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👨🏻‍💻  About Me

I'm Fardin Abbasi, a senior EE student at the University of Tehran. I'm also studying Management as a minor program. I've had a very pleasing time during my undergraduate studies, and I am currently seeking more opportunities to grow and influence my community.

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Fardin Abbasi's Projects

ai-economist icon ai-economist

Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).

ball_and_beam_control_system icon ball_and_beam_control_system

Implementation and analysis of a Ball & Beam Control System, including system modeling, linearization, controllability, observability, and the design of controllers and observers, with a focus on stabilizing the system using PID controllers, state feedback, and estimators to handle nonlinearities, disturbances.

bayes_classifier icon bayes_classifier

Performing classification of penguin species using a Naive Bayes classifier, both implemented from scratch and with Scikit-Learn, including data preprocessing, training, and evaluation.

decision_tree icon decision_tree

Implementation of Decision Tree and Random Forest algorithms, with various hyperparameters, developed from scratch and using scikit-learn for comparison and analysis.

deep_rl icon deep_rl

Exploring deep reinforcement learning techniques, particularly focusing on the implementation and testing of algorithms like Deep Q-Learning (DQN) and Dueling DQN.

electromagnetic_levitation_control_system icon electromagnetic_levitation_control_system

Modeling and analyzing a magnetic levitation system, including the design and evaluation of PID and PI controllers to achieve stability and desired performance in both time and frequency domains.

expectation_maximization icon expectation_maximization

Implementing the Expectation-Maximization algorithm and applies Gaussian Mixture Models (GMM) to classify images.

image_processing icon image_processing

Implementation of a 2D correlation method for locating an electrical element (BA3240) on a PCB.

imagecompression-histogrammatching icon imagecompression-histogrammatching

Implementations and analyses of various mathematical and computational techniques, including Lagrange interpolation, LU decomposition, image compression with SVD and FFT, image denoising, histogram matching, and QR decomposition using Gram-Schmidt methods.

laplace_transform icon laplace_transform

Modeling and simulating electrical and mechanical systems using the Laplace transform in MATLAB and Simulink.

linear_programming icon linear_programming

Operational Research [ECE 145] - Fall 2023- University of Tehran - Dr. Ramezani Moghaddam

linear_regression icon linear_regression

Performing polynomial regression of varying degrees on data affected by white and Poisson noise, evaluating the model performance based on MSE loss and the bias-variance trade-off.

logistic_regression icon logistic_regression

Implementing logistic regression with L2 regularization from scratch to classify circular datasets by mapping the feature space into higher dimensions.

machine_learning icon machine_learning

Containing various ML projects, including image and text classification, clustering, regression, and neural networks. Projects include implementations of Random Forest, SVM, Decision Trees, EM algorithms, and advanced models like MLP and CNN, with datasets ranging from facial emotion detection to ECG signals and more.

ml_fake_image_detection icon ml_fake_image_detection

Detecting fake images using machine learning, involving feature extraction from real and AI-generated images, and implementing various classification models such as Random Forest, SVM, and Logistic Regression to accurately distinguish between real and fake images.

neural_networks icon neural_networks

Machine Learning Course [ECE 501] - Spring 2023 - University of Tehran - Dr. A. Dehaqani, Dr. Tavassolipour

parzenwindow icon parzenwindow

Performing non-parametric Parzen Window density estimation with a Gaussian kernel, implementing the method both from scratch and using built-in functions, and compares the results across various window widths and sample sizes.

pca icon pca

Applying Principal Component Analysis for image compression, exploring how varying numbers of principal components affect image quality and compression ratio.

randomprocess-quantization icon randomprocess-quantization

Analyzing random processes to determine stationarity using statistical methods and implements analog-to-digital conversion, quantization, and signal transmission with noise in MATLAB.

signal_processing icon signal_processing

Implementing a convolution function from scratch and analyzing an LTI system by adding noise and echo to an audio signal, with detailed plots and results provided.

stm32_basics icon stm32_basics

Implementations of basic components like timers, LCD displays, external interrupts, and digital pins on the STM32F103R6 microcontroller, demonstrating fundamental embedded system concepts.

svm icon svm

Implementation of Support Vector Machines on the Iris dataset, featuring both scratch and scikit-learn versions with various kernels.

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