- W. Murray Wonham (Distinguished Carl Adam Petri Lecture)
- Christel Baier
- Stephen A. Edwards
- Matthieu Latapy
- Kurt Lautenbach

Bio: W. Murray Wonham received the BEng degree in Engineering Physics from McGill University in 1956, and the PhD in Control Engineering from the University of Cambridge (UK) in 1961. From 1961 to 1969 he was associated with several US research groups in control, including the Research Institute of Advanced Studies (RIAS), Brown University's Department of Applied Mathematics, and NASA's Electronics Research Center. Since 1970 he has been a faculty member in Systems Control, with the Department of Electrical and Computer Engineering of the University of Toronto.

Wonham's research interests have included stochastic control and filtering, geometric multivariable control, and discrete-event systems. He is the author of "Linear Multivariable Control: A Geometric Approach" (Springer-Verlag: 3rd edn 1985), co-author (with C. Ma) of "Nonblocking Supervisory Control of State Tree Structures" (Springer-Verlag: 2005), and author of "Supervisory Control of Discrete-Event Systems" (www.control.utoronto.ca/~wonham), updated annually 1997-2013. He has published over 100 research articles in refereed journals and supervised over 60 Master's and PhD candidates.

Wonham's affiliations and awards include the following:

- Fellow of the Royal Society of Canada (FRSC)
- Life Fellow of the Institute of Electrical and Electronics Engineers (IEEE)
- Foreign Associate of the (US) National Academy of Engineering (NAE)
- Honorary Professor, Beijing University of Aeronautics and Astronautics (BUAA)
- University Professor Emeritus, University of Toronto
- Advisory Editor, Discrete Event Dynamic Systems
- Member, Professional Engineers of Ontario
- IEEE Control Systems Science and Engineering Award
- Brouwer Medallist of the Netherlands Mathematical Society

In this lecture we first introduce supervisory control theory for discrete-event systems (DES) in a framework of finite automata and regular languages, with emphasis on the criteria of nonblocking and maximal permissiveness. Also stressed is the importance of control modularity and transparency. Turning to Petri Nets (PN), we indicate how the counterpart control design problem can be posed and (in many but not all cases) solved using integer linear programming. Finally we discuss the feasibility of a "DES transform" approach by which the PN problem is first converted to a DES problem, and the DES solution converted back to a PN implementation. Here we point out several interesting issues for further research.

Bio: Christel Baier is a full professor and head of the chair for Algebraic and Logic Foundations of Computer Science at the Faculty of Computer Science of the Technische Universität Dresden since 2006. From the University of Mannheim she received her Diploma in Mathematics in 1990, her Ph.D. in Computer Science in 1994 and her Habilitation in 1999. She was an associate professor for Theoretical Computer Science at the University of Bonn from 1999 to 2006. She is a member of the DFG review board for computer science since 2012 and co-speaker since 2013. Since 2011 she is a member of Academia Europa.

Talk:

Probabilistic model checking is a well-established technique for the automated quantitative system analysis that has been applied successfully in various application areas, such as coordination algorithms for distributed systems, communication and multimedia protocols, biological systems, resilient systems or security.The talk reports on the experiences made in inter-disciplinary research projects where probabilistic model checking is applied for the analysis of the trade-off between several cost and reward values, such as energy and utility. The formalization of the relevant performance measures requires several concepts like quantiles, conditional probabilities and expectations and ratios of cost or reward functions that are not supported by state-of-the-art probabilistic model checkers.The talk will provide an overview of the challenges that we had to address and reports on our current work in this direction.

Bio: Stephen A. Edwards received the B.S. degree in Electrical Engineering from the California Institute of Technology in 1992, and the M.S. and Ph.D degrees, also in Electrical Engineering, from the University of California, Berkeley in 1994 and 1997 respectively. He is currently an associate professor in the Computer Science Department of Columbia University in New York, which he joined in 2001 after a three-year stint with Synopsys, Inc., in Mountain View, California. His research interests include embedded system design, domain-specific languages, compilers, and high-level synthesis.

Talk:

About ten years ago, integrated circuits hit a power wall: improvements in uniprocessor performance ceased and processor vendors began delivering multicore chips. While this allowed them to claim performance improvements, in reality, programmers were hard-pressed to realize them because it required a shift to parallel programs. Yet the switch to massive parallelism is not a panacea. Further performance improvements demand the use of circuitry more specialized than general-purpose processors: application-specific circuits that are mostly idle and can squeeze more computation per switching event. I propose synthesizing these application-specific circuits from the functional language Haskell. My approach -- rewriting to a simple dialect that enables a syntax-directed translation enables parallelization and distributed memory systems. A functional starting point is a more abstract, mathematically sound representation that enables precise reasoning about parallel algorithms and very aggressive optimization. In particular, Haskell's exclusive use of immutable data structures eliminates the parallel cache coherency problem: once data is created, it never changes. Transformations include scheduling arithmetic operations, replacing recursion with iteration, and improving data locality by inlining recursive types. I am developing a compiler based on these principles, which I describe.

Bio: Matthieu Latapy is a CNRS senior researcher, head of the Complex Systems departement of the LIP6 laboratory, hosted by University Pierre and Marie Curie, Paris, France. He works on all kinds of questions related to complex networks like the internet, the web, peer-to-peer exchanges, social networks, etc. He is particularily interested in the identification of research questions transversal to many of these objects (including metrology, analysis, modeling, and algorithms), and their resolution as well as practical applications. He introduced recently the concept of link streams to model the dynamics of interactions better than dynamic graphs, and works mainly on this topic now. He published numerous papers in high-quality international journals and conferences in computer science, physics, mathematics and sociology.

Talk:

Large software may be modeled as graphs in several ways. For instance, nodes may represent modules, objects or functions, and links may encode dependencies between them, calls, heritage, etc. One may then study a large software through such graphs, called complex networks because they have no strong mathematical properties. Studying them sheds much light on the structure of the considered software. If one turns to the analysis of the dynamics of large software, like execution traces, then the considered graphs evolve over time. This raises challenging issues, as there is currently no clear way to study such objects. We develop a new approach consisting in modeling traces as link streams, i.e. series of triplets (t, a, b) meaning that a and b interacted at time t. For instance, such a triplet may model a call between two modules at run time. Analysing such streams directly turns out to be much easier and powerful than transforming them into dynamic graphs that poorly capture their dynamics. We present our work in this direction, with directions for applications in software analysis.

Bio: Kurt Lautenbach worked in Petri’s group at University of Bonn (1966- 1968) and in Petri’s group at GMD (German National Research Centre for Mathematics and Computer Science) (1968-1979). He got his PhD in Mathematics at the University of Bonn in 1973 and was professor at the University of Bonn (1979-1988). He is currently full professor of Computer Science at University of Koblenz where he leads the Working Group on innovative Petri net theory which deals with current issues in the fields of modeling, simulation, analysis and diagnosis in Petri nets and their application in practice.

Talk:

The aim of this lecture is to introduce “Propagation nets” as a kind of Petri nets whose flowing objects are uncertain values. The approach is influenced by Bayesian networks (J. Pearl) and probabilistic Horn abduction (D. Pool). In contrast to Bayesian networks, the algorithms are not “hidden” but part of the nets. The net structure together with a simple firing rule allows uncertain reasoning in backward and forward direction, where backward and forward direction are dual to each other in terms of a Petri net duality. Propagation nets allow to deal with several kinds of uncertainties. This is shown for probabilities, intervals and fuzzy numbers