From academic cell biology research to data science and AI systems, now building solutions where models inform real-world decisions.
🧠 Portfolio & Projects
https://dosorio79.github.io/portfolio
Projects, experiments, and write-ups live there — this GitHub hosts the code.
- 📊 Data science applications in pricing, marketing analytics, and decision systems
- 🤖 GenAI and agentic applications, including RAG pipelines and LLM-powered tools
- 🧠 NLP and ML applied to customer feedback and operational insights
- 🚀 Practical deployment of AI systems and data products
- 🤖 Agentic and GenAI applications for learning and knowledge workflows
- 🧩 Retrieval-augmented generation (RAG) and local LLM systems
- 👁️ CompVis — industrial safety face recognition app
Repo: https://github.com/kolapally/computer_vision
Demo: https://compvis.streamlit.app/
More projects and documentation are available in the portfolio above.
- Agentic AI systems
- Applied GenAI products
- LLMOps & local model deployment
- Responsible and practical AI adoption
- Data products delivering measurable business value
Generative AI, ML systems, experimentation, pricing analytics, RAG pipelines, or even cytoskeleton biology and CRISPR.
- LinkedIn: https://linkedin.com/in/dosorio
My first computer was an IBM PS/1 running MS-DOS. Learning to navigate directories, copy files, and manage storage manually built foundations that later reappeared in Linux, Bash, and development workflows.
After years in academic research studying cellular systems, I transitioned into data science, where experimentation, reproducibility, and analytical thinking remain central to how I build solutions today.
FastAPI · Vector databases · RAG pipelines · Local LLM deployment · Dockerized services
⚡ Fun fact: My first PC had 40 MB storage and 1 MB RAM — and we still got things done.