Investigating how user interfaces impact scalable network displays

IOT technology is a brand new, and rapidly growing field. Currently, there are no best practices published in the design of real-time, dynamic network displays. Our project focuses on developing and testing new business processes, user personas, and design-guidelines associated with these types of displays in a real-world environment. The findings from this work will not only inform future software development at Distrix, but also aims to offer meaningful contributions to the methodology literature in information visualization and human computer interaction.

Investigation of high-resolution image reconstruction of large objects through turbid media

This project focuses finding solution for acquiring super resolution image from objects submerged in turbid media. The project group will look at various environments including high pressure / high temperature test setups.

Real-Time Radar Data Analysis for Classification of Ground and Aerial Targets

Radars are being used more and more in critical sites such as airports, military bases and borders for surveillance of huge areas to detect unwanted intrusions. Determination of the type of each target is essential for such systems to identify the nature of the intrusion and avoid false and nuisance alarms. This thesis is focused on the design of automatic target classification systems based on analysis of real radar data from different sites and environments.

Image Enhancement for Color Deficient People

I have been recently graduated from the School of Electrical Engineering and Computer Science of University of Ottawa. I did my PhD in Image Color Processing, and I found out the available position with Irystec Company is fit to my knowledge and experience. As a PhD candidate, I had the opportunity to gain extensive experience in Image Processing, Computer Vision and Machine Learning fields. Conducting research on the image processing subject as my
PhD thesis topic, elevate my knowledge in design, coding, and testing. My M.Sc.

Accelerating Phase Unwrapping

The project aims at enhancing performance and efficiency in InSAR (Interferometric Synthetic Aperture Radar) systems. Such systems are used to measure displacement or deformation of any object on earth. Both environmental and industrial studies can benefit from projects like this, as it will help them make decisions based on a more realistic view of current conditions. They will also have a better chance of accurate speculation of the consequences of their decisions.

Security assessment of mobile financial services

Information technology rapid evolution was always closely followed by sophistication of malware. And with ubiquitous shift to mobile platforms, rise of mobile malware and in particular banking malware came as no surprise. In general, any financial operation on a mobile platform potentially exposes a user to the variety of threats including data leakage, theft and financial loss. Driven by financial profits, banking malware leverages user's cluelessness, openness of mobile platforms, often a lack of security measures.

Machine-to-Machine Remote Asset Monitoring & Optimal Inspection and Repair Logistics

Cyber-physical systems or Industrial Internet of Things (IIoT) applications are more advanced than commercial IoT devices/applications mainly because of the prevalence of connected sensors and embedded systems in the industrial world. The objective of this project is to develop and package a low range, low power (LoRa Technology) remote asset monitoring and control system for “remote fixed utility” IIoT applications.

Machine learning in fluid composition quantification

A critical issue in the oil and gas industry is to quantify the composition of fluids flowing back from the hydraulic fracturing process. This quantification is usually carried out by a manual process (frequently via a visual test) to estimate the water and oil produced from a well flow back process. A sample of these onsite tests are sent to laboratories for chemical analysis. This process has been the status quo for decades. This approach is manual, prone to error, and does not lend itself to sophisticated real time analysis.

Junior hockey competence analytics

Analytics is about awareness of the states of knowledge of users. Users can become aware of their owns states of knowledge at different levels. Analytics measures such levels of each user, and engages them in taking initiatives to hop from one knowledge state to the next.
The hops happen mostly gradually, depending on the capacity of the user, punctuated by dramatic jumps. Analytics identifies such scenarios where dramatic jumps are necessary and offers the information needed to enact such jumps.

Identifying transportation mode based on smartphone sensor data using machine learning tools and statistical methods

Detecting an individual’s transportation mode has an invaluable role in applications, by allowing the application to be aware of user’s current context, and modify their functionality accordingly. There has been numerous research in this area, each using a different approach and achieving different outcomes. The goal of this internship to better understand the state of the art technology in classifying modes of transportation (e.g.