Æ»¹ûÒùÔº

Description

The project aims to develop a smart mandibular advancement device. It will be based on flexible hybrid electronics and will monitor physiological parameters such as heart rate, breathing pattern, blood oxygen saturation , head accelerometry and EEG signal from inside mouth. The flexible hybrid electronic part will be integrated with a custom made mandibular advancement device. The undergraduate summer student will assist a postdoc to design the flexible PCB, integrate the electronic parts on the PCB and collect data using the device. The student will also help a PhD student to design and fabricate EEG electrodes for this project.

Tasks per student

Tasks -Design PCB -Integrate electronic components on the PCB -Design and fabricate EEG electrodes -Test tthe smart mandibular advvancement device and collect data with it

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Number of positions

1

Academic Level

Year 3

Description

Energy storage is viewed as one of the key ingredients to the decarbonization of the energy sector through electrification. One major challenge electricity system planners have is how one can represent and determine the optimal storage assets in long-term planning studies. In this project, the student will investigate novel ways to represent and size aggregate system-level storage technologies in deeply decarbonized electricity systems.

Tasks per student

The student will work at extending a data-driven long-term generation capacity approach currently under development in the power engineering lab. This will first involve work on manipulating large datasets of wind power generation, solar power generation and demand time series. The primary goal will be to determine sets of necessary data manipulations to determine proxy constraints that energy storage assets need to meet. An application of this method in optimizing system-level storage in a toy power system.

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Number of positions

1

Academic Level

Year 3

Description

At the Intelligent Automation Lab, we recently developed a cutting-edge electrical vehicle transmission prototype. The numerous parts are coming in, and we are looking for help to assemble the transmission, prepare the data-acquisition, calibrate the sensors, conduct some experiments, and process the data. The intern will work in close collaboration with the PhD student in charge of the project. This is a good opportunity to learn the nuts and bolts of getting high quality experimental results, as well as some new techniques of system identification from experimental data. Our research focuses on the machine learning control of the transmission dynamics. Therefore, these experiments are a crucial stepping-stone toward new discoveries.

Tasks per student

Assemble the transmission, prepare the data acquisition, calibrate the sensors, conduct some experiments, and process the data. The intern will work in close collaboration with the PhD student in charge of the project.

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Number of positions

1

Academic Level

No preference

Description

Haptic effects are increasingly used in consumer products, whether to deliver notifications of incoming messages, communicate information to deaf-blind individuals through their hands, or enrich videogame experiences. To produce these effects, various actuation technologies have been developed, including eccentric rotating mass, linear resonant actuators, and piezoelectric membranes, among others. Despite extensive use of these devices in consumer technologies, there has been surprisingly little in the way of investigation and comparison of their power consumption, and how power relates to the perceived intensity of the stimuli they provide. Complicating matters, such perception is dependent on frequency of the stimuli, the body location where the stimuli are delivered, and the size of the contact area. This project aims to overcome this limitation in current domain knowledge.

Tasks per student

1. development of testing procedure and test bench 2. carry out a preliminary such test procedure 3. publish the results as a valuable resource to the haptics community.

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Number of positions

1

Academic Level

No preference

Description

This project involves the exploration of novel strategies for auditory rendering in a mixed reality scenario such that the computer-generated information is delivered to the user in a more effective manner, facilitating awareness of such information while minimizing interference with the user's attention to other activities. The student should be familiar with the basics of signal processing techniques, and be comfortable rapidly prototyping different design concepts. Mobile development experience would be particularly useful.

Tasks per student

software prototyping conducting user tests to evaluate the prototype designs

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Number of positions

1

Academic Level

No preference

Description

Treating patients with schizophrenia for auditory hallucinations has traditionally required multiple trials of antipsychotic medications with approximately one in three patients being resistant to antipsychotic therapies. An alternative called Avatar Therapy has been developed and shown to effectively reduce the distress and helplessness associated with auditory hallucinations. While Avatar Therapy shows great promise, there are many open questions as to the requirements for optimal delivery of this treatment. Similarly, many potential enhancements to how avatars are rendered to the patient remain to be tested. Exploration of these questions and enhancements requires development of a mixed reality platform that offers to the therapist the ability to easily adjust various parameters of the avatar(s). We will iteratively design, implement, and test such a platform, and then apply the knowledge gained to an augmented reality version of the platform suitable for use outside of the therapist's office. The resulting intelligent medical device will offer the possibility of providing therapeutic benefits to patients in their day-to-day activities.

