Leif Peterson joined Rice University as a lecturer for the Department of Statistics in 2022. He is also  principal of NXG Logic, LLC, a data analytics software startup, and an independent consultant in biostatistics, bioinformatics, machine learning and neural networks. 

Peterson’s research interests include computational methods for statistics, biostatistics, bioinformatics, machine learning and neural networks, numerical optimization, Monte Carlo simulation, and text mining.

Prior to starting at NXG Logic in 2019, Peterson was a shuttle mission radiation specialist at NASA's Johnson Space Center (1986-1995), an associate professor of medicine at Baylor College of Medicine (1995-2006), director of the Center for Biostatistics at Houston Methodist Research Institute (HMRI, 2006-19), a professor of bioinformatics and biostatistics at the Institute for Academic Medicine, HMRI (2016-19), and a professor of healthcare policy and research at Cornell University via his appointment at HMRI (2006-2019). 

Peterson has held an adjunct associate professor appointment for many years at the University of Texas School of Public Health, Department of Biostatistics and Data Science (2011-19), where has taught biostatistics since 2011. He has also taught several courses at the University of Houston and Texas A&M University.

Peterson is a senior member of SIREN - Società Italiana Reti Neuroniche (Italian Neural Network Society), senior member of Institute for Electrical and Electronics Engineers (IEEE) and a senior member of its Computational Intelligence Society (CIS). He served on the IEEE-CIS Bioinformatics and Bioengineering Technical Committee (BBTC) and the IEEE-CIS-BBTC Task Force on Neural Networks.

Selected Publications:

Comparison of Gene Identification Based on Artificial Neural Network Pre-processing with k-Means Cluster and Principal Component Analysis

Optimization of classifier ensemble diversity

Improved dimension reduction for pattern classification using noise eigenspace projection

Artificial neural network analysis of DNA microarray-based prostate cancer recurrence

Classification analysis of surface-enhanced laser desorption/ionization mass spectral serum profiles for prostate cancer

Image classification of artificial fingerprints using Gabor wavelet filters, self-organizing maps and Hermite/Laguerre neural networks

Logistic ensembles of Random Spherical Linear Oracles for microarray classification

Machine learning-based receiver operating characteristic(ROC) curves for crisp and fuzzy classification of DNA microarrays in cancer research

Covariance matrix self-adaptation evolution strategies and other metaheuristic techniques for neural adaptive learning

Text-mining protein-protein interaction corpus using concept clustering to identify intermittency

Progression inference for somatic mutations in cancer

Adjustment of lifetime risks of space radiation-induced cancer by the healthy worker effect and cancer misclassification

In silico molecular dynamics docking of drugs to the inhibitory active site of SARS-COV-2 protease and their predicted toxicology and ADME

Books:

Peterson, L.E. Classification Analysis of DNA Microarrays. New York(NY), John Wiley and Sons, 2013.  ISBN 978-0-470-17081-6

Effects of Ionizing Radiation: Atomic Bomb Survivors and Their Children (1945-95). (Eds, Peterson, L.E., Abrahamson, S.). Washington (D.C.), National Academy Press, 1998.  ISBN 978-0-309-06402-6