Abstract:
Given data graph G and query graph P, subgraph isomorphism search is to find subgraphs of G that are isomorphic (i.e., structurally identical) to P.  The problem finds numerous applications, but is computationally  intractable.  Over the years the problem has attracted researchers from different fields, and many algorithms have been proposed.  Roughly, these algorithms can be grouped into three types: those based on Constraint Solving; those based on Depth-First Search and Backtracking; and those  based on Relational Join. In this talk, I will first give a brief overview of  each of these types of algorithms, and then provide the main ideas on the most recent Backtracking algorithms proposed by Database researchers (including our own work).  I will also discuss some variations of problem.

Bio：
John (Junhu) Wang received his PhD in Computer Science in 2003 from Griffith University, Australia.  He is currently an associate professor at the same university. Before joining Griffith University as an academic staff, he worked as a lecturer at Monash University, Australia from September 2001 to February 2003.  His current research interest is in Graph Query  Processing, Knowledge Representation, Social Network Analysis, and Text Data Analysis.  Previously, he worked on Constraint Reasoning, XML and Tree Pattern Query Processing. More details about Dr Wang can be found at http://www.ict.griffith.edu.au/~jw/.

Abstract:
　The National Center for Atmospheric Research (NCAR) was established by the National Science Foundation in 1960 with the vision being a world-class research center leading, promoting and facilitating innovation in the atmospheric and related Earth and Sun systems sciences. This presentation will briefly introduce NCAR and its seven laboratories, and then focus on the Research Applications Laboratory (RAL). RAL’s main mission is to conduct fundamental and use-inspired research that contributes to the understanding of the Earth system, extend the capabilities of the scientific community, and transfer knowledge and technology for the betterment of society. We will introduce RAL research and development efforts, and technology highlight.

Abstract:
　Uncertainties in land-surface models (LSMs) parameterization and parameters, in atmosphere forcing conditions used to drive LSMs severely limit their applications in understanding the role of land-atmosphere interactions on weather and climate. To assess these uncertainties, we conducted physical ensemble simulations for selected observation sites. The Noah with multiparameterization (Noah-MP) community land model was used to perform 1152 physics ensemble experiments. We will present results of using two statistical methods (natural selection and Tukey’s test) to identify the range of uncertainties associated with atmospheric forcing conditions, vegetation parameter, and sub-processes, and to mitigate those uncertainties to obtain similar performance to the ensemble mean of the “best” ensemble experiment. We will also discuss impacts of these uncertainties on regional climate simulations.

　Advancing the understanding of the nexus among food, energy, and water systems has recently emerged as a new science frontier, and the research community started modeling agricultural management in earth-system models to develop an integrated modeling tool for investigating relevant land-atmosphere interactions and agriculture sustainability issues. We discuss progress in developing of agricultural management (crop-growth, irrigation, tile drainage) models in Noah-MP and WRF-Crop. Especially, we will focus on the uncertainties in transitioning these agriculture models from field scales to continental scales.

Abstract:
  Today’s changing climate poses two formidable challenges: 1) the projected climate change by IPCC will lead to more frequent occurrences of heat waves, severe weather, and floods, and 2) the current trend of population increase and urban expansion is expected to continue. The combined effect of global climate change and rapid urban growth, accompanied with economic and industrial development, will inevitably make people living in cities more vulnerable to a number of the urban environmental problems. It is imperative to employ integrated modeling systems to accurately represent the land-atmosphere interactions cross various temporal and spatial scales in order to assess such problems. In this paper, we will discuss community efforts in modeling urbanization effects in regional and global models (e.g., WRF and CESM), including recent enhancements to urban hydrologic models and new modeling capabilities in addressing urban heat-island mitigation strategies. This paper will also discuss recent observation projects and the observed effects of urbanization on precipitation extremes. We will conclude this paper with a short discussion on current challenges in urban modeling.