Tasks per student

1. Haptic augmentation: prototyping and testing wearable technologies suitable for reproducing the sensation of someone touching or grabbing your arm or shoulder 2. Biosignals-based quantitative evaluation: making use of ocular biomarkers and other physiological indicators of stress to measure affective state

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Number of positions

2

Academic Level

No preference

Description

This project aims to leverage the benefits of head-worn, panoramic imaging systems to provide navigation assistance for the visually impaired community, 1) safely guiding users during intersection crossing to avoid veering, which can be dangerous and stressful, and 2) helping them navigate the last few meters to doorways they wish to enter. Our proposed approach combines a machine learning strategy leveraging existing image datasets, possibly augmented by crowdsourcing, and iterative design of the feedback mechanisms. This is informed by our lab's experience with sensor-based intersection-crossing assistance systems, and in developing the Autour app, which provides a real-time description of street intersections, public transport data, and points of interest in the user's vicinity. Students should have experience in machine learning, mobile software development, and interest in assistive technologies.

Tasks per student

(Both sub-projects consist of the same research tasks, but applied to different problems) 1. compilation of suitable training data 2. model development 3. feedback testing

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Number of positions

2

Academic Level

No preference

Description

Our lab works on the design of wearable haptic devices that can be attached to the body or inserted into regular clothing, capable of sensing human input and delivering richly expressive output to the wearer. We are particularly interested in applications to rehabilitation therapy, sports training, information communication, virtual reality, and mobile gaming. Learning a new motor skill typically requires repeated physical training, cognitive training, and retention. This project investigates the use of haptic feedback to improve learning of new dance steps, as a template example of other coordinated motor skills. For this activity, it is critical to have a precise idea of rhythm, spatial movement, and body posture during the performance. Often these factors emerge while practicing movements intermittently. However, in the process of traditional dance learning in a classroom, it is difficult for novice dancers to follow the specifics of rhythm, spatial movement and body posture, while in sync with the instructor, at a defined pace. Can these problems be reduced using vibrational feedback delivered through haptic footwear?

Tasks per student

design of haptic cues to convey changes in weight transfer, rhythm and direction of movement experimentation on benefits of haptic feedback on dance learning

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Number of positions

1

Academic Level

No preference

Description

To accurately and efficiently model the electromagnetic fields within sophisticated microstructures of modern engineering systems and devices, high performance computing (HPC) methods, such as parallel and distributed simulations on emerging multicore/manycore platforms, are deemed promising for overcoming current computational bottlenecks. While robust and reliable 3-D automatic mesh generation procedures and solution strategies for electromagnetics are emerging, major computational challenges still remain for effective parallel and distributed 3-D adaptive finite element methods (AFEMs). Uniting AFEMs and HPC methods to achieve high gains in efficiency makes it possible to solve previously intractable problems; however, effective implementation of such techniques is still not well understood. AFEMs for parallel/distributed computing introduce complications that do not arise with simpler solution strategies. For example, adaptive algorithms utilize unstructured meshes that make the task of balancing processor computational load more difficult than with uniform structures.

Tasks per student

The students in this project will research and develop efficient parallel and distributed adaptive algorithms for unstructured meshes that use complex data structures for implementing dynamic load balancing strategies for HPC environments such as multicore/manycore architectures. The students’ role will include involvement in all aspects of the engineering research process for this project including actual implementation of algorithms as executable code.

