faculty

Mazdak Tootkaboni, PhD

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

Teaching

Courses

CEN 202: Mechanics of Materials

The behavior of materials and members under axial load, torsion, flexure, shear and combined loads, including the deflection of beams and buckling of columns. The relationship between stress and strain, principal stresses and strains and yield and fracture criteria are discussed. Previously offered as CEN 303.

CEN 306: Structural Analysis

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.)

CEN 425: Structural Mechanics

Study of techniques used to analyze structural indeterminate systems. Energy methods used to determine stresses and deformations in structural members. Approximate and numerical methods used for structural analysis. Introduction to plastic structural analysis. Composite structures. Introduction to the analysis of plates and shells.

CEN 449: Reliability Analysis

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.

CEN 525: Structural Mechanics

CEN 549: Reliability Analysis

CEN 590: Master's Thesis

Thesis research on an experimental or theoretical project in civil and environmental engineering under a faculty advisor. A formal thesis must be submitted to fulfill the course requirements.

CEN 590: Master's Thesis

Thesis research on an experimental or theoretical project in civil and environmental engineering under a faculty advisor. A formal thesis must be submitted to fulfill the course requirements.

EAS 600: Dissertation Proposal Prep

Doctoral thesis proposal development based on technical writing process, data interpretation, experimental design. Students who successfully complete the course will be able to assess information from the primary scientific literature, formulate scientific questions (hypotheses), and generate an experimental plan to help validate or nullify their hypothesis. Students will demonstrate a command of oral and written communication skills by completing this course.

EAS 601: Pre-Dissertation Research

Research investigations of a fundamental and/or applied nature defining a topic area and preliminary results for the dissertation proposal undertaken before the student has qualified for EAS 701. With approval of the student's graduate committee, up to 15 credits of EAS 601 may be applied to the 30 credit requirement for dissertation research.

Research

Research awards

$ 216,051 awarded by ONR / UNIVERSITY OF CALIFORNIA IRVINE for Optimal Design and Additive Manufacturing of Functionality Graded Shell-Based PH Steel Metamaterials
$ 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
$ 150,066 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

Research

Research interests

Data-centric, uncertainty-informed, and AI-enabled analysis and design
Physics-informed machine learning
Topology optimization for design of structures and architected materials
Multi-fidelity information fusion and information theoretic design of experiments
Stochastic computational mechanics

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

Dr Tootkaboni received his PhD in engineering mechanics from the Department of Civil and Systems Engineering at the Johns Hopkins University. Since 2010, He has been on the faculty of the Department of Civil and Environmental Engineering at University of Massachusetts Dartmouth (UMassD) with joint appointments in Center for Scientific Computing and Data Science Research and the Department of Mechanical Engineering.

Dr Tootkaboni’s research is cross-disciplinary and focuses on drawing upon advances in data analytics, machine learning, and optimization to develop techniques that help engineering mechanics community move towards resource-efficient, uncertainty-informed and climate-conscious solutions. He is a recipient of the NSF early CAREER award, the University of Massachusetts System President’s Science and Technology award, and the UMassD Chancellor’s Sponsored Research Recognition award, and serves on the editorial board of the ASCE Journal of Engineering Mechanics. He is also an active member of Engineering Mechanics Institute (EMI) and its Probabilistic Methods Committee and have consistently led technical sessions and minisymposia on a diverse array of topics such as resilience analytics, topology optimization and architected materials.

Dr Tootkaboni’s research has been funded by, NSF, ONR, USDOT, and Michellen North America as well UMass President’s office and has appeared on New York Times, and MIT news among others.