ECE NSERC USRA projects
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Project contact
(faculty member)
Project titleBrief description
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Lukas ChrostowskiSilicon photonics for quantum computingUsing the relatively mature silicon photonics technology, and very mature CMOS electronics technology, we are aiming to implement a quantum computer. We are using a cavity quantum electrodynamics (cQED) approach with single atoms implanted in silicon as qubits, 4K cryogenic operation in vacuum, mid-IR wavelengths, single photon sources and detectors, and possibly NEMS. We are quickly assembling a world-class team to tackle this immense challenge.
We need intense efforts in developing process design kits and Libraries using detailed electromagnetic device design, together with achieving significant process improvements in electron beam lithography fabrication necessary to realize the quantum silicon photonics vision.
We are recruiting in the areas of:
- photonic device and circuit design
- fabrication process innovation, statistical process control
- experimental equipment design and development, including automation, cryogenics, laser design
- photonic characterization and control
- packaging and integration with external optics and electronics
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John MaddenSmart skin for robotics and medical devicesHelp develop a technology that may be used to help Honda's ASIMO robot feel its environment, or be use to detect medical issues through a bed sheet. Project will involve the use of rubber and gels to create soft, stretchable and low cost sense electrodes for detecting touch, proximity, bend, shear, temperature, pressure and moisture.
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André IvanovOptimization Software for Cadmium Zinc Telluride (CZT) Scanner We are developing an optimization software focused on reactive force fields for molecular dynamics simulations. This project will involve the use of probabilistic optimization techniques such as Monte Carlo to optimize classical reactive forcefield parameters such that they match quantum mechanical computations on small sets of molecules and atoms containing Cadmium, Zinc and Tellurium (CZT). These forcefields will be used to model CZT radiation sensor characteristics. Such sensors can be applied to various medical imaging and transportation security scenarios (e.g., airport, container shipments). The incumbent should have experience in C++/Python software development and a background in chemistry and physics is preferred but not necessary.
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Karthik PattabiramanThingsJS: Dynamic IoT Middleware
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Karthik PattabiramanLetGo: Failure Recovery for High-Performance Computing ApplicationsHigh performance computing (HPC) represents an efficient way to aggregate massive computing power (i.e. supercomputers) for scientific workloads. Such systems generally require sustained focuses on fault tolerance and energy efficiency. Checkpoing/Restart is one of the most important techniques for failure recovery in HPC systems. The traditional checkpoint/restart approach regularly saves important application information, and, if an application crash is detected, it loads this previously stored information in an attempt to continue application’s execution. The system LetGo developed in our group, looks at this problem in a different way: if an error is detected, LetGo attempts to repair the error, and directly continue the application’s execution. We use simulations and performance modelling to show that with LetGo the application performs 10% - 20% more efficiently than without LetGo. The next step of the project contains three tasks: a). as HPC applications run on massively parallel supercomputers, to be useful LetGo has to serve these applications, b) It would be interesting to evaluate LetGo on applications with checkpointing systems such as Berkeley Lab Checkpoint/Restart (BLCR), and c). while we have shown that LetGo can work for a large number of applications, we still need to be able to reason about the correctness each particular LetGo repair heuristic. Through this project, the students will gain experience with parallel computing environments like large-scale clusters, parallel programming languages, classic system/application level fault tolerance mechanisms, and program behavior analysis.
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Julia RubinMobile Application SecurityModern application stores, such as Google Play and Apple App Store, screen mobile applications to identify and prevent malware from entering the store. In this project, we aim at developing novel automated techniques for identifying applications that exhibit malicious behavior. Relying on a combination of static and dynamic program analysis, information retrieval, and machine learning techniques, we build a just-in-time validation mechanism for mobile applications that runs on the user device and tracks application execution. The student working on this project will use existing application analysis frameworks, such as soot or asm, for instrumenting mobile applications, devise data structures for storing and retrieving this information in an efficient manner, and will analyze the collected information using statistical and qualitative methods. S/he will also inspect the recorded information for a number of already known malicious samples, in order to validate that such an approach can indeed be effective for identifying these anomalies. At the end of the project, the student will be familiar with mobile technologies and will be able to analyze and discuss major flaws in mobile applications. The student will also learn to build high-quality mobile applications himself/herself.