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Number of positions

1

Academic Level

Year 2

Description

The polymerase chain reaction (PCR) is widely used to amplify and identify DNA samples. Most commercial PCR systems require over an hour to produce a result, but we have recently demonstrated a new approach that uses laser heating of gold nanoparticles to drive the reaction. This has allowed us to produce test results in under five minutes and opens the technique up to point-of-care applications. In addition we have demonstrated a new technique to optically monitor the amplification of DNA during the reaction by measuring UV light transmittance. Specifically we measure the decrease in 260 nm optical absorption as DNA bases (deoxyribose nucleoside triphospate molecules (dNTPs)) are converted to double stranded DNA. By avoiding the use of fluorescent molecules this greatly simplifies the process. The goal of this SURE project is to develop a lock-in detection technique for UV monitoring in order to further improve sensitivity. Some of the research will be undertaken at the Lady Davis Research Institute of the Jewish General Hospital.

Tasks per student

Student 1: Adapt UV LED driver to deliver sinusoidally modulated current to LED and measure modulated signal Student 2: Insert lock-in detector into system and measure the filtered signal Both students: Develop complete system for modulation and detection, and use to measure different concentrations of dNTP molecules based on UV transmittance.

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Number of positions

2

Academic Level

No preference

Description

Optical microcavities are very high quality factor optical resonators which can be very sensitive to changes in their surrounding environment. By functionalising them with a suitable surface chemistry they can be used as sensors to detector specific biological or chemical molecules. Current microcavity sensors need either tunable lasers or optical spectrum analysers to operate but we are developing an approach which avoids the need for these for these by measuring the response of the resonator in the time domain rather than the frequency domain. In this approach, we modulate the optical signal at RF frequencies and then use RF detection methods to measure the attachment of the target molecules to the sensor. In this project the students will work on the design of a technique to obtain multiple measurements from a single light source that interrogates multiple resonators. The project will consist of numerical modeling and experimental validation.

Tasks per student

Student 1: Develop a numerical model of RF modulation and detection scheme, using either MATLAB or a dedicated RF modeling tool Student 2: Work alongside a graduate student to implement RF modulation and detection and compare with modeling results

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Number of positions

2

Academic Level

Year 1

Description

In this multi-segment on-going research project, we consider how to design a broadband wireless access communications system that can adaptably adjust itself to the continuously changing complex environment by using machine learning (ML) techniques. We aim to explore the potential of applying ML techniques to harvest relevant environmental information for improving the resource allocation, performance and operation of the corresponding broadband wireless access communications system. Relevant environmental information can include weather (e.g., rain, snow, fog, temperature, etc.), terrain (e.g., user locations, relative positions, buildings, obstacles, etc.), propagation (e.g., power, frequencies, etc.), social relationships (e.g., user groups, social networks, etc.) Various ML-based algorithms within a prototype testbed will be developed for the specific topics such as 3D channel modelling/estimation, hybrid ARQ, hybrid massive-MIMO precoding/beamforming, etc., to demonstrate the effectiveness of the Artificial Intelligence (AI)-augmented systems in terms of performance benchmarks such as energy consumption, increase in achievable capacity, reduction in interference, etc. Students will have a chance to understand various new concepts and development tools in both wireless communications (channel modelling, antenna array, beam forming, MIMO, etc.) and machine learning (deep neural network, reinforcement leaning, etc.), and to be involved in practical prototype development, and testing. As an example, one sub-project aims to make use of both the terrain and weather information available in many sources such as Google map, online meteors, to develop a ML-based channel estimator for dynamic resource allocation in a broadband wireless access communication system.

Tasks per student

Study the general concepts of ML and wireless communications. Learn how to search for and read scientific papers on a given signal processing or machine learning methods. Investigate Matlab toolboxes, PyTorch, Keras, Tensorflow, and DSP/FPGA hardware for possible applications to algorithm/prototype implementation. Assist in implementation and testing algorithms/prototypes, and in collecting, documenting and commenting the test results. The following skills and experiences are great assets: software development/testing, antenna design, Matlab, Python, VHDL, etc.

