🔭 I’m currently deepening my work in Genetic Algorithms and adaptive learning systems, exploring how evolving models can optimize themselves the way natural systems do.

🎙️ I’m also passionate about Voice AI and real-time systems. I’ve built low-latency speech-to-text → LLM → text-to-speech pipelines, optimized concurrency paths, and shipped features that improved both performance and user retention.

🛠️ I love building distributed, reliable backend systems — from high-throughput event pipelines to cloud-native microservices on AWS. Turning ambiguous problems into simple, well-designed systems is where I do my best work.

🤝 I’m looking to collaborate on end-to-end deep learning or systems projects, especially those involving LLMs, NLP pipelines, real-time inference, or large-scale architecture.

🌱 Currently expanding my work in PyTorch, advanced computer vision, and cross-platform model deployment across M1, x86, and ARM (including ONNX and compiled runtimes).

💬 Ask me anything about machine learning, neural networks, distributed systems, or how AI can be engineered to behave more intelligently, more responsively, and more human-aligned.

👨‍💻 Languages

🌐 Web & API

🧠 Machine Learning & AI

🧠 LLMs & NLP

🛠️ Tools & Deployment

🗄️ Databases

🎨 Design (Optional)

• 🔍 CRISP – Multi-model client insight engine combining sentiment analysis, risk modeling, and GPT-based scoring.
• 🧠 AutoMind – Memory OS that indexes and retrieves everything you read/watch/hear via embeddings + RAG.
• 🌐 DistNote – Distributed peer-to-peer note sharing with gossip protocol and conflict resolution.
• 📊 CacheSim-Lite – C++ simulator for evaluating cache eviction strategies under real-world loads.
• ⏳ TimeTravelDB – Time-traveling query engine for versioned data with temporal indexing.