Tammam Bakeer Dr.-Ing. habil.

Dr.-Ing. habil. · Dresden, Germany

Tammam Bakeer

Computational structural mechanics, reliability and inverse problems

I develop methods for assessing existing structures under uncertainty.

My work asks when what we already know is enough.

Explore research Selected publications
The assessment cycle: a structure is idealised into a physical model, discretised, calibrated against measurements, used to predict, and evaluated into an engineering decision that acts back on the structureidealisationdiscretisationcalibrationpredictionevaluationinterventionmeasurementsphysicalstructurephysicalmodelnumericalmodelidentificationand uncertaintypredictivesimulationengineeringdecision

From structure to decision

  1. Physical structureIdealisation
  2. Physical modelDiscretisation
  3. Numerical modelCalibration with measurements
  4. Identification & uncertaintyPrediction
  5. Predictive simulationEvaluation
  6. Engineering decisionIntervention feeds back to the structure
From a physical structure to a model, from measurements to a prediction, and from evidence to an engineering decision.
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Selected research contributions

Bayesian inverse problems

What can measurements tell us?

Examining sensor informativeness, identifiability and the uncertainty that remains when structural properties are inferred from measurements.

2026 · Mechanical Systems and Signal Processing 257, 114606

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Structural reliability

How do partial safety factors apply to nonlinear systems?

Extending the partial safety factor format to nonlinear structural systems using a notion of homogeneity.

2023 · Reliability Engineering & System Safety 234, 109150

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Computational mechanics

How can we assess structural stability?

Assessing the buckling stability of masonry walls with the transfer-matrix method.

2016 · Engineering Structures 110, 1–20

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When is the evidence enough?

A prediction can be uncertain while the decision is already clear.

Measurements help us estimate a structure’s condition. An assessment asks a further question: does the available evidence support accepting the structure, or is intervention needed?

My current research examines when the futures consistent with the observations support the same decision, and when the remaining uncertainty could change it.

Explore current research
Measured condition of a structure up to today, a fan of possible futures consistent with that data, and an intervention threshold: for a long span every future says the same thing, and only later do they disagreedecision settleddecision openmeasuredtodayintervention thresholdevery future the datastill allowsconditionyears in servicefutures that cross: intervention needed Uncertain predictions can still support a clear decision Measured condition up to today, followed by possible futures. Initially all futures stay above the intervention threshold. Later they disagree. This is a conceptual illustration, not measured research data. MeasuredPossible futures Intervention threshold TodayTime →
Possible futures consistent with the same observations initially support the same decision. Later they cross the intervention threshold at different times. Conceptual illustration.
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Research and engineering practice

Portrait of Tammam Bakeer
Tammam Bakeer, Dresden

From the mechanics of a structure to the decisions made about it, in research and in engineering practice.

This brings together nonlinear analysis, numerical modelling, structural reliability, monitoring and data-driven methods, applied to bridges, buildings, heritage structures and other infrastructure.

Beyond engineering, my interests include physics, mathematics, the history of scientific ideas and portrait drawing.

Career and background →Research profile →
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Recent work

2026

Conference paper — Information-guided Bayesian modelling for structural health monitoring, with Max Herbers and Steffen Marx, presented at SMAR 2026 in Dresden, in the session on intelligent digital methods for extending the service life of structures beyond 100 years, and published in Procedia Structural Integrity. DOI

2026

Journal article — Sensor informativeness, identifiability and uncertainty in Bayesian inverse problems for structural health monitoring, in Mechanical Systems and Signal Processing. DOI

2026

New preprint — Local information operators for spatial identifiability in distributed-parameter inverse problems in computational mechanics. arXiv
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Research and collaboration

I am building a research programme on information sufficiency for structural decisions: what measurements must establish before a structure can be accepted, and when the available evidence already settles the decision.

I welcome collaboration on structural health monitoring and digital twins, Bayesian inverse problems and structural reliability, numerical methods and high-performance computing, and AI and scientific machine learning for structural engineering.

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