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Number of positions

3

Academic Level

Year 2

Description

Orbital Angular Momentum (OAM) has been considered to be one of the candidate transmission techniques for solving the broadband demand issue. In this ongoing research project, we aim to develop an OAM-MIMO prototype for ultra high-speed wireless communications. Studies and development of this OAM-MIMO prototype include considerations in antenna designs, wireless channel modeling, resource allocation algorithms. A testing environment will be developed to conduct prototype performance testing/evaluation by using both simulations and measurements.

Tasks per student

Study the general concept and characteristics of Orbital Angular Momentum at radio frequencies. Learn how to search for and read scientific papers on a given signal processing or antenna design subject. Leverage Matlab, antenna designs, DSP/FPGA hardware to implement the testbed platforms for OAM. Learn how to test functional operation and performance of the developed testbed, and to collect, document and comment on the test results. The following skills and experiences are great assets: software development/testing, antenna design, Matlab, VHDL, etc.

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Number of positions

2

Academic Level

Year 2

Description

Full-Duplex Massive Multi-Input Multi-Output (FD-massive MIMO) Active Antennas Arrays (AAA) are considered for the next-generation broadband communications. Using a massive number of antenna elements can (i) help to adaptively create narrow beams continuously steered to follow the target user while avoiding interference from other users, (ii) increase the communications range, and system capacity. The smart AAA system can follow the mobile user based on (i) a hybrid 2-stage digital and RF precoding structure to reduce the complexity, and (ii) a full-duplex operation for simultaneous transmission/reception over a frequency slot to enhance both spectrum utilization and latency. In this on-going project, we investigate, design and test new promising antenna 3-dimentional structures (such as metamaterials, EBG, dielectric filled, etc.), with integrated power and low noise amplifiers, as well as RF combiners/splitters and smart DSP based control sub-system. The hardware testbed consists of powerful multi-FPGA, multi-microprocessor, and RF Analog-to-Digital Converter (ADC) and Digital-to-Analog Converter (DAC) modules to be programmed with digital signal processing algorithms for transmission and reception/detection of real wireless communications signals.

Tasks per student

Study the general concept of Full-Duplex massive MIMO, radio-wave propagation, antenna design and simulation; learn the operation of the antenna design and simulation CAD tools HFSS, Matlab, PCB/DSP/FPGA design tools; prepare the simulation set-ups; assist graduate students and/or research associates to evaluate/analyze simulation results.

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Number of positions

3

Academic Level

Year 2

Description

Multi-Input Multi-Output (MIMO) has been used in wireless systems such as LTE, WiMAX, Wi-Fi. Full–Duplex massive-MIMO (FD-massive MIMO) is considered for the next generation cellular communications (especially to support broadband Industrial IoT, M2M applications). In this on-going project, we measure and characterize MIMO Self-Interference channels in both microwave bands (for wider signal penetration application) and mmWave bands (for wider bandwidth, high peak data rates applications) and different practical scenarios in order to understand the implications on the FD-MIMO design requirements, in particular, on RF self-interference cancellation. We will investigate various types of channel environments: controlled free-space (e.g., in anechoic chamber), simulated rich scattering (e.g., reverberation chamber), or practical indoor and outdoor environments. Students will have a chance to understand MIMO systems, Self-Interference Canceller design, Self-Interference and Intended Signal channel measurements, and to work with real-life measurement facilities and testbeds..

Tasks per student

Study the general concept of massive-MIMO, radio-wave propagation in free-space and in rich-scattering environments; learn the operation principle of measurement equipment/facilities such as vector network analyzer, spectrum analyzer, vector signal generators, anechoic chamber, reverberation chamber and/or MIMO testbeds; prepare measurement set-ups; assist graduate students and/or research associates to evaluate/analyze measurement/simulation results (e.g., using Matlab).

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Number of positions

1

Academic Level

Year 2

Description

For power-efficient operation, RF Power Amplifiers (PA) should operate near the saturation region, but this creates non-linear behaviors and distortions in amplified complex signals. Typical approach to balance power efficiency and performance degradation is to use PA linearizers. Non-linear power amplifier with memory is challenging to linearize using conventional models and techniques. In this project we will investigate, develop, simulate and test Deep Neural Network (DNN)-based algorithms to linearize typical power amplifiers with memory.

