Building intelligent systems from prototype to production — RAG pipelines, multi-agent LLMs, and everything in between.
I'm a Computer Science Master's graduate from Arizona State University (GPA: 3.89) with hands-on experience building production-grade GenAI systems, multi-agent LLM pipelines, and end-to-end ML solutions.
- 🔬 Currently working as an AI & Data Engineer at RVCoLab, ASU — building multimodal emotion-recognition systems, agentic voice AI, and real-time generative content pipelines
- 🤖 Deep experience with RAG architectures, ReAct agents, agentic orchestration (LangChain, LlamaIndex), and scalable model deployment across AWS, Azure & GCP
- 🎯 Open to GenAI Engineer, ML Engineer, and LLM/Agentic AI Engineer roles
- 🏆 Co-author of a granted patent in automated dermatology disease detection (IND 102069, Sept 2022)
AI & Data Engineer · RVCoLab, MIX Center – Arizona State University (Feb 2026 – Present)
- Building a multimodal emotion-recognition system fusing facial action unit detection (OpenCV, DeepFace) with biometric signals (EEG, GSR), feeding into an LLM-based context layer for real-time avatar behavior
- Developing an Agentic AI voice system using an ASR → LLM reasoning agent → TTS pipeline with a LangChain tool-calling layer, FAISS vector store, and autonomous avatar state triggers
- Designing end-to-end GenAI data pipelines: raw sensor ingestion → feature engineering → model inference → LLM-generated narrative output, tracked with MLflow and served via FastAPI
- Implementing real-time Stable Diffusion-based scene generation conditioned on user affect — reducing manual content curation time for researchers by 40%
GenAI & Agentic AI
ML & Deep Learning
Backend & APIs
Frontend & Visualization
Cloud & DevOps
🔨 Portfolio actively under construction — projects dropping soon. Watch this space!
Open to full-time GenAI / ML Engineer roles · Always happy to collaborate on interesting AI projects