Research
Data-Driven Prompt Recovery
Researching how to predict viable inputs from groups of outputs produced by large language models.
AVAILABLE FOR COLLABORATION
Chris Nippert · Computer Science
Building fast, optimized code
Backend- and systems-oriented Computer Science graduate student focused on efficient software, AI/ML, and solving technically interesting problems.
Current focus
Independent tracks, shared curiosity
I am currently pursuing these as separate research and personal-project threads.
Personal hardware project
ESP32 Electric Drum Kit
A first hardware project using piezo-disk drum triggers, a 16-channel multiplexer, an ESP32, and a KiCad circuit design.
View repository ↗Selected work
Projects worth exploring
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Speculative Parallel Best First Search
A codebase for research on parallelizing best-first search algorithms (A*, etc.).
- Language
- C++
- Domain
- Parallel search
- Algorithm
- Best-first / A*
- Focus
- Speculative parallelism
Explore project -
Nearest Neighbor Bucket Map
A data structure designed to get a near neighbor given some key that doesn't exist in the structure. It utilizes a logarithmically sized stack of bucket maps.
- Language
- Julia
- Average case
- O(log s)
- Benchmarked
- 109.67 ns
Explore project -
Open Trove
AI-assistedA self-hosted inventory and collection manager with user-defined schemas. Build your own structure for anything — wardrobe, kitchen, board games, tools, whatever — then search, filter, and browse it all from one place.
- Backend
- FastAPI
- Frontend
- React + TypeScript
- Search
- SQLite FTS5
Explore project
Technical focus
How I like to work
I enjoy collaborative problem-solving: working through constraints, sharing ideas, and building practical, efficient solutions together. I am also proficient with AI tools and AI-assisted development workflows for exploration, iteration, and coding.
Backend SystemsAI / MLLLM TuningMultithreadingComplexity AnalysisLinuxCybersecurityAI-Assisted Development
Live sites