Tasks per student

Study about Power Amplifier characteristics, characterization, measurements and Subsequent Modeling in Matlab. Learn about typical PA parameters such as: gain compression (P1dB compression point), Amplifier Saturation Output Power (P3dB), IMD, IIP3, OIP3 (input/output third-order intercept points), AM/AM and AM/PM distortion. And also about other concepts such as: ACPR (for modulated signals, like QPSK or QAM) and Error vector magnitude (EVM) (for modulated signals, like QPSK or QAM). Review literature other conventional and new ML based PA linearization techniques.

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Number of positions

1

Academic Level

Year 2

Description

The limited Software Quality Assurance (SQA) resources of software organizations must focus on software modules that are likely to be defective in the future. To that end, defect prediction models are trained using historical data to identify defect-prone software modules (e.g., methods or files). After being trained using data from historical releases, defect prediction models can be used to prioritize SQA effort according the predicted defect proneness of the modules of a future release. The techniques and studies in the defect prediction literature tend to focus on source code files when making predictions. However, defects may arise in other software artifacts as well. For example, a bug in a build system file can cause software releases to be incorrectly assembled, leading to, e.g., application crashes. In this project, we will explore how defect prediction can be adapted to the context of predicting defect-prone areas of "secondary" software artifacts (e.g., build systems, test code, infrastructure scripts).

Tasks per student

The successful applicant will be expected to: - Use a high-level scripting language (e.g., Python, Ruby) to automate the collection of defect data from historical software archives like version control (e.g., Git) and issue trackers (e.g., JIRA) - Clean the data using best practices for machine learning/statistical analysis - Use machine learning and statistical techniques to analyze the data (e.g., R, Python's Scikit Learn)

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Number of positions

1

Academic Level

No preference

Description

Semiconductor homojunctions and heterojunctions composed of atomic layers offer new degrees of freedom for engineered semiconductor junctions beyond that of traditional compound semiconductors. In this project, homojunctions and heterojunctions composed of the transition metal dichalcogenides WSe2 and WS2 will be designed, assembled, and characterized electronically. The goal of this work is to verify that clean atomic interfaces can be assembled by exfoliation and stamping methods, and to subsequently apply this method to the fabrication of high electron mobility transistor structures.

Tasks per student

The students will each: 1) use Anderson's rule to design pn homojunctions and pn heterojunctions for vertical charge transport and lateral charge transport experiments 2) assemble the homojunctions and heterojunctions using a PDMS based stamping system incorporating piezo-control, localized heating, and optical microscope 3) contact the homojunctions and heterojunctions using electron beam lithography 4) measure the I-V and C-V characteristics versus temperature, applied bias, and if time avails itself, magnetic field

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Number of positions

2

Academic Level

No preference

Description

Flicker noise, a manifestation of charge fluctuation, is often the limiting noise source in low-frequency potentiometric sensors. In this project, flicker noise will be measured and analyzed using cross-correlation and auto-correlation methods. Potentiometric ion sensors, consisting of functionalized large area monolayer graphene transistors with multiple contacts will be studied. The goal of the project is to identify the various contributing sources of charge fluctuation, and to use this knowledge to develop graphene transistors with lower noise floor for improved precision in potentiometric sensing.

Tasks per student

The student will: 1) Automate a noise measurement system to acquire voltage versus time data and systematically vary potentials. 2) Develop software to calculate auto-correlation and cross-correlation functions, applying knowledge of FFT, windowing functions, and basic theory of power spectral density and correlation functions. 3) Acquire and analyze correlation data from monolayer graphene transistors, to identify the dominant sources of charge fluctuation in these transistors (eg. contacts, channel bulk, channel edges, substrate, superstrate). 4) Extend the system to automate the detection of discrete sensing events, with the aim of achieving single ion detection sensitivity.

