Hybrid Systems: Computation and Control (HSCC) 2019 is the 22nd in a series of conferences focusing on original research on concepts, tools, and techniques from computer science, control theory, and applied mathematics for the analysis and control of hybrid dynamical systems, with an emphasis on computational aspects. By drawing on strategies from computation and control, the hybrid systems field offers techniques that are applicable to both man-made cyber-physical systems (ranging from small robots to global infrastructure networks) and natural systems (ranging from biochemical networks to physiological models). Papers in the conference are expected to range over a wide spectrum of topics from theoretical results to practical considerations, and from academic research to industrial adoption.
Program Committee
Alessandro Abate, University of Oxford, UK
Erika Abraham, RWTH Aachen University, Germany
Matthias Althoff, TU München, Germany
Ebru Aydin Gol, Middle East Technical University, Turkey
Christel Baier, TU Dresden, Germany
Stanley Bak, Safe Sky Analytics, USA
Sergiy Bogomolov, Australian National University, Australia
Samuel Coogan, Georgia Institute of Technology, USA
Jonathan DeCastro, Toyota Research Institute, USA
Jyotirmoy Deshmukh, University of Southern California, USA
Ruediger Ehlers, University of Bremen, Germany
Lu Feng, University of Virginia, USA
Goran Frehse, Université Grenoble Alpes, France
Jie Fu, Worcester Polytechnic Institute, USA
Sicun Gao, UC San Diego, USA
Miriam Garcia Soto, IST Austria, Austria
Khalil Ghorbal, Inria, France
Ichiro Hasuo, University of Tokyo, Japan
Joao Hespanha, UC Santa Barbara, USA
Jianghai Hu, Purdue University, USA
Franjo Ivancic, Google, USA
Jean-Baptiste Jeannin, University of Michigan, USA
Taylor T Johnson, Vanderbilt University, USA
Raphael Jungers, UC Louvain, Belgium
Maryam Kamgarpour, ETH Zurich, Switzerland
James Kapinski, Toyota, USA
Atreyee Kundu, IISc Bangalore, India
Jerome Le Ny, Polytechnique Montreal, Canada
Jun Liu, University of Waterloo, Canada
Rupak Majumdar, Max Planck Institute, Germany
Ian Mitchell, University of British Columbia, Canada
Dejan Nickovic, Austrian Institute of Technology, Austria
Meeko Oishi, University of New Mexico, USA
Michael Posa, University of Pennsylvania, USA
Maria Prandini, Politecnico di Milano, Italy
Akshay Rajhans, MathWorks, USA
Vasumathi Raman, Nuro, USA
Matthias Rungger, ABB, Germany
Dorsa Sadigh, Stanford University, USA
Ricardo Sanfelice, UC Santa Cruz, USA
Sriram Sankaranarayanan, University of Colorado Boulder, USA
Sanjit Seshia, UC Berkeley, USA
Krishna Shankaranarayanan, IIT Bombay, India
Zhikun She, Beihang University, China
Ashish Tiwari, Microsoft, USA
Ashutosh Trivedi, University of Colorado Boulder, USA
Jana Tumova, Royal Institute of Technology, Sweden
Mahesh Viswanathan, University of Illinois at Urbana-Champaign, USA
Rafael Wisniewski, Aalborg University, Denmark
Majid Zamani, TU München, Germany
Organizing committee
Program Committee Chairs
Necmiye Ozay, University of Michigan, USA
Pavithra Prabhakar, Kansas State University, USA
Publicity Chair
Taylor T. Johnson, Vanderbilt University, USA
Repeatability Evaluation Chair
Sergiy Bogomolov, Australian National University, Australia
Steering committee
Rajeev Alur, University of Pennsylvania, USA
Werner Damm, OFFIS, Germany
Martin Fränzle, Univ. of Oldenburg, Germany
John Lygeros, ETH Zurich, Switzerland
Oded Maler, Verimag, France
Paulo Tabuada, UCLA, USA
Claire Tomlin, University of California Berkeley, USA
Topics of interest include, but are not limited to:
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
Regular papers
Maximum 10 pages, 10pt font, two-column ACM format.
Submissions should present unpublished original research, not under review elsewhere. Regular papers can include new theoretical foundations, algorithms, and/or practical results with strong evaluation components.
All regular papers including special track papers on Safe Autonomy, Artificial Intelligence and Machine Learning will be judged on significance, originality, relevance, correctness, and clarity. Authors of accepted regular papers with a computational component will be invited to participate in an optional repeatability evaluation process after notification of acceptance.
Tool and case study papers
Maximum 6 pages, 10pt font, two-column ACM format.
Tool papers will be judged on the significance, clarity, and novelty of the implemented tool/technique described in the paper. Case study papers should report the evaluation of a technique or tool on a challenging application and/or benchmarks.
We consider reproducibility and repeatability of the results presented in the tool/case study papers an important aspect of such papers. While submission of a repeatability evaluation package is not mandatory, we strongly encourage the authors to submit such a package at the time of paper submission. Tool or case study papers with a repeatability evaluation package will be judged on the merit of both the paper itself, but also on the repeatability of the presented results. Tool/Case study papers not accompanied by a RE package would be judged on the strength of the benchmarks (e.g. large-scale industrial/proprietary benchmarks), or the role of the tool as a component in a complex tool-chain ecosystem. Instructions on preparing the repeatability evaluation package can be found here. The deadline for submission of the repeatability package is five days after the paper submission deadline.
04月16日
2019
04月18日
2019
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