SCIENTIFIC COMPUTING AND IMAGING INSTITUTE
at the University of Utah

An internationally recognized leader in visualization, scientific computing, and image analysis

Background

Orly Alter is a Utah Science, Technology, and Research associate professor of bioengineering and human genetics at the Scientific Computing and Imaging Institute1  and the Huntsman Cancer Institute at the University of Utah, a scientific advisory board member of the National Cancer Institute (NCI) -DOE Cancer Moonshot collaboration on predictive oncology, and the chief scientific officer and a co-founder of Prism AI.2  Alter received her Ph.D. in applied physics at Stanford University and her B.Sc. magna cum laude in physics at Tel Aviv University. Her Ph.D. thesis, which was published by Wiley,3,4,5  is recognized as crucial to gravitational wave detection and quantum computing.6,7,8 

Research Interests

Inventor of the "eigengene,"9,10,11,12  Alter formulates comparative spectral decompositions, physics-inspired13  multi-tensor14,15,16  generalizations17,18,19,20  of the singular value decomposition, to (i) compare and integrate any data types, of any number and dimensions, and (ii) scale with data sizes. Her models (iii) are interpretable in terms of known biology and batch effects and (iv) correctly21  predict22,23,24,25,26  previously unknown mechanisms.27,28  Her prospective and retrospective validation29,30,31,32  of a genome-wide pattern of DNA copy-number alterations in brain33,34,35,36  tumors proved that the models discover predictors of survival and response to treatment that are (v) the most accurate and precise, (vi) clinically actionable in the general population based upon as few as 50–100 patients, and (vii) are consistent across studies and over time. She discovered this, and patterns in lung,37,38  nerve,39  ovarian,40,41,42,43,44,45  and uterine tumors, in public data. Such alterations were recognized in cancer, yet all other attempts to associate them with outcome failed, establishing that Alter's artificial intelligence and machine learning (AI/ML) is uniquely suited to personalized medicine.

  • 26th Annual Meeting of the Society for Neuro-Oncology (SNO) (Boston, MA, November 18–21, 2021).
  • Decade of the Physical Sciences in Oncology Network (PS-ON) at the National Cancer Institute (NCI) Virtual Symposium (September 21–23, 2020).