Mohamad H. Kazma Mohamad H. Kazma

About Me

I’m Mohamad Kazma, a recent PhD graduate in Civil Engineering from Vanderbilt University. I received my B.E. degree in Civil and Environmental Engineering from Notre Dame University-Louaize, Lebanon, in 2019, and my M.Sc. degree in Civil Engineering from Vanderbilt University in 2024. My research develops scalable, control-theoretic frameworks for monitoring and informing decisions about built and natural infrastructure networks under partial sensing, uncertainty, and physical constraints.

I completed my PhD under the supervision of Dr. Ahmad F. Taha in the Department of Civil and Environmental Engineering at Vanderbilt University. My dissertation, Advances in Observability for Nonlinear Networks: Theory and Application, addresses sensor allocation, observability quantification, stability analysis, network partitioning, and probabilistic node selection for nonlinear and differential-algebraic systems, with validations on power grids, water distribution networks, and combustion reaction networks. A detailed overview of my research themes and applications is available on the Research page.

Current Position

Vanderbilt University, Graduate Research Assistant in Civil Engineering (Defense passed May 12, 2026)

Advisor: Dr. Ahmad F. Taha (Dept. of Civil and Environmental Engineering)

Committee: Dr. Ahmad F. Taha (Chair), Dr. Thomas Beckers, Dr. Sankaran Mahadevan, Dr. Daniel Work

Dissertation: Advances in Observability for Nonlinear Networks: Theory and Application

Education

Vanderbilt University
PhD, Civil Engineering — Jan. 2022 – Aug. 2026
MSc, Civil Engineering — Jan. 2022 – Dec. 2024

Notre Dame University-Louaize
BEng, Civil and Environmental Engineering — Jan. 2015 – May 2019

Contact

JH261, 2301 Vanderbilt Place
Nashville, TN

mhkazma.github.io

Research Interests

My research is at the intersection of control and dynamical systems theory, combinatorial and submodular optimization, with applications to large-scale built and natural infrastructure networks. Topics of interest include: (i) observability, controllability, and safety (control barrier functions) for nonlinear and differential-algebraic systems (representing most real-world systems); (ii) sensor and actuator allocation in networked systems; (iii) uncertainty quantification and propagation in large-scale infrastructure networks; (iv) submodular and combinatorial optimization for monitoring and control; (v) scalable network partitioning and clustering; and (vi) probabilistic node selection.

Infrastructure application areas include power grids (transmission and renewable-integrated networks), drinking water distribution networks (quality and hydraulic dynamics), coupled hydrologic and hydrodynamic systems (overland flow and infiltration in watersheds), and energy balance models for climate.

Teaching

Vanderbilt University

  • CE 3300: Risk, Reliability, and Resilience Engineering (SP2025)
    Instructor: Dr. Hiba Baroud — Taught 6 of 12 modules on probability and statistical inference using R.

  • CE 6380-01: Applied Machine Learning (SP2024)
    Instructor: Dr. Sankaran Mahadevan — Covered modern ML methods with Python for science and engineering.

Notre Dame University-Louaize

  • Drilling & Production Engineering Lab, PEN 472 (FA2021)
  • Environmental Engineering Lab, CEN 365 (SP2020 – SP2021)

Awards & Certifications

  • Certified Associate in Project Management (CAPM®), Expired July 2024
  • Selected for the 2020 IP Valorization Grants Program at Berytech — Innovation Voucher ($25,000)
  • Co-recipient, ELCIM–IRI Center of Innovation and Technology Innovation Voucher ($6,000) for project “Concrete Masonry Units Enhanced with Phase Changing Materials”
  • 2nd place team, ASCE 2019 Popsicle Bridge Competition (Lebanon)

Invited Talks

  • Scalable Control Engineering for Built and Natural Infrastructure Networks — KTH Royal Institute of Technology, Division of Decision and Control Systems, Harry Nyquist Room, Stockholm, Sweden. June 8, 2026. [Slides]

Technical Skills

Programming: Python, MATLAB, R, Julia, LaTeX

Optimization: CVX, Gurobi, CPLEX, YALMIP, SeDuMi

Software: EPANET, PowerWorld, GAMS, GitHub, Power BI, Tableau, ANSYS, Abaqus, SAP2000, AutoCAD, Civil 3D, TRNSYS-18, Primavera P6, MATPOWER, Cantera, QGIS

Machine Learning: TensorFlow, PyTorch, Scikit-learn

Decision Analysis: Palisade Suite (Evolver, @Risk)

Languages: Arabic (Native/Fluent), English (Fluent)

Curriculum Vitae

My CV is available here.