Welcome to the personal webpage of Dr. Mahdi Shadabfar.
This website serves as a platform for you to stay informed about his latest research and professional endeavors.
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| Latest Presentations |
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| 1. Random fields in MATLAB |
| 2. Object-oriented programming in 8 minutes |
| 3. Probabilistic analysis of ground vibrations |
| 4.Covid 19 prediction using probabilistic models |
| 5.Covid 19 prediction using probabilistic models |
| 6. |
| Latest Conference Papers |
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| 1. AI-based back analysis of multiphysics processes ... |
| 2. Reliability analysis of slope stability ... |
| 3. A hybrid Monte Carlo-Simulated Annealing ... |
| 4. Effects of height and span of structures ... |
| 5. A simplified method for the seismic analysis ... |
| 6. Effects of crossing angle on the behavior of ... |
| Latest Journal Papers |
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| 1. Probabilistic Machine Learning for Predicting ... |
| 2. Probabilistic estimation of thermal crack ... |
| 3. Randomized Fractional SEIR-VQHP Model ... |
| 4. Time-Variant System Reliability Analysis ... |
| 5. Spatial uncertainty quantification of ... |
| 6. A combined review of vibration control strategies ... |
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Online Courses
Dr. Mahdi Shadabfar has prepared the following courses, which will be presented as online classes. If you are interested in enrolling in any of these courses, please click on “More Information” below to view the course details and preregistration link.
Time Series Prediction using Deep Learning
MLP Neural Networks, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Gated Recurrent Units (GRUs), Long Short-Term Memory (LSTM) Networks
Monte Carlo Sampling Method
Monte Carlo Sampling, Latin Hypercube Sampling, Importance Sampling, Surrogate Modeling, Reliability-based Design, Time-variant System Reliability Analysis
Geostatistics
Data Preprocessing, Distance Matrix and Lag Distance, Cloud Variogram, Variogram Estimators, Kriging Interpolation, Variance Contour and a Measure of Error
Physics-Informed Neural Networks (PINN)
Neural Networks as Solvers of PDEs, Numerical Solution of PDEs, ِDerivatives of ANN, Types of Cost Functions, PINN in Pytorch, Deep XDE Library
With the increasing utilization of artificial intelligence, specifically artificial neural networks (ANNs), it has become more crucial than ever to acquaint students and professors with these methods. To address this need, we have meticulously crafted an exceptional educational resource in the form of a training video. In this resource, Dr. Mahdi Shadabfar delivers an introduction to ANNs in less than an hour, guiding you through the step-by-step implementation using the MATLAB programming environment. Whether you are a novice or already well-versed in ANNs, regardless of your field of study or research interests, we wholeheartedly recommend taking advantage of this invaluable educational resource. Simply fill out the form below, and the access link to this resource will be provided to you.
A Gift
I am writing this message as a permanent post, to ensure that each time we access this page, it remains visible. Certain things must be reiterated from time to time. Please always bear in mind that you are a gifted individual, irrespective of your social status, educational or professional background, or the challenges and hurdles you may face. God has bestowed upon you numerous talents that you can nurture and utilize. The entire universe exists for your growth and refinement. Maintain your trust in God and never give up.
Last Word
سبد خرید