About Us
💉 💧 = T1D
Christopher Risi is a computer science PhD student at the University of Waterloo specializing in artificial intelligence. He works in the University of Waterloo's Computational Health Informatics Lab (CHIL) and as a Consultant, AI Research and Health Insights at Gluroo Imaginations Inc. Christopher's research focuses on finding ways to utilize a wide variety of AI tools for easing and improving diabetes management. Christopher has Latent Autoimmune Diabetes of Adults (LADA) a subtype of T1D.
Walker Payne is a data scientist at Gluroo. He is also a type 1 diabetic, having been diagnosed nearly 15 years ago.
Dvir Zagury-Grynbaum is a mathematical physics undergraduate student at the University of Waterloo with research and application experience in causal inference and causal AI. He will bring his expertise to help answer questions standard ML tools have trouble with in finite data scenarios where Randomized Controlled Trials are not always possible, such as diabetes health data scenarios.
Abdullah Shahid is a computer science undergraduate at the University of Waterloo. Diagnosed with Type 1 Diabetes nearly a decade ago, he has developed a diabetic lifestyle management app as a personal project in the past and has interned at companies like Lyft. He aims to leverage his experience to make life easier for diabetics around the world.
Junwon Park is math undergraduate student majoring in Statistics and minor in computation at the University of Waterloo. He has a strong background in dealing with time series data, data quality checks, and anomaly detection for finance data. With these experiences, Junwon (Paul) Park aims to leverage his knowledge to contribute to this project and hopefully help more people with diabeties.
Andrew Yang is Big Mac on Discord.
Jonathan Gong is a computer science undergraduate at the University of Waterloo. He has a passion for AI solutions in healthcare as well as experience with developing computer vision models for medical imaging and disease detection. Explore his latest AI projects on GitHub.
Safiya Makada is a software engineering undergraduate student at the University of Waterloo. She has previous experience as a Machine Learning Engineer Intern in a startup, and has a passion for making technologies that improve health outcomes. Having lived with a type 1 diabetic for 8 years and having work experience with a diabetes nonprofit, she has seen first hand how technology can save lives.
Gavin Katz is a biomedical engineering undergraduate student at the University of Waterloo. He has previous experience working in software development at biotech startups, leveraging his knowledge of ML to create predictive models that assist in the diagnosis of congenital heart disease. He is currently interning at a data analytics firm in Toronto, and is excited to learn about what approaches can be taken to improve the lives of those living with diabetes.
Alyssa D'Souza is a software engineering undergraduate student at the University of Waterloo, specializing in AI and computational math. With prior software development experience at the Ontario Institute for Cancer Research, she is eager to find similarly impactful opportunities and is excited to bring a blend of software engineering and ML skills to the team.
Shivam Singal is a software engineering student at the University of Waterloo, specializing in machine learning and data engineering. Previously, he worked with WAT.ai to develop a reinforcement learning-based chess engine, gaining hands-on experience in self-learning algorithms. He has also built data processing pipelines and machine learning models through past internships, building a strong foundation in AI-driven solutions for real-world applications. Shivam is eager to bring his skills to the blood glucose control project and is excited to explore how machine learning can improve health outcomes for people with diabetes.
Cristiano Da Silva Is a nanotechnology undergraduate at the University of Waterloo. Diagnosed with Type 1 two years, ago, he sought to improve the sustainability and affordability of diabetes treatment by designing a reuasble glucose monitor applicator, which was recognized as a global winner from Oxford University's Rhodes Trust. As an advocate and educator, Cristiano has hoped to inspire others by sharing his story through organizations like TEDx, SickKids Diabetes Day, and Diabetes Hope Foundation.
Vilohith Rao is a Data Science student at the University of Waterloo.
Anton Ryavkin is a mathematics undergraduate student at the University of Waterloo majoring in Statistics and Computational Mathematics. Having lived with a Type 1 diabetic for several years, he understands the day-to-day struggles of people with diabetes and the importance of technology in the management of the disease. Anton seeks to help people with diabetes by leveraging his ML experience from past internships and schoolwork.
Tony Chan is a Computer Engineering student at the University of Waterloo with experience in full-stack development for healthcare systems, AI, and machine learning. He has a strong track record in building scalable systems, integrating complex technologies, and solving technical challenges. Tony is passionate about using technology to make a meaningful impact, especially in improving and saving people's lives.
Rebecca Ma is a Computer Engineering Master's student at the University of Waterloo. Her research is in ML, particularly on the robustness of AI models. Previously, she completed her undergraduate degree in Biomedical Engineering (also at UWaterloo), which contributed to her interest in joining this project and exploring the intersection of healthcare and technology.
Julia Zhu is a computer science student at the University of Waterloo, driven to make a real impact in people’s lives. She is excited to bring in her skills in machine learning and software development to the team!
Nathan Lu is a Management Engineering student at the University of Waterloo with experience in data science research. At the university, he worked on cleansing datasets and developing classification algorithms to uncover trends and generate accurate insights. Nathan is excited to contribute to the team, collaborate with diverse members, and continue expanding his skills in the world of machine learning.
