Meet Our Students

Graduate Student Profiles

Below is a list of international students at UBC Applied Science who provided profiles about their research. It will give you an idea why students chose to come to UBC, what they like about Vancouver and what their career goals are. Profiles courtesy of the Faculty of Graduate + Postdoctoral Studies.

Bench Scale Primary Microscreen and Algae Photobioreactor setup. The Algae PBR is lit with a pink grow light for scientific purposes while the microscreen is pink purely for aesthetic purposes.
The feasibility of primary microscreening and algae photobioreactors for small-scale passive wastewater treatment and reuse in urban areas
This research seeks a resolution between two opposing trends in cities around the world: the greening of the urban realm and the exhausting of municipal water supplies. Green space in urban areas has been widely shown to increase economic productivity, physical and mental health, social cohesion, and lower urban energy consumption. However, a lush urban realm comes with an expense: water and nutrients. Even in rainy Vancouver, we struggle to keep our lawns alive in summer months, let alone places not located amidst a temperate rainforest. Wastewater is an abundant and nutrient rich water source capable of reconciling this rift. This research project is a feasibility study on a wastewater treatment process designed for distributed small scale reuse within the urban realm–primary microscreening followed by an algae photobioreactor and UV disinfection. To assess feasibility, wastewater is collected from two points in UBC’s sewer network and first gravity filtered through a 54um microscreen to remove suspended particulate. The filtered water is then fed to a flow cell resembling a solar panel where a symbiotic community of algae and bacteria consume the remaining dissolved carbon and nutrients powered by sunlight. The efficiency of the treatment processes is being analysed according to energy use and effluent quality, and the microbial community is being DNA sequenced for characterization. The primary research objective is to determine whether the treatment train is capable of meeting unrestricted urban reuse guidelines in British Columbia and elsewhere.
Rabe Arshad, International Doctoral Fellow
Rabe Arshad, International Doctoral Fellow
User mobility management in wireless networks
Supporting user mobility is considered to be an intrinsic feature of wireless networks. With the massive deployment of wireless nodes to support increasing traffic demands, there exists a number of challenges in offering streamless services to users with mobility. Such user mobility issues need to be incorporated in the capacity planning phase and there arises a need to have mobility management techniques that could minimize the effect of user mobility on the desired data rate. As a part of my PhD, I am working on such novel mobility management techniques using tools from stochastic geometry to quantify and reduce the effect of user mobility in various wireless networks.
Sahand Sarbishei poses for a photo
Sulfur deportment in ferronickel production via Rotary Kiln-Electric Furnace process
Nickel is an essential component of stainless steel with a wide range of application in architecture, construction, automotive and transportation. The rotary kiln-electric furnace (RKEF) process is a pyrometallurgical route that has long been used for the production of ferronickel. Since the presence of impurities would have negative effects on the properties of ferronickel, it is necessary to control the form and concentration of impurities. Sulfur is a deleterious impurity that reacts with alloy components and forms non-metallic inclusions that lead to decrement in mechanical properties of nickel alloys. This project aims to investigate sulfur deportment in the RKEF process by employing various fuels and reducing agents as well as regulating the conditions in the rotary kiln. The long-term goal of this study is to produce high purity ferronickel while diminishing the load of the refinery.
Molecular Dynamics simulation of piezo-ionic sensors
With increasing interest in motion capture, soft robotics, and wearable medical technologies, human (bio) compatible sensors are required. When creating these bio-friendly sensors, they need to be flexible, conductive and compatible with human tissue. Unfortunately, the materials currently available are either solid, as in electric wire, or liquid, as in car batteries. Smart hydrogels are a promising class of materials that can potentially bridge the gap between current sensor technologies and tomorrow’s soft-sensor requirements. On a nanoscopic level, hydrogel resembles three-dimensional hollow honeycomb cells that trap the conducting particles (ions). By choosing the correct chemical process for creating the gel, one can virtually program it to respond to external stimuli like temperature, pH or mechanical impact (as in touch sensors) - hence the name “smart.” To optimize the performance of hydrogels in touch sensors, one needs to understand in detail the behavior of ion movement in the honeycomb cells when pressure is applied. Through a computer simulation tool called Molecular Dynamics, we perform an extensive analysis of the flow of ions in the gel cells. Through extensive virtual trials, we select the most optimal chemical structure. The computational screening will allow the experimentalist to synthesize the most favorable gel possible and gain insights into it on a nano level. The optimized hydrogel structures could revolutionize the field of soft tissue human-friendly sensors or artificial muscles.
