R D Power Generation

Mehrzad Tartibi, Ph.D.

Founder of Delbeat Inc.

**** ****** **. #***, ********, CA 94704

**@*******.*** · 407-***-****

Summary: Expert in cardiovascular biomechanics with 10+ years of hands-on experience in computational and validation testing. Specialized in developing computational methods, modeling passive and active nonlinear soft tissues, unsteady fluid-solid interactions, particularly forward and inverse finite element analysis. Experienced in MRI, CT, and Ultrasounds. Skilled in MatLab, most commercial finite element (FE) and computational fluid mechanics (CFD) software packages. Able to collaborate effectively with cross-functional teams and communicate technical information to non- technical stakeholders. Seeking a biomechanical research and development position in a technology- driven organization where I can use my abilities to lead and drive product innovation, validation, and FDA approval.

Skills: Continuum mechanics, nonlinear finite element (FE), soft-tissue cardiovascular modeling, hemodynamics, fluid-solid interaction, modeling & measurements. Cardiovascular imaging, MRI, CT, and ultrasounds; soft tissue phantom design, construction, and imaging. Cell culture, passage, staining, and single-cell testing. Linear and nonlinear vibration FE modeling, testing design, measurements, high Cycle Fatigue, design of experiments, wear, and surface mechanics. Experienced with Matlab, Abaqus, Comsol, Fluent, Patran, Nastran, Ansys, LS-Dyna, Python. Delbeat Inc. Berkeley, CA

Founder and CEO Jan 2019 now

• Developed a software package that uses cardiac MRI images and builds patient-specific heart models to estimate and predict the state of the heart's ventricles.

• FDA product filing is in progress. The product assesses heart failure with local mechanical and electrical myocardium properties and cardiac chamber pressure (patent pending).

• In collaboration with UCSF and a Cleveland Clinic researcher, I led and participated in a cross-functional team that studied the effect of a gel injection in a swine-failing heart model. We used clinical catheters to measure 48 heart ventricle pressure. We also acquired cardiac MRIs of the subjects before and after the mitigating gel injections. Moreover, I modeled the swine heart failure model studies and submitted our findings in our first manuscript.

• Consulted companies and researchers with methods to assess their heart failure and lung FE modeling. UCSF and SF VA Hospital Berkeley, CA

Postdoctoral fellow Jan 2015 - Dec 2018

• Winner of NIH Small Business Innovation Research (SBIR) grant on the optimal application of MitraClip, a device to control the size of mitral valve opening.

• Developed and published a new physics-based method that coupled mechanical forces with tissue growth.

• Developed an inverse FEA-based Navier-Stokes method to measure the pressure drop in blood vessels using MRI 4D-flow (providing an entire velocity field).

• Developed a software tool to process MRI-based displacement measurement (DENSE MR sequence, an image- based displacement measurement technique) and computed myocardial transmural strains in healthy and infarcted tissues of animal subjects.

• Led a cross-functional team of MRI experts, graduate students at UC Berkeley, and MRI scanner company experts to validate my FEA-Based Navier-Stokes method and test a Siemens-developed Lattice Boltzmann CFD method.

• Designed, built, and conducted MRI studies of a heart-size phantom to validate our DENSE measurement.

• Developed a numerical technique for calculating the unloaded configuration of arteries and applied it to abdominal aortic aneurysms (AAA) patients.

• Conducted a Fluid-Solid interaction model of blood flow and vessels using COMSOL. UC Berkeley Berkeley, CA

PhD Student Jan 2008 - Dec 2014

• PhD Dissertation: Material Identification and residual stress measurement of solid bodies - a none-destructive approach (developed in-house FEA 3D code using MatLab and its parallel computational capabilities)

• Measured a single-cell cytoskeleton mechanical material properties by designing and implementing a hybrid AFM cell- compression and confocal microscopy experiment and FEA computational model. Trained in handling live cells, including culturing, passaging, staining, imaging, and single-cell patterning. Mehrzad Tartibi, Ph.D.

Founder of Delbeat Inc.

2038 Parker St. #116, Berkeley, CA 94704

**@*******.*** · 407-***-****

• Developed, implemented, and validated a fretting wear program capable of predicting the wear volume and wear depth of bodies in contact using Python and Abaqus implicit and explicit solvers.

• Let a team of lab mates validate the methodology using a wear-accelerating test rig and many specimens with multiple material pairs.

• Trained other lab-mates on FEA commercial codes, such as PATRAN and ABAQUS, to conduct implicit and explicit analysis on linear and nonlinear problems (contact problem, natural frequency eigenvalue problems, and forced- harmonic response calculation)

• As GSI (graduate student instructor) and head GSI of Continuum Mechanics (ME185 in Fall 2010); Mechanical Behavior of Materials (ME108, four semesters), which required leading the material lab testing; Statics (ME85, one semester); Physics (8A, three semesters) – recognized as one of the outstanding GSI of ME department in 2010. Siemens Power Generation Orlando, FL

Principal Engineer, & Dynamic Core Competency Owner (CCO) Feb 1997- Dec 2007

• As Dynamic Core Competency Owner (CCO), in charge of introducing and developing innovative technologies in the field of vibration and contact dynamics – owned four projects: Vibration Wear measurement and prediction, Blade Mistuning prediction tool development, Flutter prediction tool, and Component-Damping measurement, calculation, and validation.

• Led several design, instrumentation, and validation teams as a senior and principal engineer:

• Designed, analyzed, and validated the high cycle fatigue life and 3d unsteady aeroelasticity of different components of gas turbines (airfoils, leaf springs, combustion rings, etc.).

• Designed, installed, and supervised the instrumentation, installation, and validation phase in the Berlin Test Bed

(BTB) at Siemens facility, testing the new gas turbine engines.

• Developed a wear prediction tool for general forms of contact conditions.

• Validated the results in BTB by using dynamic strain gauges and accelerometers.

• Mentored entry-level and mid-level engineers to complete research projects. Education:

• University of California Berkeley

PhD in Mechanical Engineering Department (Continuum Mechanics, Numerical Computational, Emphasis and Bioengineering), May 2015

• University of Central Florida, Orlando, Florida

M.Sc. Mechanical Engineering (Mechanical systems and vibration), August 2000

• Abadan Institute of Technology (A.I.T.), Abadan, Iran B.Sc. Mechanical Engineering (Fluid and Heat transfer), August 1989 Publications:

• Google Scholar: https://scholar.google.com/citations?hl=en&user=BS5_RNkAAAAJ

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