faculty
Mazdak Tootkaboni, PhD
Associate Professor
Civil & Environmental Engineering
Contact
508-999-8465
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Education
2009 | Johns Hopkins University, Baltimore, MD | PhD in Structural Mechanics |
2002 | Tehran University, Iran | MSc in Civil Engineering |
2000 | Tehran University, Iran | BSc in Civil Engineering |
Teaching
Programs
Programs
- Civil & Environmental Engineering MS
- Civil Engineering BS, BS/MS
- Engineering and Applied Science PhD
- Environmental Resources Engineering
Teaching
Courses
Analysis of forces, moments, and deformations of determinate and indeterminate beams, fames, trusses, and other structural systems. Classical and computer methods used. (Formerly offered as CEN 321.)
The ideas and methods to quantify the reliability of structural systems through calculating their probability of failure. The concepts of uncertainty in the loads and the strength of structural members are introduced and simulation is used to propagate these uncertainties to quantities of interest that define failure.
General topics of interest and relevance to civil & environmental engineering applications. Topics may include subject matter related to transportation engineering, geotechnical engineering, structures design, water resources, fluid mechanics, and/or environmental science and engineering. Laboratory and field exercises may supplement lecture material. Course can be repeated with change of content.
Research
Research awards
- $ 79,964 awarded by Michelin North America, Inc | Massachusetts Institute of Technology for Near-Miss Traffic Vehicle Statistics from Crowdsourced Data Analytics: Phase I. Graph Representation of Telematics Data and Modeling
- $ 61,852 awarded by US Department of Transportation | Morgan State University for CMV Safety Countermeasures using Telematics and Driving Simulator Data
- $ 477,181 awarded by Office of Naval Research for UMassD MUST III: Multi-Fidelity Information Fusion for Accelerated Predictive Modeling and Optimal Design of High Entropy Alloys
- $ 387,696 awarded by Office of Naval Research for UMassD MUST II: A Unifying Framework for AM Process-Informed Design of High-Contrast Multi-Material Systems for Eigenvalue-Driven Physics
- $ 370,177 awarded by Office of Naval Research for UMassD MUST II: Enhanced Source Localization Using Optimally Designed Metamaterials and Advanced Machine Learning for Underwater Applications
Research
Research interests
- Stochastic computational mechanics and uncertainty quantification
- Construction of consistent data-driven stochastic models
- Stochastic multi-scale modeling of heterogeneous materials
- Design topology optimization under uncertainty
- Stochastic non-linear analysis of thin-walled structures
Select publications
- A. Asadpoure, M. Tootkaboni, and J.K. Guest (2010).
Robust topology optimization of structures with uncertainties in stiffness - application to truss structures
Computers and Structures - M. Tootkaboni, L. Graham-Brady (2010).
A multi-scale spectral stochastic method for homogenization of multi-phase periodic composites with random material properties
International Journal for Numerical Methods in Engineering, 83, 59-90. - M. Tootkaboni, L. Graham-Brady (2010).
Stochastic direct integration schemes for dynamic systems subjected to random excitations
Probabilistic Engineering Mechanics, 25, 163-171.
Mazdak P. Tootkaboni earned his high school diploma in mathematics and physics in June 1995. He then attended University of Tehran in Iran where he was awarded BSc in Civil Engineering and MSc in Earthquake engineering in April 2000 and December 2002 respectively. He joined the Department of Civil Engineering at the Johns Hopkins University in 2004 and earned his PhD degree in Structural Mechanics in May 2009.
Dr Tootkaboni’s research lies at the intersection of computational mechanics and applied probability and statistics. He develops schemes that combine recent advances in stochastic modeling (e.g. stochastic PDE solving techniques) and applied statistics (e.g. machine learning and statistical inference) with the existing methods in computational mechanics. These schemes have a wide range of applications, from uncertainty modeling (representation and propagation) to model validation and from reliability analysis to integration of experiments and computational models, and fault tolerant (uncertainty informed) design topology optimization. He is an associate member of ASCE and a member of Engineering Mechanics Institute (EMI) and its Probabilistic Mechanics Committee.