Evolving Critical Systems
Prof. Mike Hinchey, Lero – the Irish Software Research Centre University of Limerick, Ireland – Abstract: Increasingly software can be considered to be critical, due to the business or other functionality which it supports. Upgrades or changes to such software are expensive and risky, primarily…
Next-generation data-parallel dataflow systems
Prof. Frank McSherry, ETH Zurich – Abstract: The Naiad project at Microsoft Research introduced a new model of dataflow computation, timely dataflow, which was designed to support low-latency computation in data-parallel dataflow graphs containing structured cycles. This model substantially enlarged the space of data-parallel computations…
More is different: how complex networks lead to new emergent social behavior
Prof. Jorge M. Pacheco, Universidade do Minho – Abstract: The holy-grail of computational social science is to understand how societies behave as a collective, knowing how individuals interact with each-other. Conversely, if all we know is how societies behave collectively (as happens all too often…
Privacy-Preserving Event Stream Processing in the Cloud
Prof. Pascal Felber, Université de Neuchâtel, Institut d’informatique – Abstract: Stream processing provides an appealing paradigm for building large-scale distributed applications. Such applications are often deployed over multiple administrative domains, some of which may not be trusted. Recent attacks in public clouds indicate that a…
Folk Theorems for Multi-Agent Systems
Prof. Michael Wooldridge, University of Oxford – Abstract: The Nash Folk Theorems are a collection of related results that characterise the Nash equilibria that can be sustained in repeated games. As the name suggests, the Folk Theorems are technically simple, but this simplicity belies the…
Behavioral Signal Processing: Enabling human-centered behavioral informatics
Prof. Shrikanth Narayanan, University of Southern California, USA – Abstract: Audio-visual data have been a key enabler of human behavioral research and its applications. The confluence of sensing, communication and computing technologies is allowing capture and access to data, in diverse forms and modalities, in…
Elastic and Fault-Tolerant Stream Processing in the Cloud
Prof. Peter Pietzuch, Department of Computing, Imperial College London – Abstract: As users of “big data” applications want fresh processing results, we witness a new breed of stream processing systems that are designed to scale to large numbers of cloud-hosted machines. Such systems face new…
What happens when you let reality inspire your research?
Prof. Paulo Veríssimo, University of Lisbon, Portugal – Abstract: It is not often that one finds concrete problems capable of inspiring really advanced research. Computing and communications, having become commodities which societies largely depend on, created such an opportunity in what concerns their security and…
Disciplined Approximate Computing: From Language to Hardware, and Beyond
Prof. Luis Ceze, University of Washington, USA – Abstract: Energy is increasingly a first-order concern in computer systems. Exploiting energy-accuracy trade-offs is an attractive choice in applications that can tolerate inaccuracies. A key challenge, though, is how to isolate parts of the program that must…
Talk1:The OpenRISC experience & Talk2:Machine Guided Energy Efficient Compilation
Dr. Jeremy Bennett , Embecosm, UK – Abstract: Dr. Jeremy Bennett brings us two short lectures: the first one is under the theme “Free softcores, tools and toolchains: The OpenRISC experience”, the second short lecture is about “MAGEEC: Machine Guided Energy Efficient Compilation”. Free softcores,…
Mathematics, Physics & Machine Learning Seminar Series (Online)
The Mathematics, Physics & Machine Learning seminar series has started on October 2020 and runs until March 2021.
The seminars aim to bring together mathematicians and physicists interested in machine learning (ML) with ML and AI experts interested in mathematics and physics, with the goal of introducing innovative Mathematics and Physics-inspired techniques in Machine Learning and, reciprocally, applying Machine Learning to problems in Mathematics and Physics.
Attendance is free but registration is required.
More information is available here.
International European Conference on Parallel and Distributed Computing
The 27th International European Conference on Parallel and Distributed Computing (Euro-Par 2021) will take from August 30 to September 3 2021 in Lisbon.
Euro-Par is the prime European conference covering all aspects of parallel and distributed processing, ranging from theory to practice, from small to the largest parallel and distributed systems and infrastructures, from fundamental computational problems to full-fledged applications, from architecture, compiler, language and interface design and implementation, to tools, support infrastructures, and application performance aspects.
The 2021 edition of Euro-Par will be organized as a collaboration between INESC-ID and Instituto Superior Técnico (IST).
– Abstract Submission: February 5, 2021
– Paper Submission Deadline: February 12, 2021
– Author Notification: April 30, 2021
– Camera-Ready Papers: June 6, 2021
More information is available here.