About Me

Tony Angiola is a longtime UFO researcher, investigator, and writer with more than three decades of experience studying documented UFO cases and related phenomena. He is a former Mutual UFO Network (MUFON) Assistant State Director for Virginia and is best known for his extensive research into the 1964 Socorro, New Mexico UFO incident involving police officer Lonnie Zamora.

Tony began his work in UFO research in the early 1990s and, alongside that work, spent over 30 years in information technology as a PC technician and computer network engineer. Throughout those decades, he applied his technical background directly to UFO research, developing a reputation for careful investigation grounded in documentation, witness testimony, and physical data. His work has emphasized the technical and environmental aspects of UFO reports, including radiation effects, electromagnetic disturbances, and reported propulsion characteristics.

In 2015, Angiola partnered with fellow researcher Ben Moss to begin a focused, long-term reexamination of the Socorro case. Working under the banner of TUFOG (The UFO Guys), they conducted a multi-year investigation that uncovered new witness testimony and involved close collaboration with Ray Stanford, one of the original investigators of the incident. Their findings are detailed in the co-authored book SOCORRO UFO! Not of This World. Together, Angiola and Moss have presented their research at multiple MUFON symposiums and UFO conferences across the United States.

Angiola has appeared as a guest expert on television programs, including the History Channel’s Hangar 1: The UFO Files, Syfy’s NASA’s Unexplained Files, and other documentary productions focused on UFO research.

Now based in Colorado, Tony is a full-time writer and researcher for Rocky Mountain Ranch Research. His current work includes writing The Valley: Colorado’s Paranormal Triangle and developing the RMRR Investigators Timeline Tool, a public research platform currently in beta and free during development. The timeline spans from 1800 to the present day and currently contains just under 2,000 documented cases, complete with detailed reports, photographs, and video when available. The tool includes advanced reporting features, allowing users to print individual reports or export them to PDF. The long-term goal of the project is to train analytical algorithms to identify patterns within the data and ultimately develop a prediction model based on user-selected criteria.