ICCS is well known for its excellent line up of keynote speakers. This page will be frequently updated with new names, lecture titles and abstracts.
Charlie Catlett, Argonne National Laboratory | University of Chicago, USA
Understand Cities Through Measurement and Embedded Intelligence
Xiaofei Chen, Southern University of Science and Technology, China
Liesbet Geris, University of Liège | KU Leuven, Belgium
Sarika Jalan, Indian Institute of Technology Indore, India
Petros Koumoutsakos, ETH Zürich, Switzerland
Xuejun Yang, National University of Defense Technology, China
Argonne National Laboratory | University of Chicago, USA
Charlie Catlett is a Senior Computer Scientist at Argonne National Laboratory, a U.S. Department of Energy scientific research laboratory. Catlett is also a Senior Fellow at the Computation Institute of the University of Chicago and Argonne National Laboratory, and a Visiting Artist at the School of the Art Institute of Chicago. His current research focus areas include urban data science, cyber security and privacy, mobile devices and social networks, and the use of mobile and embedded computing to create intelligent infrastructure. He served as Argonne’s Chief Information Officer from 2007-2011.
From 2004 through 2007 he was director of the TeraGrid Initiative, a national-scale facility supported by the National Science Foundation.
In 1999 Charlie co-founded the Global Grid Forum, (now Open Grid Forum) serving as its founding chair from October 1999 through September 2004. Concurrently, he directed the State of Illinois funded I-WIRE optical network project, deploying dark fiber and transport infrastructure to ten institutions in Illinois. I-WIRE today provides over 200 Gb/s of lambda and dark fiber resources to major projects including TeraGrid, the Starlight international optical network hub, Optiputer, and ESnet.
Prior to joining Argonne in 2000, Charlie was Chief Technology Officer at the National Center for Supercomputing Applications (NCSA). As part of the original team that established NCSA in 1985, Charlie participated in design, deployment, and evolution of NSFNET, which was one of several early national networks that collectively evolved into today’s Internet. Beginning in 1992 his team designed and operated NCSAs web infrastructure during the exponential growth of the web following NCSA’s release of the Mosaic web browser.
Global urbanization, quality of life in cities—from air quality to mobility to equitable opportunity—and reducing negative impacts of cities on the natural environment are among the grand challenges of the 21st century. Within these challenges are critical research questions, suggesting that partnerships between the scientific community and city planners, designers, and operators—as well as city dwellers—will be essential. Catlett will discuss a series of collaborative interactions between the science community in Chicago and the City of Chicago, including the motivation and process behind the NSF-funded Array of Things project and how it is being replicated in other cities.
Southern University of Science and Technology, China
CHEN Xiaofei, Professor of Geophysics at School of Earth and Space Sciences, USTC; Distinguished Professor of Changjiang Scholar Program of the Ministry of Education; elected Fellow of IUGG(2015); elected Member of Chinese Academy of Science (2015). BS.(1982),University of Science and Technology of China; MS.(1985),Institute of Geophysics of China Earthquake Administration, China; PhD.(1991),University of Southern California, USA. He was with Peking University as a Professor in the Department of Geophysics during 1996-2008. He had been Director of Division Solid Geophysics, Chair of Department of Geophysics, deputy dean of the School of Earth and Space Sciences during 1996-2008 in Peking University. He was awarded by the National Natural Science Foundation for Distinguished Young Scientists in 1996,and the Earth Science Award by Ho Leung Ho Lee Foundation in 2009. He was elected as Vice President of the China Seismological Society in 2011, and Vice President of the Chinese Geophysical Society in 2012. Currently, he is an Editor of Geophysical Journal International, Associate Editor in-Chief of Earthquake Science. His main research interests are computational seismology and applications in Earth Structure Imaging and Seismic Hazard Mitigation. He had published more than 120 scientific research papers.
