Graduate Student Highlights

Angela Kohut

I am a PhD student in the Computational Science program in the School of Computer Science who is advised by Dr Stefan Kremer (Computer Science) and Dr Steffen Graether (Molecular and Cellular Biology). As a Computational Science student, I get to apply Computer techniques to the field of biology. My research focuses on determining the best methods for classifying protein structural data using Machine Learning techniques. My goal during my PhD is to develop and optimize an initial framework of a mathematical model that can characterize similar structures. The main idea is to obtain 2-dimensional representations of the protein structures that can be used to train a deep neural network for the classification of these structural patterns. This new framework can be then implemented as a tool to classify protein structures in a standard fashion, while also giving users the flexibility to define classification categories.

I obtained a Bachelor of Chemistry with Honours and an MSc in Chemistry at Western University. During my third year of undergraduate studies, I was introduced to the field of Computational Chemistry. In my first research position, I learned about the applications of Quantum Chemistry where I was exposed to the complexity around the chemical interactions. During my Master's, I explored various theories in Computational Biochemistry and Biophysics and developed a new method to show that Adenosine Triphosphate (ATP) Synthase, a protein responsible for producing ATP (an energy storage molecule), rotates within a cell membrane at an atomic level.

After my Mater's degree, I quickly realized that I wanted to learn more about other Computer Science techniques that can be applied to the fields of Chemistry and Biology. Having researched graduate programs in Ontario, I concluded that the PhD in Computational Sciences program at the University of Guelph aligned with my goals.

Corey Alexander

Corey Alexander

The Public Health Agency recently completed the Canadian Food Consumption Survey. The goal of the survey was to understand the eating habits of Canadians to help facilitate responses to foodborne disease outbreaks. The challenge with conducting surveys of this nature continues to be a decline in response rates, and user fatigue - especially for longer telephone surveys - where respondents quit a survey before it’s completely out of boredom. In response, Corey is working to explore new ways of engaging respondents of online public health surveys through the use of gamification. The goal is to develop methods to improve the quality and quantity of data collected. Corey is part of Dr Daniel Gillis’ Alternative Data Collection Research program. 

During his time in the School of Computer Science, Corey has also helped develop the Farm To Fork system to improve the quality and quantity of food donated to food banks. Corey has been awarded the Guelph Mercury’s 40 Under 40 Award, as well as the University of Guelph Student Life’s Be The Change Award. 

Dave Radford

Dave Radford

I applied to Grad School in the 4th year of my undergrad studies at Algoma University in my hometown of Sault Ste. Marie, Ontario. I graduated with a Bachelor of Computer Science (B.COSC) with Honours. Even after applying to several schools, including Guelph, I still wasn't sure if I wanted to continue my education. That changed when I received an offer from the University of Guelph in May 2013. I decided to pursue my M.Sc in the fall of that year. It would be my second time living away from home and my first time at a large university.

I began my studies in the Fall of 2013 with my advisor Dr Dave Calvert. My Master's thesis, which will be completed in June of 2016 is focused on parallel computing on CUDA GPUs. My topic is focused on parallel design patterns and how they can be applied to serial algorithms, specifically, genetic algorithms configured for solving the travelling salesman problem. My thesis contributions show the effectiveness of parallel patterns when applied to algorithms that were not solely developed to be parallel and that fit the structure of particular parallel patterns. My research interests are machine learning, parallel computing, algorithms, and artificial intelligence.

Over the course of my studies, I've worked as a Teaching Assistant covering topics such as Software Design, Parallel Programming, and the Analysis of Algorithms. My coursework introduced me to the application areas of data mining and machine learning, a field in which I am actively pursuing a career, and the Internet of Things. I also spent two semesters working with some professors in the Department of Geography helping them develop a prototype application for watershed modelling software in Java. In both of my eligible years at Guelph, I also earned the CPES Dean's Scholarship for my academic performance. Guelph is a great city and my experiences at the University have been exceptional.

Kassy Raymond

Kassy Raymond

I am a PhD student in Computational Sciences with a Collaborative Specialization in One Health working under the supervision of Dr. Deborah Stacey (School of Computer Science) and Dr. Theresa Bernardo (Population Medicine). I am also a Technical Manager for the Global Burden of Animal Diseases (GBADs). My research area will look at the operationalization of data governance principles to improve the quality, discoverability, and reusability of animal health and production data in the GBADs knowledge engine. I received an Ontario Graduate Scholarship to pursue this research.

