Randy R. Reibel
Measuring how knowledge systems accumulate, compress, and saturate.
Independent researcher developing information-theoretic tools to measure how scientific knowledge accumulates, compresses, and saturates over time. Previously founder and CEO of Blackmore Sensors and Analytics (acquired by Aurora Innovation, 2019) and VP of Lidar at Aurora. PhD in Optical Physics, Montana State University.
Knowledge as a communications path.
Knowledge, viewed through a signal-processing lens, is a communications path between the past and the present. Scientific fields, software ecosystems, biological taxa, and patent catalogs each accumulate structure and extract information about their underlying reality. They should exhibit measurable signatures of saturation as the large eigenvalues are captured and diminishing returns set in.
The research program is empirical. ArXiv papers, Wikipedia articles, GitHub commit histories, and IETF standards are parsed, embedded, and compressed using complementary techniques: principal component analysis on sentence-transformer embeddings, perplexity-based marginal information from from-scratch GPT-2 training, low-rank adaptation of pretrained models, gzip baselines, and sparse autoencoder feature counting. Each technique captures a different property of structural regularity.
The framework has consequences beyond scientometrics. If knowledge systems saturate, the intelligence explosion has a ceiling. If diminishing returns on mined information are universal, the Fermi Paradox admits an information-theoretic resolution: advanced civilizations may rationally stop expanding once the energy cost of extracting new mutual information exceeds the value of what remains to be found.
A thirty-year through-line.
The research program is new. The underlying question is not. For three decades, across physics research and lidar commercialization, Reibel has worked on a single problem in different forms: how signal gets extracted from noise, and where the fundamental limits lie. The substrate changed. The instinct did not.
He earned a combined B.S. in Physics and Computer Science from Western Washington University in 1996 before pursuing optics at Montana State University, where he joined Randy Babbitt's lab working on photon echoes and spatial-spectral holography in rare-earth-doped crystals. His 2002 PhD thesis demonstrated high-bandwidth optical coherent transient true-time delay, a technique for steering phased-array radars across extreme bandwidths using Tm:YAG crystals cooled with liquid helium.
After a postdoctoral stint at the U.S. Air Force Academy working on high-energy lasers and holographic wavefront sensing, Reibel returned to Bozeman to co-found S2 Corporation, commercializing spatial-spectral holography for wideband radar signal processing. He and colleague Pete Roos co-founded Bridger Photonics in 2006 to commercialize ultra-linear chirped laser sources. At Bridger he also developed computational imaging techniques for lidar, using compressed sensing to reconstruct high-resolution imagery from sparse measurements.
In 2015, Reibel spun FMCW lidar technology out of Bridger into Blackmore Sensors and Analytics, recognizing that autonomous vehicles needed what coherent lidar uniquely offered: continuous low-peak-power operation, simultaneous range and velocity measurement, and effective immunity to interference. Blackmore pioneered the commercial positioning of FMCW lidar and attracted strategic investment from BMW, Toyota, and FLIR. In 2019, the company was acquired by Aurora Innovation, where Reibel served as VP of Lidar through the Uber ATG integration and the company's transition to a public entity. He stepped away from industry in 2022.
Signal extraction, in many forms.
Curated from a full publication record of 60+ peer-reviewed papers and conference proceedings.
Sixteen issued or pending.
Spanning work at Montana State University, USAF, Bridger Photonics, Blackmore Sensors and Analytics, and Aurora Innovation.