Programme.
Starting time: 13:00 UTC, 14:00 BST,
15:00 CEST, 09:00 EST, 22:00 JST
(The times below are in UTC)
12:45-13:00
Opening and welcome to WAISE 2020, Organisation Committee
Session 1: Machine Learning Uncertainty and Reliability
Chair: Orlando Avila Garcia
13:00-13:15
Revisiting Neuron Coverage and its Application to Test Generation, Matthias Woehrle, Stephanie Abrecht, Maram Akila, Sujan Sai Gannamaneni, Konrad Groh, Christian Heinzemann and Sebastian Houben
A Principal Component Analysis approach for embedding local symmetries into Deep Learning algorithms, Pierre-Yves Lagrave
13:15-13:30
A Framework for Building Uncertainty Wrappers for AI/ML-based Data-Driven Components,
Michael Kläs and Lisa Jöckel
13:30-13:45
Session 2: Machine Learning Safeguards
Chair: Rob Alexander
Rule-based Safety Evidence for Neural Networks, Tewodros A. Beyene and Amit Sahu
Safety Concerns and Mitigation Approaches Regarding the Use of Deep Learning in Safety-Critical Perception Tasks, Oliver Willers, Sebastian Sudholt, Shervin Raafatnia and Stephanie Abrecht
Positive Trust Balance for Self-Driving Car Deployment, Philip Koopman and Michael Wagner
Integration of Formal Safety Models on System Level using the Example of Responsibility Sensitive Safety and CARLA Driving Simulator, Bernd Gassmann, Frederik Pasch, Fabian Oboril and Kay-Ulrich Scholl
13:45-14:00
14:00-14:15
14:15-14:30
14:30-14:45
14:45-15:00
Comfort break
Chair: Simos Gerasimou
SafeDNN: Understanding and Verifying Neural Networks
Corina Pasareanu, NASA Ames and Carnegie Mellon University, United States
15:00-16:15
Comfort break
16:15-16:30
Session 3: Assurances for Autonomous Systems
Chair: Chih-Hong Cheng
A Safety Case Pattern for Systems with Machine Learning Components, Ernest Wozniak, Carmen Carlan, Esra Acar-Celik and Henrik J. Putzer
Structuring the Safety Argumentation for Deep Neural Network Based Perception in Automotive Applications, Gesina Schwalbe, Bernhard Knie, Timo Sämann, Timo Dobberphul, Lydia Gauerhof, Shervin Raafatnia and Vittorio Rocco
An Assurance Case Pattern for the Interpretability of Machine Learning in Safety-Critical Systems, Francis Rhys Ward and Ibrahim Habli
A Structured Argument for Assuring Safety of the Intended Functionality (SOTIF), John Birch, David Blackburn, John Botham, Ibrahim Habli, David Higham, Helen Monkhouse, Gareth Price, Norina Ratiu and Roger Rivett
16:30-16:45
16:45-17:00
17:00-17:15
17:15-17:30
New Ideas and Emerging Results
Chair: Zakaria Chihani
Dependability engineering concepts for autonomous AI-based systems, Georg Macher, Eric Armengaud, Davide Bacciu, Jürgen Dobaj, Omar Veledar and Matthias Seidl
Applying Heinrich’s Triangle to Autonomous Vehicles: Analyzing the Long Tail of Human and Artificial Intelligence Failures, Amitai Bin-Nun, Anthony Panasci and Radboud Duintjer Tebbens
Solving AI Certification in SAE G-34/EUROCAE WG-114, Mark Roboff
17:30-17:40
17:40-17:50
17:50-18:00
Comfort break
18:00-18:15
Plenary Discussion
Chair: Philip Koopman
18:15-18:45
Plenary Discussion: How Close Are We in Engineering Safe AI Systems?
18:45-19:00
Wrap Up & Best Paper Award
