MDC x CampusAI Hackathon 2026
An AI-Powered Weekly Planner for UMich Students
Team
Team #21
Date
March 2026
The Problem:
Inefficient Scheduling
Fragmented Information
The Cost of Manual Scheduling
Mental Health Impact
Meet Alex: Our Target User
Alex
Freshman, Computer Science
University of Michigan
Alex's Goals
Stay on top of assignments & studying
Attend campus events & club meetings
Maintain healthy work-life balance
Current Behaviors
Checks multiple websites for events
Writes tasks in Notes
Plans schedule 2 hours daily
Adjusts plans frequently
Alex is a UMich freshman trying to stay on top of academics and campus life. But with everything spread across different website, his schedule becomes overwhelming and hard to balance. Last week, he overloaded his schedule with events and missed assignments. Now he has given up on attending events, which has negatively impacted his work-life balance.
Let’s Hear About Alex’s Story
Our Solution: Mandala Weekly Planner
An AI-Powered Weekly Planner
Mandala automatically organizes student schedules by aggregating data from multiple sources and generating optimized weekly plans that balance academics, campus events, and personal time.
How It Works
1
Data Aggregation
Automatically pulls course data if provided and events from Happenings@Michigan
2
Intelligent Analysis
AI analyzes user preferences to understand optimal scheduling patterns
3
Schedule Generation
Creates balanced weekly schedules with study blocks, event recommendations, and personal time
Our Goal
Save time
No more manual entry—everything syncs automatically to user’s favorite calendar app
Balanced Living
Academics, events, and personal time in harmony
Cognitive Relief
Reduces decision fatigue and mental overhead
The Result?
Students like Alex can focus on learning and experiencing college life rather than managing calendars.
Demo: Alex's Week with Mandala
Link to Video Demo: https://youtu.be/MpA35XX8cEU
Link to Website: https://mandalaplanner.lovable.app/
Technical Architecture
System Architecture
Data Sources Layer
Events from Happening@Michigan • Courses from User
Data Processing Layer
Simple ETL Pipeline • Data Normalization
AI Engine (Google Gemini)
Schedule Planner • Priority Scores
Output Layer
Google Calendar • Web Dashboard
Because Every Student Deserves Balance
Imagine a world where no student misses opportunities, falls behind, or burns out due to poor scheduling. Where every learner can thrive academically while fully experiencing campus life.
That's the world Mandala is building—one optimized schedule at a time.
Problem Solved
Schedule Chaos
Data Sources
2 APIs
Tech Stack
AI-Powered
Thank You!
Questions? Let's discuss how Mandala can transform student success.
Key Features & Capabilities
Automatic Schedule Generation
Mandala creates optimized weekly schedules based on event priorities and personal preferences.
Saves 45+ min/week
Boost Focus Time
Mandala identifies work blocks based on user's productive hours and protects them from interruptions .
40% better retention
Event Recommendations
Explore relevant campus events based on major, interests, and availability. Never miss career fairs, workshops, or social activities.
Campus engagement
Impact & Validation
If a struggling learner used this today, would it actually help them?
Reduces cognitive load
Eliminates decision fatigue from constant schedule management
Improves academic outcomes
Better time allocation leads to improved grades and retention
Enhances well-being
Structured planning reduces stress and improves work-life balance
Maximizes opportunities
Ensures students don't miss events and leaves time for them to “study hard and play hard”
Data Sources & Integration
Integrated Data Sources
Happening@Michigan
Data Retrieved: Campus events, workshops, performances, career fairs, club meetings, location & time
User Input
Data Collected: Personal tasks, preferences, weekly routines, study habits
Google Calendar API
Synchronization for seamless schedule export and real-time updates.
Export AI-generated schedules with an .ics file
Sync with mobile devices
Real-time conflict detection