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Fault event detection through causal analysis of binary time series posté par Nokia

CDI - temps plein

Description de l'offre

Nokia is a global leader in the technologies that connect people and things. With state-of-the-art software, hardware and services for any type of network, Nokia is uniquely positioned to help communication service providers, governments, and large enterprises deliver on the promise of 5G, the Cloud and the Internet of Things. 
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About Nokia Bell Labs
Over its nearly 100-year history, Nokia Bell Labs has invented many of the foundational technologies that underpin information and communication networks and all digital devices and systems. This research has resulted in nine Nobel Prizes, four Turing Awards, three Japan Prizes and a plethora of National Medals of Science and Engineering, as well three Emmys, two Grammys and an Oscar for technical innovations. Nokia Bell Labs continues to conduct disruptive research focused on solving the challenges of the new digital era and innovating the technology that will define the next industrial revolution.

Internship: Fault event detection through causal analysis of binary time series

In general, RCA is a hard problem in complex systems, because it requires a deep knowledge of cause-effect dependencies among many features, physical and logical components the network nodes. In the data driven approach, where most of this knowledge is assumed to be unavailable a priori, a major difficulty can emanate from the fact that many of the variables are hidden or unknown. Furthermore, even in a fully observable system we are faced with the combinatorial explosion of cause-and-effect dependencies and the difficulty to collect enough information for distinguishing causal dependencies from spurious correlations.

The goal of this project is to explore techniques for causal analysis of binary (or discrete-valued, in a more general case) time series that represent local state change sequences of monitored network resources. We aim at deriving a causal graph that explains the relationships between these time series, whereas the occurrence of an original (source or root) fault can be considered as an external intervention into the system on a particular network resource that can causally propagate to other resources. More specifically, given as input a set of time series, our objectives is

1.detection of fault occurrences helped by the inference of high-level causal graphs before and after these external interventions,
2.Study of different data generating models such as Noisy-OR or dynamic Bayesian networks, structural equation models adapted to time-series, or models derived from formal methods (event generating models based on connected automata on Petri nets)
3.Experimentations with the synthetic data as well as with real alarm logs collected in operator networks.

The internship will be co-advised by Armen Aghasaryan (Nokia Bell Labs, Paris-Saclay) and Gregor Gössler (INRIA Grenoble). Candidates must have a strong interest in formal methods (concurrency theory, Bayesian networks) as well as have good skills for data intensive simulation and analysis.

The trainee will benefit from a large degree of autonomy regarding the evaluation and interpretation of results as well as the tuning of the algorithm. Outstanding work performed by the intern may lead to co-authorship in publications and can also be pursued in a PhD thesis.

Duration 6 months (full time)


Last year Master-level student (final project). Solid technical skills and background in at least some of the following

areas are required:

• Causal inference and modelling, Machine learning, Bayesian networks, Big Data analytics

• Analytics platforms, Spark and Spark streaming, Hadoop/MapReduce

• Python or Matlab Programming skills

Location of the internship: Nozay 91620
Site accessible from Massy RER station by public transport and Free buses departing from the Pont de Sèvres, Porte d'Orléans, Argenteuil, Chaville, Fontenay-le-fleury.

Imagine creating technology that has the potential to change the world. Working with us, you will have a positive impact on people’s lives and help to overcome some of the world’s most pressing challenges. We act inclusively and respect the uniqueness of people. At Nokia, employment decisions are made regardless of race, color, national or ethnic origin, religion, gender, sexual orientation, gender identity or expression, age, marital status, disability, protected veteran status or other characteristics protected by law. Nokia culture welcomes people as their true selves. Come create the technology to connect the world. 

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