Developed a full-stack web application
(TypeScript/JavaScript) to generate
rarity rankings for NFT's, integrating with leading
marketplace’s API to enable users to quickly identify
rare NFT's and check their listing status, improving
market research efficiency by 80%.
Built a scalable Node.js backend with REST API
endpoints to return NFTs based on customizable filters
such as max rank, price, and rarest traits. Optimized
performance to handle 3,000+ concurrent requests by
implementing efficient data fetching and caching
mechanisms using PostgreSQL , ensuring low-latency
access to NFT data.
Built a dynamic React frontend (TypeScript/JavaScript) to load and display NFTs in real-time with user-defined filters. Styled
using a mobile-responsive library, reducing load times by 50%.
Developed a Discord bot (TypeScript/JavaScript/Node.js) to notify users of profitable
resale opportunities by leveraging historical sales data
to assess deal quality. This feature increased user
engagement by 80% and provided a seamless way for users
to stay updated on market opportunities.
Astronofty
<JavaScript, React, Solidity>
Jan 2023
Secured 2nd place overall out of 150+ teams at UofTHacks
X, a 36-hour hackathon, for developing a blockchain-based
NFT marketplace app.
Built and optimized React (JavaScript) components to synchronously
upload images and metadata to IPFS, enhancing user engagement by 80% during the demo.
Reduced deployment time by 66% by implementing a
solution for deploying locally-compiled binaries onto
Kubernetes/OpenShift via command-line, cutting average
deployment times from 45 minutes to 15 minutes.
(Kubernetes/GoLang used for this and three below).
Eliminated 80% of manual configuration errors by enabling
the Kubernetes operator to automatically fetch data from
deployed services and update configurations, deprecating
legacy startup scripts and reducing overall startup time
by 40%.
Improved application stability by introducing startup
probes for legacy applications with longer boot times,
resulting in a 50% reduction in startup-related failures
and downtime during production launches.
Enhanced system reliability by refactoring probes to
assign default values dynamically based on deployed YAML
files and fixing reconciliation issues, increasing probe accuracy by 30% and preventing misconfigurations.
Increased CI pipeline efficiency by rewriting the
Jenkins (Groovy)nightly pipeline to run in a GitHub PR
environment, allowing for automated testing of all
team-submitted PRs prior to merging, reducing manual
intervention by 60%.
Increased project reproducibility by taking initiative to
write a reusable GitHub parameters file for the pipeline,
enabling 100% reusability and ensuring consistent pipeline
setups across different environments.
Streamlined developer onboarding by authoring
comprehensive project documentation and mentoring an
incoming intern, reducing onboarding time by 50% and
enhancing new team members’ productivity within their
first sprint.