Building across AI, full-stack development, and signal intelligence.
I'm Paila Akash, a Computer Science student who likes taking ideas apart, understanding how they work, and turning them into something useful. My projects connect language models, RF signals, and interactive web experiences.
- 🎓 Studying B.Tech CSE (Generative AI) at K L University.
- 🧠 Exploring LLM uncertainty, hallucination detection, and RAG.
- 📡 Building RF simulations, direction-finding tools, and visual dashboards.
- 🌱 Developing LILNEST, a maternal and child wellness app project.
- ✨ Experimenting with 3D interfaces, motion, and full-stack development.
- ⚡ My favorite kind of project: one that makes me learn something new.
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K L University |
🧠 Interpretable and evidence-aware AI |
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Languages |
Web Development |
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AI & Scientific Computing NumPy · SciPy · Matplotlib · Simulink |
Tools & Interfaces PyQt6 · PyQtGraph · GSAP |
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Can a model reveal when it's guessing? A research project exploring internal uncertainty signals in RAG. Includes entropy baselines, logistic and MLP probes, reproducible evaluation, and a local evidence-aware chat dashboard. Current results are predictive; causal and cross-model experiments remain future work.
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From invisible signals to visible patterns. A simulation and analysis workspace combining Python dashboards with MATLAB/Simulink models. Explore signal generation, spectrum views, recording replay, antenna arrays, and MUSIC-based direction estimation.
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Thoughtful software for everyday care. A maternal and child wellness application project with dashboard, medical-record, marketplace, and time-capsule modules. Combines a Next.js interface and Django backend, with interactive 3D elements and role-based user flows.
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The calculations behind the visualizations. A MATLAB/Simulink workspace for RF signal generation and processing, antenna-array modeling, direction and distance estimation, classification, and dashboard experiments.
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A playground for code, motion, and personality. A portfolio built with Next.js and TypeScript, featuring a 3D scene, particle effects, terminal animation, a command palette, and motion experiments with GSAP and React Three Fiber.
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A compact interface for a busy store. A lightweight, static admin-dashboard demo for products, orders, and customers. Uses seeded sample data and runs directly in the browser with plain HTML, CSS, and JavaScript.
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