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Number of positions

1

Academic Level

No preference

Description

Fresh water sources remain under-sampled in space and time due to the difficulty in achieving reliable, precise, and accurate sensors suitable for field studies. The goal of this project is to test wirelessly connected ion sensitive graphene field effect transistor arrays in the laboratory and in the field, with an emphasis on understanding sensor reliability.

Tasks per student

The student will work in a team to conduct tests of the precision, accuracy, and reliability of ion-sensitive graphene field effect transistor arrays in a laboratory environment, and potentially in an external field environment.

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Number of positions

1

Academic Level

No preference

Description

With the goal of establishing a more sustainable energy future, the penetration of various renewable energy sources has been continuously growing. However, the volatile nature of wind and solar power results in stability and security concerns of power grids. The aim of the project is to investigate the impacts of the randomness of renewable energy sources on power system voltage stability. The stochasticity of renewable energy sources can be modeled by stochastic differential equations in power system stability study. The impacts of the randomness on voltage stability, therefore, can be investigated by applying the theory of stochastic differential equations. The student will run Monte Carlo simulations to validate the analytical results obtained from the theory of stochastic differential equations in power system voltage stability assessment. The student is expected to have a good background knowledge in probability, statistics, stochastic process, and linear algebra. It is required that the student is comfortable using Matlab and it is preferred that the student is proficient in programming.

Tasks per student

1. Study the modeling of the randomness of the renewable energy sources in power system voltage stability assessment; 2. Study the fundamentals of stochastic differential equations; 3. Run Monte Carlo simulations to validate the analytical results obtained from the stochastic differential equations in power system voltage analysis.

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Number of positions

1

Academic Level

Year 3

Description

This project deals with generating ultraviolet (UV) light by injection electrons into semiconductor nanostructures. This project is driven by the need of sustainable, efficient, and compact UV light sources, for a wide range of applications such as non-light-of-sight communications, sensing, sterilization, among others. Replacing conventional UV light sources (that rely on toxic materials and have low efficiencies) with semiconductor UV light sources is positioned to be the next revolution in photonics. Specifically, the student will look into the reliability issue of UV light emitting devices with semiconductor nanostructures, with the expectation of identifying limiting factors for device reliability. This summer project opens to students at all levels, but the student should have very basic knowledge in electrical and optical properties of semiconductor materials, charge carrier transport, and LEDs. That being said, the evaluation is not based on your level, but your knowledge.

Tasks per student

1. Literature review and understand electrical and optical properties of GaN based light emitting devices 2. Learn and perform device fabrication 3. Device performance characterization, regarding to their electrical, optical, and thermal properties

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Number of positions

1

Academic Level

No preference

Description

Multiple Sclerosis is the most common neurodegenerative disease affecting young people. Currently, there is no cure. There is a significant unmet need to define robust and sensitive outcome predictors for progressive MS, defined as progressive worsening of neurological function (accumulation of disability) over time. Prof. Arbel is part of an interdisciplinary collaborative research network, comprised of a set of researchers from around the world, including neurologists and experts in MS, biostatisticians, medical imaging specialists, and members of the pharmaceutical industry. The team recently received a Collaborative Network Award by the International Progressive MS Alliance (IPMSA). The objectives of the grant include: (1) the federation of the first large Magnetic Resonance Image (MRI) progressive MS dataset (~40,000 patients over time) from hospitals around world and from almost all large phase 3 clinical trials for progressive MS and (2) the development of new Magnetic Resonance Imaging (MRI) markers for predicting Multiple Sclerosis disability progression for use in clinical trials. Professor Arbel’s team is currently developing new machine learning techniques to automatically discover (MRI) markers for disability prediction in progressive MS and as an outcome measure in early phase trials to facilitate drug discovery. Specifically, her team has begun to develop new deep learning frameworks that are completely data-driven, in which latent image features are identified using large amounts of imaging data. Supervised learning will result in the identification of features predictive of future clinical progression.

Tasks per student

The goals of the project are to explore methods to visualize the resulting imaging markers associated with clinical progression in order to permit their clinical interpretation by neurologists. The student will work closely with graduate students and Research Assistant in Prof. Arbel’s lab and with members of the collaborating teams, particularly at the Montreal Neurological institute.

