Uploaded April 2026 | Updated September 2026, 3 weeks ago
Dr. Silvano Colombano received an M.A. in Physics and a Ph.D. in Biophysical Sciences from the University at Buffalo. He has spent most of his working career at NASA-Ames Research Center first as a researcher in Closed Ecological Life Support Systems (CELSS) and later in Artificial Intelligence and Robotics. He began the development work on the Astronaut Science Advisor (a.k.a. PI-in-a-box) and managed the project until its deployment on SLS-2 (Space Shuttle STS -58) in 1993. He has been doing research and development work in Artificial Neural Networks, Genetic Algorithms and Fuzzy Logic in the Intelligent Systems Division at NASA-Ames. He is author or co-author of over 80 technical publications. He lead a group in “Evolutionary Biotronics”, comprising projects in Evolutionary Hardware, Modular Cooperative Robotics and Artificial Life, and organized a workshop on Self-Sustaining Robotic Ecologies called “Robosphere “ in 2002, 2004 and 2006. He has been interested in self-deploying robotic space structures. He has worked on Systems Engineering for the Orion space capsule flight S/W and a Fault Management System for the Deep Space Habitat. The last project Silvano led at NASA (2019-20) was the development of Autonomous Medical Operations (AMO), a machine learning system for providing autonomy in medical care for astronauts during deep space missions. He is now retired and active in consulting and teaching projects.
The field of UAP studies faces challenges that go beyond overcoming the old stigma. Some of these challenges are simply due to a lack of clarity in how we present ourselves to the scientific world. What exactly is UAP research? What is Ufology? (interesting that the term “Uapology” has not yet emerged). I propose that unpacking this term may facilitate both acceptance and progress.
In spite of recent visibility in congress committees, it seems to me that “UAP research” is mostly still understood as an effort to prove the existence of the phenomenon. In this context much work continues to be done in analyzing images, and the “researcher” is an image processing engineer. However, I contend that the bulk of “proof of existence” work is in the analysis of historical data. In this case the researcher can be a historian to understand the background of various databases, a scientist/engineer to evaluate the alleged anomaly reported, or a psychologist to evaluate the reliability of human witnesses. Note that even the “scientist/engineer” expertise is challenged by the likely variety of phenomena, possibly involving astronomical observations, object dynamics, electrical interactions, etc. Given this complexity, It shouldn’t be surprising that any particular report can be challenged by some “external” expert, but this is not different from any science that relies on large sets of
observed data. Any particular data point can be an error, but the bulk of the data cannot be ignored. Stil the question remains: who is a UAP researcher and what expertise does s/he have?
We need to get away from “proof of existence research”. There are data we can analyze. The characterization of these data can reveal “structures” that eliminate any possible doubt about the reality of the UAP phenomenon. A good example is Robert Powell’s work on characterizing the types of object shapes that have been reported. The limited amount and similarities of reported shapes out of several thousands reports cannot be attributed to chance or fervid imaginations. As in other sciences, the structures revealed in the data validate the value of most data points. In this case the researchers are data analysts.
A related approach is to proactively gather data in controlled conditions (UAPx, Galileo). This allows for gathering the expertise that is necessary for specific types of observations, and, hopefully, obtain “clean” data. Here the researchers will typically be experimental physicists able to judge the degree of “anomaly” in any instrumental observations.
Finally, based on observations of anomalous physical behaviors (speeds, accelerations etc.), we have physicists theorizing (or speculating) on possible advanced propulsion systems or different understanding of physical reality. This is an area of research that is as legitimate as any in advanced physics, but probably even more challenging given the potentially extremely large gap between theory and possible experimental verification. This makes UAP research in this area again vulnerable to the old stigma.
I propose that we will be able to make headway mainstream science when we carefully define the specific areas where we can contribute to scientific progress, independently of assumptions that can be made about the nature of UAP.
Dr. Silvano Colombano received an M.A. in Physics and a Ph.D. in Biophysical Sciences from the University at Buffalo. He has spent most of his working career at NASA-Ames Research Center first as a researcher in Closed Ecological Life Support Systems (CELSS) and later in Artificial Intelligence and Robotics. He began the development work on the Astronaut Science Advisor (a.k.a. PI-in-a-box) and managed the project until its deployment on SLS-2 (Space Shuttle STS -58) in 1993. He has been doing research and development work in Artificial Neural Networks, Genetic Algorithms and Fuzzy Logic in the Intelligent Systems Division at NASA-Ames. He is author or co-author of over 80 technical publications. He lead a group in “Evolutionary Biotronics”, comprising projects in Evolutionary Hardware, Modular Cooperative Robotics and Artificial Life, and organized a workshop on Self-Sustaining Robotic Ecologies called “Robosphere “ in 2002, 2004 and 2006. He has been interested in self-deploying robotic space structures. He has worked on Systems Engineering for the Orion space capsule flight S/W and a Fault Management System for the Deep Space Habitat. The last project Silvano led at NASA (2019-20) was the development of Autonomous Medical Operations (AMO), a machine learning system for providing autonomy in medical care for astronauts during deep space missions. He is now retired and active in consulting and teaching projects.
The field of UAP studies faces challenges that go beyond overcoming the old stigma. Some of these challenges are simply due to a lack of clarity in how we present ourselves to the scientific world. What exactly is UAP research? What is Ufology? (interesting that the term “Uapology” has not yet emerged). I propose that unpacking this term may facilitate both acceptance and progress.
In spite of recent visibility in congress committees, it seems to me that “UAP research” is mostly still understood as an effort to prove the existence of the phenomenon. In this context much work continues to be done in analyzing images, and the “researcher” is an image processing engineer. However, I contend that the bulk of “proof of existence” work is in the analysis of historical data. In this case the researcher can be a historian to understand the background of various databases, a scientist/engineer to evaluate the alleged anomaly reported, or a psychologist to evaluate the reliability of human witnesses. Note that even the “scientist/engineer” expertise is challenged by the likely variety of phenomena, possibly involving astronomical observations, object dynamics, electrical interactions, etc. Given this complexity, It shouldn’t be surprising that any particular report can be challenged by some “external” expert, but this is not different from any science that relies on large sets of
observed data. Any particular data point can be an error, but the bulk of the data cannot be ignored. Stil the question remains: who is a UAP researcher and what expertise does s/he have?
We need to get away from “proof of existence research”. There are data we can analyze. The characterization of these data can reveal “structures” that eliminate any possible doubt about the reality of the UAP phenomenon. A good example is Robert Powell’s work on characterizing the types of object shapes that have been reported. The limited amount and similarities of reported shapes out of several thousands reports cannot be attributed to chance or fervid imaginations. As in other sciences, the structures revealed in the data validate the value of most data points. In this case the researchers are data analysts.
A related approach is to proactively gather data in controlled conditions (UAPx, Galileo). This allows for gathering the expertise that is necessary for specific types of observations, and, hopefully, obtain “clean” data. Here the researchers will typically be experimental physicists able to judge the degree of “anomaly” in any instrumental observations.
Finally, based on observations of anomalous physical behaviors (speeds, accelerations etc.), we have physicists theorizing (or speculating) on possible advanced propulsion systems or different understanding of physical reality. This is an area of research that is as legitimate as any in advanced physics, but probably even more challenging given the potentially extremely large gap between theory and possible experimental verification. This makes UAP research in this area again vulnerable to the old stigma.
I propose that we will be able to make headway mainstream science when we carefully define the specific areas where we can contribute to scientific progress, independently of assumptions that can be made about the nature of UAP.