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Julia RubinMobile Energy-EfficiencyBattery lifetime is one of the major usability concerns of mobile devices. Existing research shows that suboptimal resource usage, e.g., cases when an energy-heavy resource is bound too early or released too late, is commonplace in Android applications. “Wasteful” applications can cumulatively consume up to several hours of battery life a day, without doing anything productive for the user. To address this problem, we investigate approaches for regulating energy consumption in mobile applications. This project explores the tradeoff between energy-efficiency and user experience. Relying on a combination of static and dynamic program analysis, machine learning and crowd-sourcing, we intend to analyze the user behavior over a period of time, collect application usage patterns, and use these patterns for inferring resource binding points that optimize for both usability and performance. The student working on the project will use existing application analysis frameworks for instrumenting mobile applications so that they log information about the user behaviour. The student will also devise data structures for storing and retrieving this information in an efficient manner. At the end of the project, the student will be familiar with mobile technologies and will be able to analyze and discuss major energy-related flaws in mobile applications. The student will also learn to build high-quality mobile applications himself/herself.
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Julia RubinFault-tolerant microservice-based architecturesMicroservice-based architecture is an approach to application development in which a large application is built as a suite of modular services. Microservice-based architectures are now commonly adopted by companies such as Google, Microsoft, IBM, Netflix, and others. Yet, if not carefully designed, faults in individual microservices might impede the stability of the entire system. Our research looks at topics related to optimizing microservice-based architectures. We use static analysis and dynamic monitoring to extract information from existing cloud. Using the extracted information, we provide a set of methods and tools for reasoning about service composition and integration, and for analyzing and refactoring microservice-based architecture in order to arrive to a more robust version. The student working on this project will devise automated analysis techniques for extracting information from containers (e.g., Docker), container managers (e.g., Kubernetes), and distributed tracing tools (e.g., Zipkin), storing in in an efficient manner, and using it to improve the quality of microservce-based applications. At the end of the project, the student will be familiar with cloud technologies and will be able to analyze and discuss major architectural decisions in microservice/cloud-based applications. The student will also learn to build high-quality microservice-based applications himself/herself.
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Julia RubinGit Merge ConflictsSoftware is often built by integrating components created by different teams or even different organizations. Such “borrowed” code can comprise up to 90% of a typical software system. Our research looks at topics related to the efficient and reliable development of compositional software. Specifically, this project focuses on integration conflicts in Git repositories. We use a combination of empirical research to learn a set of textual, compilation, and semantic conflict patterns from existing repositories and automated program analysis for predicting conflicts in new integrations. We also rely on machine learning technique to help classify conflicts with better precision. The student working on this project will use existing application analysis frameworks for analyzing public Git repositories, e.g., on GitHub. The student will also devise data structures for storing and organizing the retrieved information in an efficient manner, and approaches for using this info for identifying and preventing future conflicts. At the end of the project, the student will be familiar with program analysis methods and will be able to analyze and discuss properties of a good compositional software. The student will also learn to build high-quality applications himself/herself.
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Karen CheungTissue engineering and image-based drug screeningWe are developing a new cell culture system which can be utilized in preclinical studies for cancer. Our work aims to create more realistic tissue models in vitro than conventional two-dimensional (2D) monolayer culture, because one factor essential to obtaining meaningful data in high-throughput drug screening during drug discovery is to have a cell culture environment which reproduces the in vivo environment. Our work features three-dimensional (3D) cell culture, in which cells are embedded in a material that mimics the extracellular matrix. Dispersed tumor cells are seeded within hydrogels within an array of microfluidic chambers. After on-chip culture for several days, the cells proliferate and form multicellular aggregates. The undergraduate summer student will provide crucial assistance in generating the engineered tissues, acquiring images of the cells, and analyzing the cellular response to drug treatment.
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Karen CheungInkjet dispensing of living cellsWe use inkjet systems to dispense living cells for applications in tissue engineering and genomics. We aim to optimize the process of using commercially available, piezoelectrically actuated inkjet nozzles to reliably deliver precise numbers of cells. Living cells are suspended in a solution which is supplied to the nozzle. Our previous work has shown that cell aggregation and sedimentation due to gravity have a strong impact on the ability to print over long periods of time, and we overcame these challenges by replacing the buffer solution with a neutral density solution. However, the hydrodynamics within the nozzle during cell printing require further analysis. The summer student will assist in finding optimal waveforms for printing cell suspensions, acquiring data for cell tracking using microscopy and high speed imaging.