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Number of positions

2

Academic Level

Year 3

Description

An optical processor allows to accelerate the data processing required in deep learning. Through photonic integration on a chip, the optical processor can be embedded within a modern computer platform used in applications using artificial intelligence (AI). The proposed project is in collaboration with Prof. Brett Meyer in the development of AI hardware that embeds optics. The student must demonstrate excellent communication, resourcefulness, and teamwork skills. We will provide the student with an exciting research environment where we exchange ideas and share knowledge.

Tasks per student

Assist in the development of AI hardware that embeds optics.

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Number of positions

1

Academic Level

Year 3

Description

Light with its photons allows for enhanced communication with great data transmission capacity, an important asset in today’s digital world. Optical devices are experiencing an impressive level of integration leading to exciting new possibilities. New design methodologies are required which must be experimentally validated. The proposed project to the undergraduate student relates to the design methodology development of photonic integrated chips exploiting machine learning algorithms. The student must demonstrate excellent communication, resourcefulness, and teamwork skills. We will provide the student with an exciting research environment where we exchange ideas and share knowledge.

Tasks per student

Assist in the design and experimental validation of photonic integrated circuits

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Number of positions

1

Academic Level

Year 3

Description

JAMScript is a language for developing programs for Internet of Things (e.g., smart vehicles) that with clouds and edge computing systems. A large-scale computing platform that is created using clouds, edge servers, and IoT need efficient resource scheduling methods. To do resource scheduling, we need to know the locations, loadings on the servers and also the task execution times. This project will look into instrumenting the language runtime to get progress markers at runtime and using these progress markers to determine the predicted execution times of tasks.

Tasks per student

Build performance tracing probes into JAMScript. Get the traces generated from sample application runs and train neural networks. Use the neural networks to predict the execution times of future tasks. Estimate the accuracy of the predictions using representative JAMScript programs.

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Number of positions

1

Academic Level

No preference

Description

Mbed OS is an embedded operating created by arm for Internet of Things. It is a Real-time Operating System (RTOS) that works in highly memory constrained ARM Cortex-M micro-controller based boards. In this project, you will port the C side of the JAMScript language runtime to this operating system. Unlike a full fledged OS Linux, the Mbed OS is highly feature restricted. As a result, you need to fundamentally redesign some of the components of the JAMScript runtime to get it running in Mbed OS. Although the Mbed OS is supporting many major features you can find in a normal OS, we need to revise a lot of the code base to port the C side of JAMScript over to Mbed OS. Some third party supplied components have to be replaced or done away with. You need to undertake this project if you are really passionate about embedded operating systems and would like really learn a state-of-the-art embedded OS by mapping a complex application. A group two highly motivated students can complete this project and learn a lot from it. This is for embedded systems enthusiasts or those who want to be enthusiasts.

Tasks per student

Study the C runtime of JAMScript. Identify the dependencies and remove unnecessary libraries from JAMScript runtime. Divide the JAMScript runtime into core components. Port one component at a time and test it on the target architecture.

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Number of positions

2

Academic Level

Year 3

Description

This project will extend the JAMScript runtime to support real-time audio processing tasks. There are several parts to the project. First is hooking up audio capture and processing into JAMScript programs. JAMScript is naturally a distributed language. So, we can capture with multiple sensors at the same time. There could be coordinated capture problem to gather audio signals at the same time across the different sensors. This is to capture spatial sound. We would look at the problem of specifically triggering sound capture and processing at precise time intervals. There are interesting scheduling and synchronization problems here. Because this is a summer research project, you will not be expected to solve them comprehensively, but you can relate the problems to audio processing and develop the issues that emerge from audio processing side. Second is extending the event processing mechanisms in the JAMScript runtime. This work builds on the task scheduler that is already in JAMScript and is being improved in ongoing work. As part of the extensions, we will develop mechanisms to wait for certain type of events. Third is to use the interface to capture and play audio using a single device or many devices. In the many device, case we need to investigate the synchronization in capture and playback. The fourth is benchmarking the interface and study the performance bottlenecks in the capture/playback architecture.

