Hi, I am Jim Zieleman

Currently, I work as a Full Stack Software Engineer (Data Science, Networking, Front/Back-end), serving as a contractor for the federal government. In this role, I conduct research, development, and deployment of machine learning tools using cutting-edge models and techniques.

In my personal time, I am actively exploring and engaging with generative AI, expanding my knowledge and skills in this area. I have been experimenting with developing applications that harness the power of various machine learning techniques in conjunction with generative AI. Specifically, I have a strong interest in delving into prompt engineering and its applications. My goal is to deeply explore and understand Language Models (LLMs) and eventually incorporate text, imagery, and sound to create more comprehensive and multi-modal generative experiences. I have been actively working on LocalGPT is an open-source initiative that allows you to converse with your documents without compromising your privacy. With everything running locally, you can be assured that no data ever leaves your computer. Dive into the world of secure, local document interactions with LocalGPT. Github Repo and Demo (admin:admin).

My educational background includes a major in Quantitative Finance and Mathematics from James Madison University. This allows me to apply my broader data science skills to capital markets. Furthermore, I am currently pursuing a Master's degree in Data Science at the University of Virginia to further enhance and refine my data science expertise.

Throughout my professional journey, I have acquired substantial expertise in implementing cutting-edge methodologies for natural language processing (NLP). This includes leveraging advanced techniques such as Named Entity Recognition (NER), Topic Modeling, Semantic Similarity, Sentiment Analysis, and Relation Extraction.

Moreover, I possess significant experience in the field of computer vision (CV), particularly in tasks like Object Detection, Object Classification, and Optical Character Recognition (OCR).

In addition to my NLP and CV proficiency, I have also amassed extensive knowledge working with graph databases. I have not only constructed such databases but have also developed analytical capabilities for them, such as anomaly detection and pattern recognition. I am well-versed in the traversal language Gremlin, utilizing both its Python version and other implementations.

In addition to my expertise in machine learning and AI, I possess proficiency in end-to-end full stack development. This includes data gathering, data cleaning, and data manipulation using SQL and Pandas. I have developed and utilized various machine learning models for automation purposes, deploying them to web applications that range from REST APIs to comprehensive user interfaces.

I am always enthusiastic about exploring novel ideas that leverage data science techniques to inspire the development of innovative tools and applications. My development skills encompass Python, HTML, JavaScript, and Jinja, which I have employed to create applications that streamline workflows within my workplace. Moreover, I have also conducted real-time derivatives analysis and calculations, utilizing a combination of MS Excel, VBA, and Python.

Last updated June 16, 2023