The threat and the risk caused by earthquakes are becoming more and more serious as the highly developing society. How to effectively mitigate the casualties and economic loss are the urgent problems needed to be solved for our country and other places exposed to serious risk caused by earthquakes. By combing of the knowledge of earthquakes and capability of supercomputers, computational seismology can be used to investigate the occurred destructive earthquakes and simulate the scenarios of potential earthquakes. In the past decades, we developed a powerful numerical method to solve the rupture dynamics, strong ground motion under the real complex conditions, such as the irregular topography, non-planar fault, and heterogeneous media. With helps from supercomputers, we can use this method to investigate seismic hazards with much fine resolutions and high accuracy if we have enough computing capability. It is lucky that more and more computing resource can be available due to the supercomputer developing, which enables us to investigate earthquakes with high spatial and temporal resolutions. One of the examples is the Nonlinear Tangshan earthquake simulations on Sunway TaihuLight, enabling us to investigate the seismic hazards in the frequency up to 18 Hz and resolution of 8 m. These studies of computational seismology could help us to understand the causes of seismic hazards, and provide scientific basis for designating and implementing the effective mitigating measures to seismic hazards.
University of Liège | KU Leuven, Belgium
Liesbet Geris is Francqui Research Professor in Biomechanics and Computational Tissue Engineering at the universities of Liège and Leuven in Belgium. Her research focusses on the multi-scale and multi-physics modeling of biological processes. Together with her team and their clinical and industrial collaborators, she uses these models to investigate the etiology of non-healing fractures, to design in silico potential cell-based treatment strategies and to optimize manufacturing processes of these tissue engineering constructs. Liesbet is scientific coordinator of the Prometheus platform for Skeletal Tissue Engineering (50+ researchers). She has edited several books on computational modeling and tissue engineering. She has received 2 prestigious ERC grants (starting in 2011 and consolidator in 2017) to finance her research and has received a number of young investigator and research awards. She is member and former chair of the Young Academy of Belgium (Flanders) and member of the strategic alliance committee of the Tissue Engineering and Regenerative Medicine Society. She is the current executive director of the Virtual Physiological Human Institute and in that capacity she advocates the use of in silico modeling in healthcare through liaising with the clinical community, the European Commission and Parliament, regulatory agencies (EMA, FDA) and various other stakeholders. Besides her research work, she is often invited to give public lectures on the challenges of interdisciplinary in research, women in academia and digital healthcare.
Tissue Engineering is a field that combines the principles of engineering and biomedical sciences in order to develop living implants that can restore or replace tissues or organs. One of the major challenges in tissue engineering, and an essential step towards successful clinical applications, is the translation of biological knowledge on complex cell and tissue behavior into predictive and robust engineering processes. Computational modelling can contribute to this, among others because it allows to study the biological complexity in a more quantitative way. Computational tools can help in quantifying and optimizing micro-environmental signals to which cells and tissues are exposed and in understanding and predicting the biological response under different conditions.
A wide variety of model systems has been presented in the context of tissue engineering ranging from mechanistic models (hypothesis-based) over gene network models to empirical models (data-driven), targeting processes at the intracellular over the cellular up to the tissue level. Each model system has its own benefits and limitations which delineate the context in which it can be used. Whereas mechanistic models are used as in silico tools to design new therapeutic strategies and experiments, empirical models are used to identify, in large data sets, those in vitro parameters (biological, biomaterial, environmental) that are critical for the in vivo outcome.
In this talk I will give an overview of various application of in silico regenerative medicine that were developed to answer questions from the experimental researchers and clinicians in our Tissue Engineering platform. Models of intracellular signaling, biomaterial design, bioprocess design and in vivo regeneration under challenging conditions will be discussed. I will end with a discussion of a number of challenges we are facing in the in silico medicine community as a whole as it pertains to establishing credibility of our models and technologies.
Indian Institute of Technology Indore, India
Sarika Jalan is a Professor of Physics and adjunct faculty in the Discipline for Biosciences and Biomedical Engineering at Indian Institute of Technology (IIT) Indore, India. The Complex Systems Lab at IIT Indore lead by Sarika Jalan focuses on inter-disciplinary research. Using network theory, nonlinear dynamics and computational techniques, the lab, on one hand, works on fundamental aspects of complex systems and network science research and on other hand applies techniques developed in the lab to real-world systems coming from Biology and Social science. Her recent interests are multilayer networks, synchronization, optimization and graph spectra.
