Devpost
Participate in our public hackathons
Devpost for Teams
Access your company's private hackathons
Grow your developer ecosystem and promote your platform
Drive innovation, collaboration, and retention within your organization
By use case
Blog
Insights into hackathon planning and participation
Customer stories
Inspiration from peers and other industry leaders
Planning guides
Best practices for planning online and in-person hackathons
Webinars & events
Upcoming events and on-demand recordings
Help desk
Common questions and support documentation
Platform allowing hospitals to easily share data and collaborate for federated learning projects
Training a transformer-based machine model with RNA sequence data
AI-powered enzyme engineering: combining ESM foundation models + structural GNNs to predict PETase activity, accelerating plastic-eating enzyme discovery from years to hours.
Using NLP, we will extract PPIs from the literature, annotate with biological context, and link each interaction to the supporting sentence in the paper. Results will be stored in a knowledge graph.
We have stepped into the technological direction of artificial intelligence, and we believe that it will make the modern world intelligent, intelligent, and creatively human.
Prism transforms RNA data into breakthrough drug discoveries! Like light through glass, we reveal hidden compound interactions from 95M+ transcriptomes, accelerating cancer drug development.
We aim to develop an ML tool using Sanger sequencing to identify disease-associated SNPs, enabling doctors to tailor treatments and improve patient outcomes with fast, precise, personalized care.
Provides a framework to set up and solve differential equations related to compartmental models of disease spread. Planned to integrate intuitive UI/UX to visualise virus spread across Canada.
MiniFold: Lightweight AI that makes advanced biomolecular structure prediction fast, affordable, and accessible to all
Delivering personalized off-target predictions one guide at a time
A multi-omics pipeline integrating metabolomics and transcriptomics. Using a Variational Autoencoder (VAE), we can capture non-linear relationships that are missed by existing frameworks like MOFA
N/A
Rapidly predict antibiotic resistance from bacterial genomes, empowering physicians to choose effective treatments in seconds.
Pathogenicity detection using protein language models.
Smarter Diagnostics for a Growing City: Brain Cancer Care Without Delays.
A Modular Framework for Protein Design Using Large Language Models and Diffusion Models
By predicting drug side effects using AI, we can flag risks before drug trials to save years, billions, and most importantly lives. Our model enhances scRNA data with physiochemical drug properties.
A comprehensive framework for analyzing cross-experiment consistency, implementing quality control protocols, and developing imputation strategies for sparse MAVE datasets.
Lipid nanoparticles are a promising emerging technology used to deliver drugs into the cell. Our goal is to create an efficient screening website for lipids during the synthesis stage, based on pKa.
The most fundamental project in the field of neuromorphic networks, artificial intelligence and the robotics industry
We’re exploring whether blood-based DNA methylation can help diagnose Alzheimer’s disease as a less invasive alternative to brain tissue. We built a web app and did a Epigenome-Wide Association Study.
The all-in-one healthcare command center combining medical records, appointments, predictive alerts, virtual care, and lifestyle analytics — improving patient outcomes and reducing workforce burnout
AI-powered platform that integrates neural signals, sleep patterns, and lifestyle data to predict cognitive decline risk early and guide preventive care.
NeuroGuard uses brain waves, sleep, and lifestyle data to predict cognitive risks and deliver personalized brain-health interventions
1 – 24 of 24
