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  • Degrees
    PhD, Physics, University of Maryland, College Park
    M.Sc., Physics, Indian Institute of Technology
  • Research Interests
    Machine learning methods for biosequence analysis, Mathematical modeling of biological networks

Alpan Raval is a senior research fellow at Claremont Graduate University’s Institute of Mathematical Sciences and a former professor of computational biology at Keck Graduate Institute.

Raval’s research focuses on modeling of protein families using machine-learning methods—specifically hidden Markov models, support vector machines, and their variants. Raval also explores mathematical modeling of protein structures using geometrical invariants, as well as the statistical aspects of sequence alignment.

With Keck Graduate Institute Professor Animesh Ray, Raval is the co-author of Introduction to Biological Networks, part of Chapman & Hall’s Mathematical and Computational Biology Series. The book offers a conceptual overview of biological interaction networks as a unifying theme in genomics-inspired biology and explains the biological significance of interaction networks through numerous examples.

Before entering the life sciences, Raval was a successful researcher in physics, with a theoretical discovery of a semiclassical model to explain the accelerated expansion of the universe. He also researched particle-field interactions in quantum field theory, using ideas from non-equilibrium statistical physics. This work led to the elucidation of generalized fluctuation-dissipation relations in quantum field theory that are valid in the fully non-equilibrium case.

In addition to numerous publications and refereed journal work, Raval has given invited talks at the Fermilab’s Theoretical Cosmology Group, Purdue University, University of Maryland, and elsewhere. He was granted permanent U.S. residency in 2001 as an “Alien of Extraordinary Ability.”

Co-authored with Stefano Piana, Michael P. Eastwood, and David E. Shaw. “Assessment of the utility of contact-based restraints in accelerating the prediction of protein structure using molecular dynamics simulations,” Protein Science 25 no.1 (2015): 19–29.

Co-authored with Stefano Piana, Michael P. Eastwood, and David E. Shaw. “Refinement of Protein Structure Homology Models Via Long, All-Atom Molecular Dynamics Simulations.” Proteins Structure Function and Bioinformatics 80 no. 8 (2012): 2071–9.

Co-authored with Ravishankar Rao Vallabhajosyula. “Computational Modeling in Systems Biology.” Methods in Molecular Biology 662 (2010): 97–120.

Co-authored with Aaron J. Arvey, Rajeev K. Azad, and Jeffrey G. Lawrence. “Detection of genomic islands via segmental genome heterogeneity.” Nucleic Acids Research 37 no.16 (2009): 5255–66.


Bioinformatics & Biostatistics
Bayesian Methods & Machine Learning
Statistical Theory
Applied Stochastic Methods in Computational Biology
Advanced Computational Biology