Resume

• 2006

  M.S.E.

  Mechanical Engineering

  The Johns Hopkins University

  Ph.D.

  Mechanical Engineering

  The Johns Hopkins University

• 2001

  B.S.

  Mechanical Engineering (Minor: Bioengineering)

  University of Pittsburgh

• Physics

  MEMS

  Biomedical Engineering

  C++

  SolidWorks

  Finite Element Analysis

  Experimentation

  Research

  Microsoft Office

  Data Analysis

  Optical Microscopy

  Simulations

  Matlab

  Mathematical Modeling

  Engineering

  Materials Science

  Valve-Based Microfluidic Compression Platform: Single Axon Injury and Regrowth

  Arun Venkatesan

  K. T. Ramesh

  In Hong Yang

  Adam Fournier

  We describe a novel valve-based microfluidic axon injury micro-compression (AIM) platform that enables focal and graded compression of micron-scale segments of single central nervous system (CNS) axons. The device utilizes independently controlled “push-down” injury pads that descend upon pressure application and contact underlying axonal processes. Regulated compressed gas is input into the AIM system and pressure levels are modulated to specify the level of injury. Finite element modeling (FEM) is used to quantitatively characterize device performance and parameterize the extent of axonal injury by estimating the forces applied between the injury pad and glass substrate. In doing so

  injuries are normalized across experiments to overcome small variations in device geometry. The AIM platform permits

  for the first time

  observation of axon deformation prior to

  during

  and immediately after focal mechanical injury. Single axons acutely compressed (5 s) under varying compressive loads (0–250 kPa) were observed through phase time-lapse microscopy for up to 12 h post injury. Under mild injury conditions (< 55 kPa) 73% of axons continued to grow

  while at moderate (55–95 kPa) levels of injury

  the number of growing axons dramatically reduced to 8%. At severe levels of injury (> 95 kPa)

  virtually all axons were instantaneously transected and nearly half (46%) of these axons were able to regrow within the imaging period in the absence of exogenous stimulating factors.

  Valve-Based Microfluidic Compression Platform: Single Axon Injury and Regrowth

  A Multiscale Computational Approach to Estimating Axonal Damage under Inertial Loading of the Head

  Rika

  Carlsen

  Nippon Steel Company

  Carnegie Mellon University

  Johns Hopkins University

  Sandia National Laboratories

  Robert Morris University

  Baltimore

  Maryland

  Research Assistant

  Johns Hopkins University

  Pittsburgh

  PA

  Post-doctoral Research Fellow

  Carnegie Mellon University

  Albuquerque

  New Mexico

  Research Internship

  Sandia National Laboratories

  Kitakyushu

  Japan

  Nippon Steel Company

  Assistant Professor of Mechanical and Biomedical Engineering

  Robert Morris University