Rita Orji designs persuasive technologies to promote social good, focusing on mental and physical wellness. Her apps use AI and VR to encourage positive behavioral changes and improve user engagement.

Andrew MacDougall researches nature-based climate solutions, using ACENET to run complex models. His work explores carbon absorption, potential warming effects, and the impact of reaching net-zero emissions.

David Joly researches cannabis disease resistance by studying plant genes and pathogen interactions. ACENET provides crucial bioinformatics tools and training for his team, accelerating genomic analysis.

Uyen Lai researches how to make generative AI text sound more human. Her work, using ACENET resources, compares AI and human writing styles to improve content creation and realism.

UPEI student Matthew Kozma set a Canadian record for compute-cycle use, surpassing even graduate-level researchers. His simulations, totaling over 30 million CPU hours, advanced nanotechnology research focused on DNA manipulation.

Ian Bradbury uses DNA technology and machine learning to predict how climate change will impact Eastern Canada’s aquatic species, like Arctic char. ACENET provides the computational power needed to analyze massive genetic datasets.

Dr. Damjanov investigates how galaxies evolve, focusing on the interplay between their size, stellar content, and environment. Her team uses ACENET to analyze massive datasets from telescopes and simulations.

Lourdes Peña-Castillo uses computational microbiology and machine learning to understand bacterial genomes. Her goal: to strategically manipulate bacteria for targeted treatments, rather than broad-spectrum antibiotics, enabling 'smart biotechnology'.

Stijn De Baerdemacker uses computational chemistry to simulate molecular behavior, accelerating the discovery of new materials and drugs. ACENET’s resources speed up this process by many orders of magnitude.

Dr. Erin Johnson won the Steacie Prize thanks to ACENET’s high-performance computing. Her research uses advanced modeling to predict molecular interactions, with applications in fields like pharmaceutical development.