Recent years have witnessed the emergence of the multilayer network (MN) framework, which provides more accurate insights into the behaviors of complex systems possessing multiple types of relations among the same units. For example, individual or collective behavior of a society, that is modeled by individuals interacting through the Facebook and Twitter social networks, can be better understood by considering an MN consisting of layers representing the network of connections of people in each social media. The interactions within a layer (intra-layer connection) for this particular network model of a social system encode friendship relations between pairs of two people within each social media, whereas the interactions between the layers (inter-layer connection) represent the impact of interactions in one layer on the other (for example, when two people actively interacting by Facebook increase their Twitter activity driven by their Facebook activities. Another example of a real-world system, which inherently has multiple types of relations, is the brain. In the brain MN, one layer corresponds to a physical network, and another to a functional relationship among neurons. Furthermore, the physical layer can also itself a MN in the synaptic level. Neurons can be connected by chemical or electric synapses forming a brain MN. Recently, Internet routing protocol IPv4 and IPv6 autonomous systems have also been analyzed through MN framework. We perform optimized evolution of multilayer networks to make them better synchronizable. We show that one can control the behavior of the entire multilayer network by controlling properties of only one layer.
ETH Zürich, Switzerland
Petros Koumoutsakos has received an education in Naval Architecture (NTUA Athens, U.of Michigan), Aeronautics and Applied Mathematics (Caltech). He has conducted post-doctoral studies at the Center for Parallel Computing at Caltech and at the Center for Turbulent Research at Stanford University and NASA Ames. He was appointed as Chair for Computational Science at ETH Zurich in 2000 and is currently a fellow of the Collegium Helveticum. Petros is elected Fellow of the American Society of Mechanical Engineers (ASME), the American Physical Society (APS) and the Society of Industrial and Applied Mathematics (SIAM). He has held visiting fellow positions at Caltech, the University of Tokyo, MIT and at the Radcliffe Institute of Advanced Study at Harvard University. He is recipient of the Advanced Investigator Award by the European Research Council and led the team that won the ACM Gordon Bell prize in Supercomputing (2013). His team researches the how and what of computing as applied to problems ranging from fish swimming to nanotechnology and medicine. In 2018 Professor Koumoutsakos was elected as foreign member of the US National Academy of Engineering.
Computing is a domain of knowledge emerging from the fusion of models, algorithms, data and of course computers. From the prediction of weather to the analysis of massive amounts of data, Computing has become omnipresent in Science. Computing can be used to probe and understand complex systems in ways that may not be possible by observation or experiments. Computing can also be used to make predictions and take corresponding decisions. In this talk I wish to celebrate some successes of this mode of scientific inquiry and take time to discuss some questions.
Do we understand what is it that we are computing ? How certain can we be on our predictions ? What is the relevance of the computer output to the problem we wanted to solve ? Should we even care about such issues ?
I will argue that our times present a golden opportunity to answer such questions by the proper integration of Computing and Data Sciences. Computing is essential for the progress of humankind and we must understand its powers and limitations. I will argue that in times characterized by “automation” and “easy” data we must nurture human thinking (or Computing with and without Computers) for the present and future generations.
National University of Defense Technology, China
Born in April, 1963, Prof. Xuejun Yang is a distinguished expert in computer science and technology. He is the president of the Academy of Military Sciences, academician of the Chinese Academy of Sciences and professor in National University of Defense Technology. He works on researching and developing high-performance computer architecture and system software, as well as intelligent computing. He was the chief designer of a series of supercomputers including Tianhe-1A which ranked No. 1 on the TOP500 list in 2010. He proposed the heterogeneous parallel computer architecture integrating CPUs and stream processors, and made world-leading achievements in the fields of scalable shared-memory parallel computer architecture and beyond 64-bit floating-pointing computing. He also achieved breakthroughs in the fields of the rapid deployment and the reliability technologies of supercomputers for battlefield requirements. Prof. Yang has won the First National Science and Technology Progress Award, Team Innovation Prize, the first-class State Scientific and Technological Progress Award of China, the second-class State Technological Invention Award of China, Ho Leung Ho Lee Science and Technology Achievement Award, Tan Kah Kee Science Award.
The development of science and technology has entered the era of “Intelligence explosion”. The interaction and integration between artificial intelligence and other technologies are triggering a new revolution in science and technology. While the individual intelligence grows rapidly, artificial intelligence is moving to group intelligence. Group intelligence aggregates “many low-level agents” to form “high-level agent”, which has become the worldwide forefront and hot direction in the field of artificial intelligence research. This report analyzes the theories of group perception, group cognition, group decision-making, group dynamics and the corresponding optimization algorithms. It also studies the scientific issues and key technologies of group intelligence and proposes a micROS that can support group intelligence and its architecture design.