Tasks per student

Study existing audio processing pipelines. Develop the framework for JAMScript and audio processing. Implement the framework in JAMScript: audio capture, processing, playback, etc. Study the performance of the framework.

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Number of positions

2

Academic Level

No preference

Description

This project is at the intersection of two areas of research: stochastic control and reinforcement learning. In particular, it involves investigating reinforcement learning (RL) algorithms for what is called a linear quadratic regulator (LQR). LQR is the basic model to analyze systems described by constant coefficient linear differential equations (which includes electrical circuits, spring-mass systems, thermodynamical systems, chemical processes, and others). RL efers to class of algorithms which can be used by an agent to learn optimal behavior in an unknown environment.

Tasks per student

1. Build a simulation testbed for evaluating regret bounds for LQR models.
2. Conduct a detailed evaluation of regret of Thompson sampling under different parameteric assumptions.
3. Conduct a detailed evaluation of regret of adaptive control algorithms under different parameteric assumptions.

Number of positions

1

Academic Level

Year 2 or Year 3

Description

Vehicles that are able to autonomously move in the air, on the ground, or underwater must fuse various forms of sensor data together in order to ascertain the vehicles precise location relative to objects. Typical sensor data includes inertial measurement unit (IMU) data and some sort of range data from an optical camera, radar, or LIDAR. This SURE project will focus on sensor fusion using both traditional tools, such as the Kalman filter, and untraditional tools, such as Gaussian process regression. Students best fit for this position are those interested in using mathematical tools, such as linear algebra, probability theory, and numerical optimization, to solve problems found in robotics. Experience with matlab and/or C programming is desired. Depending on the students interest and/or experience, the students may work more with data and hardware, or more with theory.

Tasks per student

- Formulate the constrained estimation problem. - Write matlab code to test the algorithm in a simulation. - Test on experimental data.

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Number of positions

2

Academic Level

Year 3

Description

The Aerospace Mechatronics Laboratory houses a wide range of unmanned aerial vehicles, including quadrotors, gliders, fixed-wing and hybrid aircraft. The overall objective of our research is to develop platforms for a range of tasks. Example applications include gliders for wildfire monitoring and fixed-wing aircraft for autonomous acrobatic flight through obstacle fields. Two SURE students are sought with strong interest and aptitude for research in the areas of robotics, mechatronics and aerial systems. Depending on the status of the above projects, the student is expected to contribute to experimental testing of components and to flight tests with these platforms. In addition, the students will be involved with interfacing new sensors into the platforms, for the purposes of acquiring data and for closed loop control. Some programming experience would be useful for the development of a real-time hardware-in-the-loop simulation. The students are expected to assist with hardware interfacing, programming, conducting experiments, and processing the data.

Tasks per student

The tasks will be varied and could accommodate mechanical, electrical or software engineering students; but ideally someone with experience in all aspects. Tasks will include some interfacing of sensing hardware with microprocessors; programming; some CAD modeling; some Matlab/Simulink modeling; and finally, experimental testing.

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Number of positions

2

Academic Level

Year 3

Description

The Æ»¹ûÒùÔº fluids laboratory is developing a multi-fan wind tunnel facility for testing unsteady aerodynamic effects on drones and other types of aircraft. To study the unsteady aerodynamics effects, the multi-fan (81 fans in total) wind tunnel facility requires a proper signal generator to vary the RPM of each fan independently. Preliminary prototyping of a signal generator to drive these 81 fans has been done using simple Arduino microcontrollers. This project aims at developing, building and testing a more robust controller that can generate 81 independent PWM signals with variable duty cycles.

Tasks per student

1) Design and fabricate a working PWM signal generator capable of generating and varying at least 81 individual outputs. 2) Help troubleshoot and optimize this device and implement desired fluctuating outputs. 3) Aid in developing a template/interface to create future signal outputs.

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Number of positions

1

Academic Level

Year 3