Dr. Catherine Stinson

Lab Director

Queen’s National Scholar in Philosophical Implications of Artificial Intelligence
Assistant Professor in the Philosophy Department and School of Computing. 

Dr. Stinson has a PhD in History & Philosophy of Science from the University of Pittsburgh, and a MSc in Computer Science from the University of Toronto. They specialize in methodology and ethics of artificial intelligence, and have published on bias in recommendation systems, psychiatric classification, explanation in Artificial Neural Networks, health data privacy, and (against) eugenic tech. Current research topics include deep learning benchmarks, adversarial examples as methodology, evaluating AI generated art, and privacy implications of large language models

Emily Medema

MSc Computing Student

Emily is a second-year Master’s student researching the spread of misinformation on Twitter (allegedly known as X). Her goal is to use Evolutionary Computing to craft the best performing piece of misinformation and analyze why specific pieces perform well.

Website GitHub

Tindur Sigurdarson

PhD Computing Student

Tindur Sigurdarson is a Ph.D. Student in the CREATE Cybersecurity program. His M.Sc. research focused on the potential for machine learning predictors to explain their own faults in the context of ethical and interpretable machine learning.

Research interests: Interpretable & Fair ML, ML for Cybersecurity, and  Data Pruning

Sofie Vlaad

PhD Philosophy Student

Poet in Residence

Sofie’s research is firmly rooted in both feminist philosophy and transgender studies. These twin schools of thought inform her work in ways that are both explicit and implicit. Her current project brings together philosophy of artificial intelligence, philosophy of creativity, and contemporary poetics to explore the relationship between art—broadly conceived—and Artificial Intelligence. Her research questions include: What are the poetics of AI-generated art? Is AI-generated art creative? Who should we consider to be the author of AI-generated art?

Currently Sofie is working on an article that posits trans poetics as a way of doing trans philosophy, a co-authored piece exploring how we might epistemically ground diversity projects in AI, and several creative works, including a collaborative arts project exploring queer/mad/trans/femme futures.

Rina Khan

PhD Computing Student

Rina Faiyaz Khan is originally from Dhaka, Bangladesh. She completed her Bachelor’s in Electronic Engineering from Multimedia University in Malaysia. She then proceeded to complete her Master’s in Computing at Queen’s University, where she is now pursuing her PhD in Computing. Rina’s research interests include AI ethics, focusing on how bias impacts marginalized communities and methods of building fairer and more equitable AI models.

Veronika Grigoreva

MSc Computing Student

Veronika is a first-year Master’s student at Queens. Her BSc research focused on bias in large language models (LLMs) and the development of a Russian language bias detection dataset. She is now working on studying the privacy issues in LLMs. Veronika’s research interests cover bias and fairness in deep learning models and social effects of modern AI technology.

Will Aitken

MASc Computer Engineering Student

Will is an MASc Computer Engineering student analyzing the pervasive coalescence between academia and industry in AI and specifically natural language processing (NLP). He is studying trends of industry influence and the impact its growth has on the integrity and feasibility of public NLP research.

Harrison Stuart

Undergraduate Computing Student

Harrison is a Computing student and BAH English Literature graduate, interested in how modern NLP technology may impact humanity’s relationship to language. He is currently assisting the lab with research concerning privacy issues in LLMs.

Malcolm Newton

Undergraduate Computing Student

Malcolm is a fourth-year Computing student interested in the impacts machine learning applications will have in agriculture, specifically on non-human animals. Malcolm is currently working on an undergraduate thesis studying improvements to computer vision in agriculture, and the potential impact of these improvements.

Lab alumni

Vanessa Ferguson

MA Philosophy, 2022

Ethicist in Residence

Vanessa’s research interests include bioethics, artificial intelligence (AI) ethics, Black studies, health studies and the intersections between them. Vanessa completed her MA at Queens University in the Department of Philosophy. Vanessa’s Master’s thesis explores how ideas of race, race science and racism are embedded in medicine, and how they inform health care, treatment, and health outcomes in sickle cell disease, specifically for Black populations in Canada and beyond. Vanessa’s primary motivations are to catalogue the Black patient experience in Canada, and globally in the context of anti-Black racism.

Annabelle Sauve

MSc Computing, 2023

Annabelle’s research focused on analyzing the language used in medical records when discussing mental health disorders.

Ernesto Lang Oreamuno

MSc Computing, 2022

My research was about software engineering in AI or SE4AI for short. I look into how software engineering practices and projects can be combined with machine learning artifacts such as datasets and models, with the intention of exploring how these elements are coalesce together into applicable business solutions.

Beyond that, I have worked in software engineering in the past 5 years, using technologies such as Docker, PostgresSQL, Nginx, RabbitMQ, Google Cloud Platform and Nginx, with languages such as Java, C# and Python, also for a more of an enthusiast side I use Rust and Elixir.

Currently, my time is dedicated to massive data extraction and analysis through the use
of machine learning.



Sam Baranek

MSc Computing, 2023

Sam conducted research on privacy preserving biometrics, specifically secure multi party computation and facial recognition.

Diggory Waddle

MA Philosophy Student

Diggory conducted research into intimate relationships with artificial intelligence. His goal is to help build a future for AI relationships that is equitable and kind.