A PhD wasn’t always my goal. When I finished my BSc in Biological Sciences, I had an interest in data science and machine learning and knew I really hated lab work. I was lucky enough to sit beside a computer science professor (Dr. Andrew Hamilton-Wright) on the bus one day. Feeling brave, I expressed my interest in data science and my concern for not knowing how to make the leap into tech. After completing some exercises to demonstrate my programming abilities, I started an MSc in Bioinformatics under the supervision of Dr. Hamilton-Wright. My Master’s research focused on exploring the use of unsupervised machine learning to analyze electrodermal activity data (i.e., data that measure activation of sweat glands on the skin, which can be used to indicate someone’s physiological response to stress).

The opportunity to do an MSc allowed me to develop personally and professionally and provided me with opportunities to develop and explore my interests outside of my direct research area. Because I didn’t have a formal computing background, it was difficult at first to get funding (and TA positions), so I jumped on contract positions to make extra money and gain experience. One of these positions was Technical Manager for GBADs. This position sparked my interest in data governance and designing data-centric systems to unleash the potential of data and led to my role as PhD student on the project. I am very excited to see where this opportunity leads!

Nic Durish

Nic Durish

Nic Durish is a Master’s student in the School of Computer Science with a specialization in Human-Computer Interaction. Nic  -completed his undergraduate degree at the University of Guelph, where, through his advisors and involvement in Computer Science events, organizations, projects and teaching positions, he became interested in pedagogy and using computing to solve real-world problems. Nic has since returned to the University of Guelph to expand on his research in this field and was recently awarded $16,000 for the 2017 Graduate Tuition Scholarship.

Nic recently joined the eNuk team. Over the course of his degree, Nic will be working to expand the community-led eNuk health and environmental monitoring apps with the remote Inuit community of Rigolet, Nunatsiavut, Labrador. In particular, and in response to a community request that eNuk “not be just another app – it has to be part of our lives”, Nic will focus his research on participatory design methods and the use of social elements of gamification to foster user engagement.

Nic often credits his advisor, Dr. Daniel Gillis, for inciting his interest in teaching, research and collaborative projects. Dr. Gillis is an Associate Professor and Statistician in the School of Computer Science, and the Director of the Physical Science & Engineering Education Research Centre at the University of Guelph. Dr. Gillis’s exceptional involvement and teaching has been recognized through awards such as; the Distinguished Professor Award for Excellence in Teaching, the Winegard Exemplary Volunteer Award, and the Guelph Mercury 40 Under 40 Award. 

Oliver Cook crouching in the snow

Oliver Cook

Climate change has already had a significant impact on the circumpolar Inuit community of Rigolet, Labrador. Changes to weather patterns and the environment have affected the traditional hunting and gathering practices of the community, as well as the health and wellbeing of the people who call Rigolet home. In particular, highly variable weather patterns and warmer waters have affected the quality and timing of ice formation, greatly impacting the community’s ability to travel and hunt during the winter months. To help manage the public health impacts, and to provide meaningful data to the community, Oliver is exploring participatory design methods to develop an eco-health monitoring program to help track changes to the land, environment, and public health. Based on community feedback, the system will be designed to both capture and provide information that is important to the community. Working under the umbrella of Dr Daniel Gillis’ Alternative Data Collection Research program, Oliver’s Master’s research is to explore the use of participatory design methods as a means of improving user engagement.

During his time in the School of Computer Science, Oliver has also helped develop the Farm To Fork system to improve the quality and quantity of food donated to food banks. Oliver has been awarded the Guelph Mercury’s 40 Under 40 Award, as well as the University of Guelph Student Life’s Be The Change Award. 

Rawan Abulibdeh

Rawan is completing her Master’s in Computer Science with a specialization in applied Machine Learning and Security. She was allowed to pursue her research goals by the wonderful faculty members at the University of Guelph, more specifically her supervisors, Dr Hassan Khan and Dr Charlie Obimbo. Her research area focuses on deciphering the personal identification number (PIN) used for authentication on a smartphone by using just the tilt motion that the screen produces when the PIN is being entered. This is done by building a Machine Learning algorithm that will be trained to detect patterns in tilt variation so that when it is fed a video input of a user entering their PIN on their device, it will be able to predict which keys are entered based on the pattern the tilt motion produced. This is the first application that does not require the screen or users’ hand to be visible to decipher PINs for authentication. This research is vital because, with the advances in computer vision, it exposes a novel side-channel that threatens the protection offered by PINs using commercial smartphones.

Rawan completed her undergraduate degree in Computer Engineering at Qatar University in 2019 and graduated with honours. Her interested in Machine Learning applications started with her internship in Al Jazeera News Agency in 2018 when she led a team that incorporated Machine Learning techniques into the agency for the first time by creating a project that can automatically assess the quality of the videos being broadcasted without the need for human interaction. Applying to the University of Guelph gave her the opportunities she needed to pursue her career goals. After completing her Master's studies she intends to continue her graduate studies by pursuing a Doctoral degree, as she is extremely keen to continue contributing to advancements in the computing field.