Rayan Chatterjee, Phd Email & Phone Number

I am adept in mathematical modelling of complex systems and computer programming.I have an interdisciplinary training in engineering and physics. Presently I am a researcher at Stanford University, USA, working on computational biomechanics of hearing. My project is on hair bundles, the sound sensors crucial for our hearing. Hair bundles generate electrical signals when mechanically deflected by sound-induced forces, a process known as MechanoElectrical Transduction (MET). However, Most components of the hair-bundle have dimensions less than a micrometer, also they are vulnerable to the low calcium concentration of their bathing fluid. It is thus challenging to experimentally determine the mechanical properties of the components of the hair bundle, and its response to stimulus under the physiological calcium concentrations at the characteristic frequency. To predict these quantities, I've developed a mathematical model for the MET process by the hair bundle, well-calibrated with experimental data.In my PhD I have worked on active fluids, which denote mathematical models (coupled nonlinear partial differential equations) for the collective dynamics of self-propelled swimmers in a bulk fluid. Research in active fluids is useful in systems is useful in fields such as biomedicine, which often involve the collective motions in systems of self-propelled particles, e.g. nanorobots used for surgical purposes. My objective was to determine the role of inertia on the dynamics of active fluids. I developed and validated a parallel computational solver to simulate the dynamics of active fluids. I applied multiple statistical techniques to analyse the simulation data. My central results establish a novel hydrodynamic theory that explains the physical conditions under which swimmers in a bulk fluid can collectively move together as an ordered flock (e.g. fish schools). I am adept at solving complex research problems, fast learner and out-of-the-box thinker. Skills and expertise:(1) Mathematical modelling.(2) Numerical algorithms.(5) Scientific computing (serial and parallel).(6) Fortran (with MPI).(7) Mathematica.(8) MATLAB.(9) C++.(10) Applied Mathematics.(11) Applied Statistics.(12) Fluid-flow multiphysics.(13) Curve-fitting.(14) Reduced order modelling (Singular value decomposition and Dynamic mode decomposition) of fluid flows.(15) Biophysics of hearing.(16) Computational Fluid Dynamics (CFD).(17) Mathematical and Computational biology.