcomes, and to support decision making. Thus, he/she should have experience in applying data analytic (e.g. statistics/econometrics or machine learning) techniques to large economic and business data sets. He/she should be an advanced user, or even a developer, of software tools for statistical analysis of high-dimensional data sets.
Typical workload: 40% education and 60% research, of which a significant part might be in collaboration with industry.
Requirements:
* PhD or equivalent advanced degree in a field relevant to data analytics, such as econometrics, statistics, machine learning, artificial intelligence, operations research or computer science;
* Self-motivation;
* Solid track record of scientific publications in international peer-reviewed journals in one of the fields above. Preference will be given to candidates having methodological expertise that goes beyond simple applications of these techniques;
* Excellent interpersonal skills, including the ability to interact with scientists, corporates, SME's, Start-Ups and stakeholders in the public sector, at a variety of levels in a collaborative, effective manner;
* A track record of success in working within teams;
* Experience in acquiring research funding is a pro.
Conditions of employment: The terms of employment of Maastricht University are set out in the Collective Labour Agreement of Dutch Universities (CAO). Furthermore, local UM provisions also apply. For more information look at the website www.maastrichtuniversity.nl/<http://www.maastrichtuniversity.nl/> , employees, A-Z.
Contract type: Tenure track for starting ass. prof.; permanent, when proven to have sufficient experience.
Organisation
Maastricht University is renowned for its unique, innovative, problem-based learning system, which is characterized by a small-scale and student-oriented approach. Research at UM is characterized by a multidisciplinary and thematic approach, and is concentrated in research institutes and schools. Maastricht University has around 16,000 students and 4,000 employees. Reflecting the university's strong international profile, a fair amount of both students and staff are from abroad. The university hosts 6 faculties: Faculty of Health, Medicine and Life Sciences, Faculty of Law, School of Business and Economics, Faculty of Humanities and Sciences, Faculty of Arts and Social Sciences, Faculty of Psychology and Neuroscience.
Applications:
Applications should be received not later than February 14, 2016. They should include a curriculum vitae and copies of some written work. Two letters of reference, assessing the applicant's research potential and personality, should be sent independently by the referees. Applications can, preferably, be sent by e-mail to: recruitment-sbe@maastrichtuniversity.nl<mailto:recruitment-sbe@maastrichtuniversity.nl> (with cc to j.urbain@maastrichtuniversity.nl<mailto:j.urbain@maastrichtuniversity.nl>) or to: Maastricht University School of Business and Economics, Personnel Department, P.O. Box 616, 6200 MD, Maastricht, The Netherlands, and refer to vacancy AT2015.245 on both letter and envelope.
For more information about the position you can contact:
Prof. dr. Jean-Pierre Urbain, phone: +31 43 3883660, email j.urbain@maastrichtuniversity.nl<mailto:j.urbain@maastrichtuniversity.nl>
or
Prof. dr. Rudolf Müller, phone +31 43 3883799, e-mail r.muller@maastrichtuniversity.nl<mailto:r.muller@maastrichtuniversity.nl>
Prof.dr. Rudolf Müller
Scientific Director
Business Intelligence and Smart Services Institute
www.biss-institute.nl<http://www.biss-institute.nl/>
r.muller@maastrichtuniversity.nl <mailto:r.muller@maastrichtuniversity.nl>
www.maastrichtuniversity.nl/web/profile/r.muller.htm
T +31 43 388 3799
M +31 6 41325231
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End of dmanet Digest, Vol 95, Issue 15
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