CO2 Sequestration by Mineral Carbonation with Valuable Metals Recovery Enhancement
This project aims to develop a novel economically-feasible mineral carbonation process to sequestrate CO2 for mitigating global warming, which can be used in practical industrial application. The international community has become increasingly concerned that greenhouse gas emissions due to our human’s excessive activities have a potentially adverse effect on global climate conditions. Especially, CO2 has been attributed as the primary causal greenhouse gas (approximately 77%) towards climate change. Except for improving the efficiency of fossil-fuel-fired power plants, the methods to sequester the CO2 emitted from these plants are also necessary. Mineral carbonation, one of the methods of CO2 sequestration, is the only permanent method which can form environmentally benign carbonate minerals stable over geologic time periods. However, mineral carbonation technology remains in relative infancy mainly because of high costs and slow reaction rate as well as low sequestration efficiency. Thus, this project will develop a new and economically feasible process for mineral carbonation to sequestrate waste industrial CO2 and apply it into practical industry.
Advanced Process Control and Analytics
Our proposed research objective is to develop a data-centric control framework that applies scalable machine learning techniques on multilevel heterogeneous process data in order to extract knowledge for improved process operation. Specifically, the objective is to successfully detect and diagnose process conditions of interest (i.e., disturbances or process upsets) and to subsequently control for or against such conditions. Ultimately, we wish to enlighten the way the process analytics community perceives value in data, in order to achieve some of the many benefits other industries are experiencing.
Non-orthogonal Multiple Access for the Internet of Things
My research is concerned with medium access control optimization for the Internet of Things (IoT). The IoT is the concept of connecting IoT devices such as sensors, alarms, healthcare monitoring devices, smart vehicles, and wearables to the Internet with minimal human intervention. These devices require supporting a massive number of connections simultaneously and energy efficiency. In order to satisfy these requirements, I work on optimizing medium access control algorithms to allocate the limited communication resources, i.e. bandwidth and power, efficiently in order to enable the 5th Generation (5G) cellular networks to support the IoT. I use different non-orthogonal multiple access schemes to enable multiple IoT devices to share the same radio communication resources to provide connectivity for a massive number of IoT devices. In addition, we work on designing the medium access control scheme to be flexible and dynamic to adapt to network changes using software-defined multiple access concept.
Mirza Sarwara
Transparent and Flexible Tactile Interface for Human Computer Interaction
The aim of my research is to develop a next generation flexible transparent tactile interface for human computer interaction that can work even while being physically deformed, a property necessary for a true wearable device. In addition to sensing touch, the device can detect the presence of a hovering finger, a stretch, and a bend. It is highly transparent and is fabricated using a simple and scalable process, and will be widely available and made using low-cost polymer materials. The working principle of the sensor is based on the well-established mutual capacitance technology used in current touch screen devices rendering it easily adaptable. The technology is being further enhanced to detect localized shear for electronic skin application. This would enable robot hands to effectively pick up fragile objects and even provide haptic feedback to surgeons using robotic arms for surgeries.
Resource Allocation and Content Caching In 5G Mobile Networks
Resource allocation, optimization, and content caching in mobile networks.
Artemis: Defending Against Automated Large-Scale Cyber Intrusions by Focusing on the Vulnerable Population
State-of-the-art defenses against automated mass-scale cyber-attacks are mostly reactive and generally follow a ‘first-detect-then-prevent’ approach. This gives attackers the ability to evade detection by adjusting their tactics in order to circumvent the employed defenses and still reach the end-users. My research advocates for a proactive approach of identifying the vulnerable users, and employing this information to better protect them by building more robust and efficient system-wide defenses. Specifically, my work investigates novel defenses at the level of the system/infrastructure as well as at the level of individual users in large socio-technical systems. The goal is to develop techniques to identify the population of users vulnerable to various types of large-scale automated attacks. Then, using this knowledge to improve the robustness and efficiency of system-wide defenses, as well as to uncover ways to influence the behaviour of vulnerable users in order to decrease their susceptibility to large-scale attacks. For up-to-date information and links to recent publications, please visit the Artemis project webpage.