diff --git a/.env.example b/.env.example
index 69287896..53c414f1 100644
--- a/.env.example
+++ b/.env.example
@@ -43,4 +43,5 @@ TEAM_IDENTIFIER=
#Resend
RESEND_API_KEY=""
-RESEND_FROM_EMAIL=""
+RESEND_FROM_EMAIL="deandrebailey@outlook.com"
+AUTH_SECRET=
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new file mode 100644
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diff --git a/apps/blade/public/valorant.png b/apps/blade/public/valorant.png
new file mode 100644
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diff --git a/apps/blade/src/app/deandrebailey/page.tsx b/apps/blade/src/app/deandrebailey/page.tsx
new file mode 100644
index 00000000..de8a1bdc
--- /dev/null
+++ b/apps/blade/src/app/deandrebailey/page.tsx
@@ -0,0 +1,564 @@
+import { Mail, Phone, MapPin, Github, AlertTriangle } from "lucide-react";
+
+const CONTACT_INFO = {
+ name: "DEANDRE BAILEY",
+ title: "Computer Science Student",
+ email: "deandrebailey.isaiah@gmail.com",
+ phone: "561-497-5405",
+ location: "Orlando, Florida",
+ github: "github.com/SquidDre",
+ githubUrl: "https://github.com/SquidDre",
+};
+
+
+
+const SKILLS = {
+ "Programming Languages": ["Python", "Java", "C", "JavaScript", "TypeScript", "SQL", "HTML/CSS"],
+ "Frameworks & Tools": ["React", "Next.js", "React Native", "Node.js", "MongoDB", "PostgreSQL", "Prisma", "TailwindCSS", "Git"],
+ "Machine Learning & Data": ["Scikit-learn", "NumPy", "Pandas", "UMAP", "PCA", "FAISS", "Sentence Transformers"],
+};
+
+const EXPERIENCE = [
+ {
+ title: "Office Assistant",
+ company: "University of Central Florida",
+ location: "Orlando, FL",
+ period: "Feb. 2025 – Present",
+ description: [
+ "Support daily operations, scheduling, document management, and student assistance",
+ "Assist 20+ students and faculty, improving office efficiency",
+ ],
+ },
+ {
+ title: "Technology Assistant",
+ company: "BPCS (Cooper City Elementary School)",
+ location: "Cooper City, FL",
+ period: "Jun. 2023 – Jul. 2024",
+ description: [
+ "Maintained 50+ laptops and desktops weekly for classroom readiness",
+ "Designed digital displays and managed tech inventory for improved accessibility",
+ ],
+ },
+];
+
+const EDUCATION = [
+ {
+ degree: "Bachelor of Science in Computer Science",
+ school: "University of Central Florida, Burnett Honors College",
+ period: "Expected Graduation 2028",
+ coursework: [
+ "Object-Oriented Programming",
+ "Data Structures & Algorithms",
+ "Calculus I & II",
+ "Discrete Structures",
+ ],
+ },
+];
+
+const PROJECTS = [
+ {
+ name: "Animore+",
+ period: "Aug. 2025 – Present",
+ status: "ACTIVE",
+ description:
+ "ANN-based recommendation system leveraging Sentence Transformers to generate semantic vector embeddings from anime text data with interactive 2D visualization.",
+ technologies: ["Python", "Next.js", "React Native", "MongoDB Vector Search", "FAISS", "Scikit-learn", "UMAP"],
+ highlights: [
+ "Engineered ANN-based recommendation system with Sentence Transformers for semantic embeddings",
+ "Implemented high-performance vector retrieval using MongoDB Vector Search and FAISS index",
+ "Applied UMAP and PCA to reduce 384-dimensional embeddings to 2D for interactive visualization",
+ ],
+ },
+ {
+ name: "DAVe Card",
+ period: "Oct. 2025",
+ status: "COMPLETED",
+ description:
+ "Social contact management app with CardDAV backend for real-time multi-client synchronization and OAuth integration.",
+ technologies: ["Next.js", "TypeScript", "TailwindCSS", "PostgreSQL", "Prisma", "NextAuth"],
+ highlights: [
+ "Developed social contact management app with CardDAV backend for real-time synchronization",
+ "Designed modern UI and OAuth login (Google, Discord, GitHub) with PostgreSQL via Prisma ORM",
+ "Engineered RFC 6352-compliant backend endpoints with optimized caching",
+ ],
+ },
+ {
+ name: "Linear Regression App",
+ period: "Sep. 2024 – Oct. 2024",
+ status: "COMPLETED",
+ description:
+ "Interactive application predicting student performance using linear regression and gradient descent with real-time visualization.",
+ technologies: ["Python", "Pandas", "NumPy", "Scikit-learn", "Matplotlib"],
+ highlights: [
+ "Built interactive app predicting student performance using linear regression and gradient descent",
+ "Leveraged NumPy for matrix operations and Matplotlib for real-time visualization",
+ ],
+ },
+];
+
+const INVOLVEMENT = [
+ {
+ organization: "Knight Hacks",
+ role: "Member",
+ period: "Aug. 2024 – Present",
+ description: [
+ 'Led a 4-member team at KnightHacks VII to build "Right Meow," a cat-matching application',
+ "Contributed to hackathon planning, project challenges, and prototype presentations",
+ ],
+ },
+];
+
+export default function Resume() {
+ return (
+
+ {edu.school} +
+Relevant Coursework:
++ {project.description} +
+ ++ {job.company} +
+{job.location}
+
+ Actively seeking internship and full-time opportunities in software engineering.
+
+ Transmission frequency ready for synchronization.
+
+
+ + I want to join the Dev Team because I want to help create tools and apps for the members of the club to use. When I first heard that the club created and is continuing to develop Blade, I thought it would be cool to code an application that makes doing what the club needs easier by doing the thing that the club does all year round. Code! +
++ However, just observing is not enough; I want to keep making the app flourish. Witnessing the improvement of the app when used in Hackathons and new features made me want to get involved. In addition, I want to see what the next amazing tools we can make are, not limited to just Blade, but more amazing tools that will get the next generation of Hack members to take the club and its tools to the next level. +
++ One of the coolest projects I worked on was an anime recommendation system using machine learning I call Animore. I built a neural network-based recommender system that suggests anime based on similarity patterns and user preferences. I focused mainly on the ML side: data processing, feature representation, and model evaluation. +
++ In addition to this, I wanted to use a unique way of showing these recommendations, so I used UMAP to map anime to an interactive map for users to navigate for recommendations based on their proximity to other anime. This was also my first time working with MongoDB and Vectors. +
++ This project taught me how to work with real data and design ML pipelines to create a project with a personal interest, which I thoroughly enjoyed. +
+
+ Thanks for getting to know me a little better.
+
+ Let's build something amazing together.
+