Breakout Session 2

This session explores how University of Alberta startup, Nanostics, is using AI to transform healthcare. Nanostics develops novel, non-invasive, early detection tests that generate a disease risk score and bring clarity to healthcare. Their AI-powered ClarityDX platform analyses clinical data to provide actionable decision support for next-step testing, including imaging or biopsy. This empowers patients and their healthcare providers to make more informed healthcare decisions. The session will highlight their path from research to real-world impact, and examine the promises, challenges, and future of AI-powered, patient-centered care.

About Catalina Vasquez:

Catalina is the Co-Founder and COO of Nanostics, a commercial-stage precision health company developing novel tools to help bring clarity to healthcare decisions. Nanostics has developed ClarityDX Prostate, a breakthrough that substantially enhances the prediction of aggressive prostate cancer and reduces the number of prostate biopsies, which are invasive, uncomfortable and carry some risk.

This workshop will prepare students for the fundamentals of using AI and showcase the unique ways Gemini for Education can help students study and prepare for their future careers. We'll explore real world examples of how AI is being applied to solve society's biggest challenges and improve lives.

About Cassi Caputo:

My name is Cassi Caputo and I have been part of the Google for Education team since 2011. I have a passion for both technology and education, and feel honored to incorporate the two in my work at Google. I joined Google at an exciting time, aligning with the launch of the "Cr-48" Chromebook prototype. I am passionate about sharing the Google for Education story and supporting schools to reach their teaching and learning goals.

The session will introduce the current state of AI/ML implementation in engineering applications, with a focus on the chemical process industry. It will discuss which AI techniques and applications have had the most impact and why, using case studies. It will describe prospects for the expansion of the use of AI/Ml in engineering systems.

An important part will be looking at decision systems in engineering (especially in the chemical process industry), identifying these as human-AI integrated decision systems, and describing the various AI-human integration frameworks currently used in the decision systems and those that will likely be used in the future. Also, the unique considerations in application of fully AI-automated approaches to engineering systems (e.g. physical safety) will be discussed.

About Dr. Vinay Prasad:

Vinay Prasad is the Jaffer Professor of Process Systems and Control Engineering at the University of Alberta. He has academic and industrial experience spanning Canada, the USA and India. He is trained as a chemical engineer and is an expert in process systems engineering and the application of modeling, control and optimization to a variety of chemical processes, especially focused on clean and sustainable energy production and on the extraction of critical minerals. He uses sophisticated AI and ML techniques combined with first principles knowledge of the discipline in these efforts, and collaborates with industrial partners to deploy solutions in their operations. He is also committed to outreach efforts, has been giving interactive talks/sessions on machine learning for students in grades 1-9 and has also delivered talks to high schoolers on career options combining chemical engineering and AI/ML.

Materials science has enabled the development of many applications and functional materials essential in modern technology, including batteries, solar cells, lasers, magnets, light emitting diodes, hard materials, superconductors, and catalysts.  To improve the properties of these materials, scientists are interested in determining their crystal structures, that is, the detailed arrangement of atoms, so that they can design better materials with specific structural features.  This presentation will discuss how machine learning methods can guide the efficient search of new materials by showcasing some problems that scientists are working on.  As a hands-on activity, students will apply decision tree models to classify everyday objects, to illustrate how this approach can be extended to classify crystal structures of materials.

About the Speakers:  

Arthur Mar - Arthur Mar leads a research program in materials chemistry, and has published >250 articles about inorganic solids, including intermetallics, chalcogenides, pnictides, and Zintl phases.  In recent years, he has been interested in applying machine-learning approaches to accelerate materials discovery and to predict crystal structures.  Allison Thomé is a graduate student in the Mar group working to develop machine-learning models to predict high-entropy alloys and superconductors, and collaborating to additive manufacturing techniques to design small modular reactors. 

Allison Thomé  - Allison Thomé (He/His) is a PhD candidate at the University of Alberta, researching interpretable machine learning models for predicting the formation and properties of high-entropy alloys. He previously earned his MSc in Chemistry from the Federal University of Santa Catarina, Brazil, where he focused on sustainable recycling approaches for developing green silica-based nanomaterials. Allison's work bridges computational methods with materials science, where advanced data analysis techniques are combined with experimental validation to expand the frontiers of materials discovery and design.

This session introduces data science and artificial intelligence through basketball data. We'll collect, clean, and analyze our own data as well as NBA and WNBA data, introduce how AI tools can help with analysis, and talk about how data can be used for decision making in any field that you are passionate about.

About David Hay:

David Hay is a developer on the Data Dunkers project, a director with the Callysto Education Initiative, and teaches high school computing science and robotics in Sherwood Park.