Information Systems Student | Builder

Building AI Systems That Help Students Plan, Learn, And Launch

I design full-stack dashboards, recommendation systems, and interactive products that turn messy student workflows into clear decisions, saved records, and next actions.

Generative AI Data Analysis Full-Stack Development Information Systems Student Success
JavaScript Python FastAPI SQLite SQL Power BI GitHub Pages Render

Selected Work

Featured Projects

Projects built around real student decisions: career planning, labor market intelligence, academic resource selection, and campus-life tradeoffs.

CareerLens project thumbnail
Live Data workflow Case study GitHub
Labor Market Intelligence JS + Python + SQL

CareerLens

A career-readiness dashboard that analyzes job postings, detects demanded skills and certifications, compares role fit, and turns resume gaps into an application-ready plan.

Impact Helps students compare roles, identify skill gaps, prioritize certifications, and create application-ready next steps.
Stack JavaScript, Python, SQL, CSV Workflow, GitHub Pages
  • Built role-based analysis for student-facing tech paths.
  • Added CSV pipeline and SQL schema for scalable market intelligence.
  • Generated Opportunity Radar, priority insights, decision briefs, portfolio evidence, and application packet assets.
Proof of Work Role Filters, Skill Demand, Certification Signals, Resume Gaps, Opportunity Radar, Decision Briefs, and Application Packet Logic.
LearnWise project thumbnail
Live Recommendation logic Case study GitHub
Academic Decision Support HTML + CSS + JavaScript

LearnWise

An academic resource optimization platform that ranks study recommendations by urgency, topic weakness, learning preference, time, and expected ROI, then saves plans for comparison.

Impact Turns course pressure, weak topics, deadlines, and time available into ranked study plans students can save and export.
Stack JavaScript, HTML/CSS, Recommendation Logic, Local Storage, GitHub Pages
  • Built custom recommendation logic for UMBC-style course planning.
  • Designed academic ROI scoring to prioritize high-impact study actions.
  • Created strategy briefs, deadline-aware schedules, saved plan history, plan export, risk scoring, and resource rankings.
Proof of Work Course Risk Scoring, Study Resource Ranking, Strategy Briefs, Schedule Generation, Saved Plan History, and Plan Export.
15 Weeks at UMBC project thumbnail
Live Browser game Case study GitHub
Interactive Systems Java + Processing + JavaScript

15 Weeks at UMBC

A choice-based campus-life strategy game where players manage health, food, grades, money, stress, support, and career readiness through a semester.

Impact Transforms campus-life decisions into a playable simulation with tracked stats, achievements, and semester outcomes.
Stack JavaScript, HTML/CSS, Game State Logic, Browser Storage, GitHub Pages
  • Built meaningful tradeoff systems across seven connected student variables.
  • Added save/load support, achievements, multiple endings, and profile-specific events.
  • Converted the original Processing project into a deployable browser game.
Proof of Work Decision Engine, Seven Tracked Stats, Save/Load, Achievements, and Multiple Endings.

Featured Case Study

Nexus AI: from scattered career prep to one student operating system

Nexus AI started from a simple problem: students prepare for internships across too many disconnected places. The product turns applications, skills, projects, resume notes, networking, and deadlines into one workspace with readiness signals and next actions.

8 career modules
3 API roadmap issues
API career report endpoint
Animated Nexus AI product showcase

Capabilities

What I bring into project work

I focus on building tools that explain what matters, store useful data, and guide people toward the next action.

FastAPI + SQLite

Nexus AI: Built a hosted backend for storing profile data, applications, goals, projects, contacts, resume notes, and career reports.

Data Analysis

CareerLens: Converted job-posting patterns into role insights, skill demand, certification recommendations, Opportunity Radar, and application-ready next steps.

Recommendation Logic

LearnWise: Ranked study actions by urgency, weak topics, time available, expected academic impact, deadline-aware schedule fit, and saved plan history.

Interactive Systems

15 Weeks at UMBC: Designed a decision engine where each action changes player stats and endings.

Deployment

Portfolio + Projects: Shipped browser-ready apps through GitHub Pages and hosted backend services through Render.

Product Thinking

All Projects: Framed student problems, built usable workflows, and connected features to resume-ready outcomes.

About

Information systems student building practical AI products

I am a UMBC Information Systems student focused on AI, data analysis, and software tools that help students make better academic and career decisions. My work combines front-end product design, backend data storage, recommendation logic, and deployment so each project can be used, tested, and explained beyond a classroom setting.

Product Focus Career planning, learning decisions, campus-life tradeoffs, and student productivity.
Build Style Usable interfaces, saved user data, clear next actions, and case-study documentation.
Direction Turning Nexus into a stronger full-stack product with authentication, database upgrades, and AI coaching.

Resume

My Resume

A concise snapshot of my Information Systems coursework, AI/data skills, deployed projects, certifications, and technical experience.

My Resume
3 Resume Projects AI + Data Focus Backend Experience