APS Fellowship Information
APS Fellows Nominated by DBIO
University of Chicago
Citation: For her novel and inventive experimental contributions to understanding the mechanical properties of living cells from the molecular to cellular levels.
Georgia Institute of Technology
Citation: For contributions to biological physics and nonlinear dynamics at the interface of biomechanics, robotics, and granular physics.
Bowling Green State University
Citation: For his significant contributions to the quantitative understanding of protein dynamics, in particular, in enzymatic reactions by developing novel single-molecule spectroscopy and methodology.
Massachusetts Institute of Technology
Citation: For elucidating principles of protein-DNA search, and for applying concepts and methods of polymer physics to characterize the three dimensional organization of genome within a cell.
University of California, Irvine
Citation: For groundbreaking work on the application of mathematical and computational methods to important problems in systems biology.
Nanyang Tech University
Citation: For his significant contributions in understanding non-canonical nucleic acid motifs, particularly the i-motif and the G-quadruplex by developing novel NMR techniques.
The Salk Institute
Citation: For pioneering work in computational biological physics towards understanding the structure and function of correlations in large scale biological systems, including representation of memories in the brain, protein sequences, and statistical learning algorithms.
Citation: For applications of statistical physics to problems concerning learning, adaptation, and information coding in neural systems.
University of Pennsylvania
Citation: For creative development and application of high resolution NMR methods to examine the role of dynamics and statistical thermodynamics in the function of proteins including use of NMR relaxation to evaluate conformational entropy, high pressure NMR, and the reverse micelle encapsulation strategy.
Citation: For pioneering work in computational biology, including the applications of machine learning, statistical inference, and information theory for the investigation of biological networks.
Max Planck Institute
Citation: For his profound and innovative use of the methods of theoretical physics to address fundamental questions in neuroscience ranging from the biophysics of action potential initiation to the collective dynamics of neuronal circuits and to the self-organization of large-scale circuit architecture.