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Karen CheungMicrofluidic airway-on-a-chipWe are developing a new cell culture system which can be utilized in preclinical studies for chronic obstructive pulmonary disease (COPD). This project will be a collaboration with the Centre for Heart Lung Innovation (HLI) at the Providence Airway Centre at St Paul's Hospital. The summer student will provide crucial assistance in creating CAD models of the microfluidic system, building the prototype system for generating the smoke/airflow profiles that replicate physiological conditions, generating the engineered tissues, acquiring images of the cells, analyzing the cellular response to smoke exposure.
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Lutz LampeIn-band Full Duplex Power Line Communications: Implementation Using Software Defined RadiosContemporary practical communication systems, such as Wi-Fi, 3G/4G mobile communications, DSL broadband, and power line communications, operate in a
half-duplex or a frequency division duplex manner, wherein bidirectional data streams are separated either in time or frequency. In-band full-duplex operation doubles the throughput of such systems by enabling simultaneous transmission and reception over the same frequency band. This project aims to build such an in-band full-duplex enabled power line communication system using software defined radios by implementing customized self-interference cancellation algorithms to provide conducive signal-to-noise ratio conditions for meaningful signal reception. The student should have a strong background in digital communications and signals and systems, and programming experience in Python and/or Matlab are mandatory. Previous experience in working with USRPs using GNU Radio, MATLAB, or LabView will be highly beneficial.
in Dc dc converter
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Martin OrdonezControl of Power Electronic ConvertersPower electronic converters require closed-loop controllers to ensure the voltages and currents are within the desired ranges. In the past decade, there has been a clear transition towards the implementation of these controllers employing digital platforms. Increased reliability and enhanced performance can be achieved through digital controllers at the expense of a higher implementation cost. The main goal of this project is to enable the implementation of power converter controllers with low-cost microcontrollers. The student will undergo exhaustive study of existing low-cost microcontrollers that could potentially satisfy the computational requirements to control power converters. In the last stage of the project, a custom control card will be developed to validate digital control algorithms. This control card will be tested in the research lab’s state-of-the-art power converter platforms to verify its applicability to a wide range of power converter topologies and control strategies. Student’s Role: The student will develop microcontroller programming skills, gain strong insight on the requirements of digitally-controlled power converters, become familiar with the market availability of low-cost industrial grade microcontrollers, and gain significant experience in the implementation of basic power conversion topologies and the different stages involved.
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Peyman ServatiSmart textile for wearable health, sports and mixed realityWe have a number of projects related to developing smart textiles and wearables targeted to health monitoring, augmented and virtual reality, rehabilitation and sports. The projects are in collaboration with UBC Faculty of Medicine and Kinesiology and in relation with local and international industries.
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Peyman ServatiLow cost sprayable solar cellsThis project focuses on the development of sprayable solar cells based on the work in our lab and development of related technologies.
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John MaddenStretchable displayBuild a simple display that is stretchable. This will be composed of gels and elastic materials, along with patterned electrochromic eleemnts.
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John MaddenNerve cell activationActivate a neuron using a sensor, such that touch will generate sufficient electrical energy to stimulate a muscle response.
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André IvanovSecurity of IoT Systems
To work on the following topics by benefiting from the unique properties of the IoT nodes:
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- Authentication: exploring solutions for identifying the legitimate nodes in the network using consensus algorithms.
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- Authorization: finding and implementing methods to authorize devices while communicating with each other.
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- Intrusion detection: Formulating and implementing methods in current state-of-the-art simulators such as AurduPilot and SegMeter to find adversary attacks. Characterizing their attack model.
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Requirements:
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- Good programming skills (C, C++, Java, JS). Good communication skills.
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- Good Analytical thinking.
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- Good knowledge of embedded systems.
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- Wanting to explore and learn new ideas.
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André IvanovRouting Congestion in VLSI circuitsMachine learning is powerful computer science techniques which can derive knowledge from big data, and provide prediction. Since nanometer VLSI (Very-large-scale integration) design and manufacturing have extremely high complexity and gigantic data, there has been a surge recently in applying and adapting machine learning techniques in VLSI physical design. We are currently focusing on the routability of VLSI circuits. Global routing and detailed routing are two important design stages in physical synthesis flow, connect all components of the chip according to a "netlist". There has been a considerable gap between routing congestion model used in global routing and real congestion after detail routing. In short, complex design rules make it difficult for traditional congestion measurement. In order to overcome the limitation, we decided to adapt the machine learning methodology, which can capture multiple hard-to-notice factors and generate accurate models for predicting detailed routing congestion.
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Candidate should be familiar with C/C++, python, basic knowledge of digital chip design flow.
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