Teaching
Vidya' teaching objectives emphasize a holistic, multi-disciplinary/interdisciplinary approach to water resources engineering. Dr. Samadi teaches courses related to engineering hydrology, advanced hydrology, computational methods in water resources, and GIS in Civil & Enviornmental Engineering. Some of her courses are listed below.
Fundamentals of Python programing; stochastic thinking and computational thinking; Random Walks; data mining and data fusion; data generation methods and gathering using APIs; time series analysis and forecast; classical hypothesis testing for making statistical decisions;deep neural network application in water resources modeling; and enviornmental system modeling and decision making, etc.1 unit Lecture and 2 units lab.
Review of basic probabilistic concepts; uncertain phenomena, total probability and Bayes' theorems; random events and random variables; probability distributions, expectation, variance, skewness, and kurtosis; statistical inference, parameter estimation and confidence intervals; classical hypothesis testing for making statistical decisions;stationary and nonstationary processes; and linear regression and model selection, etc.1 unit Lecture and 2 units lab.
Deterministic and stochastic processes in hydrology; probability Axioms; moments and expectations of distributions; introduction to frequency analysis, frequency analysis and probability; simple linear regression and multi-variate linear regression, evaluation of regression; hypothesis testing to compare methods of parameter estimation for frequency distributions in hydrology-application to infrastructure design; apply multivariate analysis in hydrologic systems; principles of time series modeling; autoregressive models (AR); Bayesian uncertainty estimation in hydrological modelling; Artificial Intelligence techniques such as Neural Networks, Fuzzy Logic; surrogate models and data mining; and IoT applications in water resources. 2 units Lecture and 1 unit lab.
Spatial analysis in hydrology and hydraulics;web-based mapping and information; create a base map of a study region including watersheds, streams,and aquifers by selecting features from regional maps; mathematical calculation on hydrologic/hydraulic geospatial maps using map algebra on raster grids; LIDAR data analysis and digital elevation model of land surface terrain to derive watersheds and stream networks; HEC-GeoHMS hydrologic modeling; assimilation of ground-based and NASA satellite data into forecasting system;hydraulic modeling using HEC-GeoRAS and velocity mapping in rivers and floodplains, etc.1 unit Lecture and 2 units lab.
Application of GIS and RS in hydrology; creating SCS Curve Number grid; watershed and stream network delineation; single-event and continues hydrologic simulation;Geospatial information for real-time operational hydrology; flood control strategies and water resources management.
GIS and engineering applications (utility system maintenance, hydrologic and hydraulics modeling, water supply, stormwater quality monitoring/control, solid waste management and hazardous waste management); GIS analysis functions and operations (feature proximity, map algebra, spatial joins, etc.); ArcGIS Spatial Analyst Extension; data collection and processing (Web services); ArcGIS Network Analyst Extension, network modeling and analysis, finding best routes, closest facility, service areas, dynamic segmentation and routing – applications to transportation engineering; ArcHydro Tools Extension; GIS data manipulation and analysis; Application of GIS for point and non - point pollution, etc.1 unit Lecture and 2 units lab.
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