Project C1: Combined Communication and Control of Mobile Networked Systems

Project C2: Deep Learning for 3D Computer Vision

Project C3: Software Developer Targeted Performance and Cost Management for Autonomic Cloud Applications

Project C4: Security and Privacy in Cloud Assisted Computing

Project C5: APODOSIS – Adaptive Data Summaries for Autonomous Streaming Systems

Project C6: Security and Privacy of Location-Based Services

Project C7: Functional Heterogeneous Systems

Link To Application Portal:

Application deadline: June 15 2017

Project C1: Combined communication and control of mobile networked systems

Supervisor: Paolo Falcone, Department of Signals and Systems – Chalmers University of Technology

Contact info: Phone +46 (0)31 772 1803, Mail: falcone@chalmers.se

Short Project description: Applications of mobile autonomous systems, such as self-driving cars, drones for patrolling and goods delivery, robots for rescue and operation in catastrophes, are ubiquitous in our society. Their operation is based on wireless networks, which can limit the performance of the overall system. The goal of this project is to develop a control design framework for networked mobile systems, where the motion control and the communication problems are solved simultaneously, rather than compensating for the limitations of the underlying network. As a result, the control task is not just subject to the fundamental limitations of the communication system, while rather prioritizes and negotiates the communication in order to limit the impact of information delays and losses on the overall system performance. The project will demonstrate the results on intelligent transportation applications.

Project C2: Deep Learning for 3D Computer Vision

Supervisor: Prof. Fredrik Kahl, Department of Signals and Systems, Chalmers

Contact info: Phone +46 31 772 50 57, Mail: fredrik.kahl@chalmers.se

Short Project description: The topic of this project is to develop new learning methods and mathematical models for the next generation of autonomous systems capable of understanding, navigating and mapping in 3D environments. In recent years, the performance of 2D recognition has dramatically improved due to Deep Learning, but today’s best-performing systems for 3D computer vision are based on purely geometric concepts, not using any recognition. There is no single, integrated modelling framework leveraging both geometry and semantics. The research will be focused on mathematical tools appropriate for the above challenge, hence a strong mathematical background is required. The work is relevant for many industrial applications, such as self-driving cars, augmented reality and autonomous robots.

Project C3: Software Developer Targeted Performance and Cost Management for Autonomic Cloud Applications

Supervisor: Philipp Leitner, Dept. of Computer Science and Engineering, Chalmers

Contact info: leitner@ifi.uzh.ch

Short Project description: Scale-out cloud services, such as Netflix or Microsoft Bing, often consist of hundreds of independent microservices running on thousands of virtual machines or containers. Deployment automation and self-management (e.g., through circuit breakers or autoscaling) are fundamental to the management of such systems. However, these autonomic principles have made testing and ops cost estimation at development time challenging. In this PhD project, the goal is to combine empirical and experimental research methods to devise approaches to test the autonomic behavior of changes to a cloud application prior to deployment. Further, models shall be investigated to estimate the impact of such changes on the financial costs of deployment, allowing to quantify the monetary costs of development decisions.

Project C4: Security and Privacy in Cloud Assisted Computing

Supervisor: Katerina Mitrokotsa, Dept. of Computer Science and Engineering, Chalmers

Contact info: Phone +46 31 772 10 40, Mail: aikmitr@chalmers.se

Short Project description: The topic of this project is the security and privacy issues of resource-limited devices (e.g., sensors) that rely on untrusted servers to perform computations. The student will develop efficient authentication and verifiable delegation of computation protocols that provide: i) provable security guarantees, ii) rigorous privacy guarantees. The overall aim of the project is to design and evaluate cryptographically reliable and privacy-preserving authentication and verifiable delegation of computation protocols. The research shall also consider the challenging setting where multiple clients outsource joint computations to untrusted cloud servers. Experience in one or more domains such as cryptography, design of protocols, secure multi party computation and differential privacy is beneficial.

Project C5: APODOSIS – Adaptive Data Summaries for Autonomous Streaming Systems

Supervisor: Marina Papatriantafilou, Dept of Computer Science & Engineering, Chalmers

Contact info: Phone +46 31 7725413 , Mail: ptrianta@chalmers.se

Short Project description: The project will address a core question of streaming big data applications in autonomous digitalized systems: if data arrives continuously from many sources and only a bounded portion of it can be temporarily persisted for analysis tasks that will be defined and run at a later stage, what should be persisted to maximize the utility of such analysis? As the volumes of data continuously generated in vehicular, energy and production systems are growing bigger, methods that can maintain appropriate summaries are needed. How to generate those in a fashion that is adaptive to the system behavior is challenging. The project will provide methods for efficient stream processing and data structures to facilitate that and to connect with real-world use-cases.

Project C6: Security and Privacy of Location-Based Services

Supervisor: Andrei Sabelfeld, Dept of Computer Science & Engineering, Chalmers

Contact info: Phone +46 31 772 1018, Email: andrei@chalmers.se

Short Project description: Location-based services/systems (LBS) see tremendous growth, with application from smartphones to autonomous vehicles and aircraft. This project is on rigorous techniques for security and privacy in LBS, including:

• security and privacy foundations of LBS: formal modeling and reasoning for LBS policies;
• application-, service-, and system-level mechanisms: enforcing security and privacy policies for LBS by such software-level techniques as information flow control (IFC), program analysis, and monitoring, and their integration with such hardware-level mechanisms as Isolated Execution Environments (IEE) and infrastructure for secure localization;
• cryptographic techniques for LBS: designing and scaling decentralized approaches, such as those enabled by secure multi-party computation.

Project C7: Functional Heterogeneous Systems

Supervisor: Mary Sheeran, Dept. of Computer Science and Engineering, Chalmers

Contact info: Phone: +46 (0)31 772 1013 Mail: mary.sheeran@chalmers.se

Short Project description: Heterogeneous systems with many types of computational units (multicores,GPUs,FPGAs,sensors,actuators) are hard to program. The typical approach is to use a hodge podge of different programming languages, which makes it difficult to guarantee global properties like functional correctness and security. This project will develop methods of programming heterogeneous systems using a single functional program, but multiple domain specific languages that generate code for the different computational units, as well as the necessary linking code and protocols. A key point is the use of Haskell’s expressive type system to separate nodes based on their roles, capabilities and locations. We will develop methods of verifying the resulting systems using both property-based testing and formal methods.