Oil supply-side policies—setbacks, excise taxes and carbon taxes—are increasingly considered for decarbonizing the transportation sector. Understanding not only how such policies reduce oil extraction and greenhouse gas (GHG) emissions but also which communities receive the resulting health benefits and labour-market impacts is crucial for designin...
Internet of Things (IoT) or Internet of Objects is defining a new era of technology, where the electrical devices communicate with each other wirelessly. IoT devices have their applications in many fields in our quotidian life, such as telecommunications, education, health care, industrial domains, etc. A barrier to overcome in the development of t...
Optimal detection is one of the most fundamental problems in communication and statistical signal processing. Nevertheless, in many applications, the optimal detection problem often reduces to an NP-complete, or even NP-hard, discrete optimization problem. This research project aims to develop randomized algorithms using Monte Carlo Markov chain me...
Traditional input methods to interface with computer systems prove to be challenging for individuals with amputations or paralysis. Although several brain-machine interfaces were developed to address this problem, their invasive nature prevents widespread adoption. Alternatively, developing interfaces using non-invasive signals has been shown to be...
Nuclear Magnetic Resonance is the premier analytical tool for characterizing chemical structure and dynamics. Yet, it battles with the challenge of relatively low sensitivity. To combat this issue, various schemes have been devised over the years. One such strategy, Non-Uniform Sampling (NUS) refers to any method of collecting variable numbers of t...
Estimating the unknown parameters of a system is critical in many engineering applications, such as the control of power electronics, motion planning for autonomous cars, flight controllers for aircraft, and rendezvous and docking controllers for spacecraft. While modern continuous-time and discrete-time estimation algorithms have found widespread ...
Biosensor technologies have enormous potential in the field of biomedical diagnostics. Despite this, certain barriers have prevented the widespread application of existing biodiagnostic technologies. The limitations include the requirements of high-end, expensive, and complicated laboratory instruments, as well as the lengthy laboratory procedures ...
Magnetic resonance imaging (MRI) is a non-invasive imaging technique that can produce high spatial resolution 3D images, especially for non-bony parts or soft tissues. Higher imaging resolution is usually preferred, to detect small lesions or irregularities in the imaging subject. This dissertation presents two projects that aims for high-resolutio...
Contactless vital sensing is gaining prominence with applications in disease control, health monitoring, and medicine; airports are beginning to use infrared thermometers to screen for fevers, automobile companies are researching how cars can wirelessly detect drowsy drivers, and the medical field is exploring the benefits of how cameras can be use...
Epidural electrical stimulation (EES) has garnered interest as a treatment option for spinal cord injury and has promoted the recovery of autonomic and voluntary motor function in patients with paraplegia. While spatiotemporal EES has been optimized to facilitate functional movement, there remains an unmet need for targeted, spatially selective sti...
