My name is Jason H. Moore, Ph.D. and I am a retro computer and retro gaming enthusiast. As a kid in the 1970s and 1980s, I had an Atari 2600 Video Computer System (VCS) followed by an Atari 400 and then an Atari 800 home computer. I had exposure to other systems including the Apple II and Commodore VIC-20. I learned to program in BASIC and dabbled with Pilot and Assembly. I found the Atari systems to be very inspiring and my experience with them set up a lifelong interest in computer science and informatics that set the stage for my career as a biomedical informatician and AI researcher. This site is modeled after my successful Atari Projects site that now has over 300 project posts.
I am having tons of fun revisiting these old systems today. I have a pretty big collection of old systems including Atari, Apple, and Commodore. I have also tried my hand at developing a retro edutainment game called Gene Medic in assembly language for the Atari 2600. My goal with this web page is to share some of the fun I am having in the hopes that it will make it easy for others to carry out fun projects with their old systems. Enjoy!
If you are curious about my day job, I am Chair of the Department of Computational Biomedicine at Cedars-Sinai Medical Center where I direct the Center for Artificial Intelligence Research and Education and helped launch the new PhD Program in Health Artificial Intelligence. I do research on agentic artificial intelligence (AI) and automated machine learning (AutoML) algorithms and methods with application to biomedical and clinical data. Some of my recent AI projects include the tree-based pipeline optimization tool or TPOT, Aliro AI, AlzKB AI, KRAGEN, ESCARGOT, EcoXAI for Agentic AI. A central theme to my research is democratizing AI through automated machine learning and agentic AI. Here is my Health AI Insights Substack where I post about agentic AI for health care. I am @moorejh on Bluesky. Here is my LinkedIn page.
Here are a few of our research papers:
Agentic AI and the rise of in silico team science in biomedical research
Evaluation of a tree-based pipeline optimization tool for automating data science
TPOT: A tree-based pipeline optimization tool for automating machine learning
Scaling tree-based automated machine learning to biomedical big data with a feature set selector
Evaluating recommender systems for AI-driven biomedical informatics
The Alzheimer’s Knowledge Base: A knowledge graph for Alzheimer disease research
