Call for Papers 2020

Past Call for Papers

SMCDC2020: Smoky Mountains Computational Sciences and Engineering Conference Data Challenge
Virtual Conference Dates: August 25-27, 2020
Website: http://smc-datachallenge.ornl.gov

General chair: Jeff Nichols, Oak Ridge National Laboratory (ORNL)
Data Challenge chair: Suzanne Parete-Koon, ORNL
Conference organizers: Becky Verastegui and Theresa Ahearn, ORNL
Media and communications: Scott Jones and Elizabeth Rosenthal, ORNL

Important dates:
Data Challenge team registration: Open from March 11, 2020 to June 22, 2020

  • Papers due: July 27, 2020
  • Poster Finalist Notifications: August 10, 2020
  • Virtual Poster presentation: August 26, 2020
  • Final paper acceptance notifications: September 1
  • Camera ready paper submission: September 15, 2020

This call is for papers detailing solutions to data analytics challenges based on eminent data sets at ORNL and beyond. These data sets come from scientific simulations and instruments in physical and chemical sciences, electron microscopy, bioinformatics, neutron sources, urban development, and other areas. The challenge questions for each data set will cover multiple difficulty levels. The first question in each challenge should be suitable for a novice, with each subsequent question increasing in difficulty and the series of questions ending with an advanced/expert level challenge question. This data challenge is part of the Smoky Mountains Computational Sciences and Engineering Conference (SMC2020). The current set of data challenges are available here: http://smc-datachallenge.ornl.gov.

Scientists and researchers are encouraged to compete in these analytics challenges whether they are at the beginning stages of incorporating data analytics into their workflow or data analytics experts interested in applying novel data analytics techniques to data sets of national importance. Students and professionals will compete in separate categories.

Participation:
To compete in SMCDC2020, register your team and select a challenge to solve. Participants may work in teams of up to 4 people and will be required to submit a paper describing their solution. See http://smc-datachallenge.ornl.gov for details about the specific analytics challenges and categories of competition.

Paper submission:
Papers should be between 6 and 8 pages in length and contain the following sections: a proposed solution to one of the data challenges, background and related work, approach and uniqueness, results, and contributions. Your code may be included as an appendix to the pdf beyond the page limit. Papers will be peer-reviewed and judged by the program committee based on how well they cover these aspects of the work. Selected contributions are planned to be published in SMC2020 proceedings in a CCIS Springer volume. A selected set of papers will become finalists and be invited to extend the work by incorporating reviewer feedback. The updated papers will be notified of final acceptance on September 1 and due during the camera-ready deadline.
Papers need to be formatted according to Springer’s single column style. Please use the paper templates available for LaTeX and Word (https://www.springer.com/gp/authors-editors/conference-proceedings/conference-proceedings-guidelines). The copyright will need to be transferred to Springer. A copyright form will be provided, which allows users to self-archive.

Papers need to be uploaded here: https://easychair.org/conferences/?conf=smc2020.

Selected teams will be asked to create a 3-minute video and present a poster describing their solution at SMC2020. Teams must have one member or a proxy available to present a lighting talk/virtual poster on August 26th.  Further details and logistics will be provided at the time of selection.

Program Committee:

  • Angelo Antonio Salatino, The Open University
  • Anne Berres, Oak Ridge National Laboratory
  • Dasha Herrmannova, Oak Ridge National Laboratory
  • Dirk Pleiter, Jülich Supercomputing Centre / University of Regensburg
  • Esteban Meneses, Costa Rica Institute of Technology
  • Garrett Granroth, Oak Ridge National Laboratory
  • Guido Juckeland, Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
  • Ioana Danciu, Oak Ridge National Laboratory
  • Jacob Hinkle, Oak Ridge National Laboratory
  • Jibonananda Sanyal, Oak Ridge National Laboratory
  • Junqi Yin, Oak Ridge National Laboratory
  • Ketan Maheshwari, Oak Ridge National Laboratory
  • Kuldeep Kurte, Oak Ridge National Laboratory
  • Madhav Vyas, BP
  • Martin Klein, Los Alamos National Laborator
  • Max Grossman, NAG/BP
  • Melissa Dumas, Oak Ridge National Laboratory
  • Monica Ihli, University of Tennessee
  • Olivera Kotevska, Oak Ridge National Laboratory
  • Peter Peterson, Oak Ridge National Laboratory
  • Pravallika Devineni, Oak Ridge National Laboratory
  • Roxana Rusitoru, Arm Ltd.
  • Ryan Warnick, BP Numerical Algorithms Group
  • Sadaf Alam, Swiss National Supercomputing Centre
  • Shang Gao, Oak Ridge National Laboratory
  • Shervin Sammak, University of Pittsburgh
  • Stuart Campbell, Brookhaven National Laboratory
  • Tirthankar Ghosal, Indian Institute of Technology Patna
  • Tjerk Straatsma,Oak Ridge National Laboratory
  • Travis Johnston, Oak Ridge National Laboratory
  • Wojtek Sylwestrzak, ICM Univeristy of Warsaw
  • Xukai Shen, BP
  • Zahra Ronaghi, NVIDIA