I'm a Data Science graduate student at Arizona State University with a passion for building intelligent AI systems. Currently working on cutting-edge AI/ML for Protein Modeling with CUDA optimization and distributed systems. Experienced in Generative AI, LLMs, RAG pipelines, and medical AI. Published researcher with expertise in Computer Vision, Quantum ML, and Deep Learning.
Jul 2025 - Oct 2025 | Tempe, AZ
Focus: Protein Modeling • CUDA Optimization • Distributed ML • PyTorch Lightning
Impact Highlights:
- Reduced preprocessing time by 60% for production ML pipeline processing 1M+ sequences
- Improved cluster quality by 35% and reduced computational overhead by 45% with CUDA-RAPIDS
- Achieved 80% faster training convergence with custom CUDA kernels
- Delivered 6x speedup in hyperparameter optimization for production deployments
Tech: PyTorch Lightning • CUDA • RAPIDS • Scikit-Learn • Distributed Systems • YAML
May 2024 - Sep 2024 | Los Angeles, CA
Focus: Generative AI • LLMs • RAG • AI Chatbots • MLOps
Impact Highlights:
- Increased system reliability by 42% and data accessibility by 63%
- Boosted chatbot response accuracy by 37% with transformer-based models
- Achieved 86% increase in data throughput with RAG techniques
- 📦 Reduced model size by 29% using 8-bit quantization
Tech: LangChain • OpenAI API • Mistral • HuggingFace • Docker • Kubernetes • AWS • Azure • Sentence-BERT
Nov 2023 - May 2024 | San Francisco, CA
🎯 Focus: Medical AI • EEG/ECG Signal Processing • Brain-Computer Interfaces
Impact Highlights:
- ⚡ Reduced EEG processing latency by 25% for real-time applications
- 🎯 Achieved 90%+ accuracy in epilepsy detection with PyTorch models
- 🚀 Cut inference latency by 30% on AWS EC2 deployments
- 📉 Reduced false positives by 18% in artifact detection
Tech: PyTorch • TensorFlow • AWS • Vision Transformers • U-Net • Jenkins
Graduate Student @ ASU | Scientific Developer @ Cadence | Specializing in AI/ML, Protein Modeling & CUDA Optimization