Overview
At the University of Michigan Law School’s IT group, I focus on .NET applications and the data structures that support them. The role also involves low-code workflow solutions, AI enablement, and finding problems before they escalate.
Context
Academic IT environments are flexible but resource-constrained. The Law School needs reliable applications for students, faculty, and staff, with data that’s consistent and maintainable. My work centers on improving how that data is structured and how applications interact with it.
What I Did
- .NET applications: Develop and maintain applications in C# and .NET. These support core Law School operations and reporting.
- Data restructuring: Lead ongoing work to restructure underlying data models. The goal is cleaner schemas, easier maintenance, and better alignment with how the school actually works.
- Low-code and automation: Use low-code platforms where they fit—workflows, approvals, simple automations. These complement rather than replace core applications.
- AI enablement: Explore and introduce AI-assisted tools where they add value. Emphasize practical, incremental adoption.
- Proactive problem finding: Look for pain points, technical debt, and process gaps before they become incidents. Propose and implement improvements.
Technical Approach
- C# and .NET for primary applications.
- SQL Server for data storage and restructuring.
- Low-code tools for workflow and automation where appropriate.
- Iterative delivery—small, testable changes over large rewrites.
Outcomes
- Continued delivery of reliable .NET applications for Law School operations.
- Progress on data structure improvements, making the system easier to maintain and extend.
- Introduction of low-code and AI tools where they fit the environment.
What I Learned
Flexible environments require clear priorities. Choosing what to improve first—data structures, applications, or tooling—is as important as the implementation. Proactive problem finding and leadership by doing help build trust and momentum.