I’m an Information Science & Engineering student who focuses on how systems fail, scale, and behave under stress — not just how they look in demos.
I enjoy working at the intersection of:
- backend systems & correctness
- testing & failure analysis
- applied ML with deep error investigation
Most of my projects are not CRUD apps — they are built to answer questions like:
What breaks first? Why did it fail? How do we detect it earlier next time?
Languages
Python · JavaScript · TypeScript · C · SQL
Backend & Systems
FastAPI · Node.js · REST APIs · Concurrency Basics · System Testing
ML / NLP
PyTorch · HuggingFace Transformers · Model Evaluation · Error Analysis
Tools
Git · GitHub Actions · Docker (basic) · Postman · Linux
Python | System Reliability | Testing
- Designed a testing framework that injects failures instead of assuming success
- Simulates latency, retries, partial outages, and flaky dependencies
- Focuses on observability, logs, and reproducibility — not happy-path testing
- Inspired by real-world distributed system testing practices
👉 Repo: https://github.com/rishika638/failure-oriented-system-test-framework
Python | NLP | Research-style Project
- Studied failure modes of multilingual transformers on noisy Hinglish data
- Identified token fragmentation, English-anchor bias, and confidence collapse
- Emphasis on why models fail, not just accuracy numbers
- Built a clean evaluation + error inspection pipeline
👉 Repo: https://github.com/rishika638/hinglish-transformer-failure-analysis
Python | Data Analysis | Visualization
- Interactive dashboard for exploratory medical data analysis
- Focused on feature behavior, distributions, and correlations
- Designed for interpretability over flashy UI
👉 Repo: https://github.com/rishika638/breast-cancer-dashboard
Automation | Python
- Automated job discovery and tracking workflow
- Reduced manual search noise with structured filtering
- Built with safety limits to avoid platform abuse
👉 Repo: https://github.com/rishika638/linkedin-job-automator
- Distributed system testing ideas
- Backend correctness & failure handling
- Production-grade project structuring
- DSA with real-world problem mapping