Academic Projects

All
Compilers
Machine Learning
Web Application
Hardware Programming
Operating Systems

Toorla, Tiny Object Orinted Readable Language

Project Description

Toorla is an object-oriented Java-like programming language which supports inheritance. Each Toorla program with .trl foramt contains one or more classes that have some fields and methods. Toorla has been implemented in four phases using Java in IntelliJ IDEA.

It has been developed as a student project for Compiler Design and Programming Languages course.

Phase I, Lexer and Parser: Toorla's grammar was implemented using ANTLR and as well as a parser to create abstract syntax tree (AST) of input program.

Phase II, Name Analyzer: The name analyzer of the language was implemented to gather information about classes, fields, methods, local variables, and scopes of program and finding name analysis errors like undefined variables or redefinition.

Phase III, Type Analyzer: A type checker was implemented to check the types of variables in input program, finding relevant errors based on Toorla's documentation and setting initial value for various types.

Phase IV, Code Generation: The machine code was generated by converting Toorla's code to jasmin as a middle layer. Jasmin assembler converts its codes to class files which can be executed by JVM later.

Compilers & Code Generation

While Interpreter

An Interpreter for While Language

Project Description

While interpreter was implemented for this language with Java in IntelliJ IDEA. The interpreter accepts the abstract syntax tree(AST) of the code as its input and executes it using visitor pattern.

It has been developed as a student project for Compiler Design and Programming Languages course.

Machine Learning

Neural Network from Scratch

Project Description

The Neural Network is implemented with Python in Jupyter notebook from scratch with ReLU as its activation function.

All gradient relations has been calculated by hand; and various normalization techniques were used to gain more accurate result. The model can load weight values from .csv file or save them on a .csv file for later usage.

As well as this, I implemented a neural network with similar structure with Pytorch to evaluate my model's accuracy.

Machine Learning

Neural Network with Pytorch

Project Description

The Neural Network is implemented with Pytorch in Google Colab to analyze different variables and methods and their effects on neural networks' performance. These are consisted of learning rate, batch size, activation function, momentum, number of epoch, regularization, etc.

The implemented NN has to do image classification, learn features of a dataset consisted of pictures from 52 different types of accessories, and predict new pictures. It has been developed as a student project for Artificial Intelligence course.

Machine Learning

Application of SciKit-Learn

Machine Learning with SciKit-Learn Library

Project Description

Various machine-learning techniques is implemented with Scikit-learn library methods in Jupyter notebook to process a dataset of some markets' customers to predict whether they come back later to that market or not.

Various pre-processing techniques was applied to the dataset as well as using different classifiers such as decision tree, KNN, random forests, etc. It has been developed as a student project for Artificial Intelligence course.

Machine Learning

Bayesian Network

Text Processing using Bayesian Network

Project Description

A Bayesian Network was implemented from scratch to process dataset consisting of different text news to predict their category with Python in Jupyter notebook.

Practical techniques like bag of words were used to obtain more accurate result. It has been developed as a student project for Artificial Intelligence course.

Machine Learning

Genetic Algorithm

Replacement Decoding using Genetic Algorithm

Project Description

A Genetic Algorithm was implemented from scratch to decode an encoded text with replacement method and extract the original text.

The algorithm uses a given dictionary as its reference for acceptable words. Mutation and cross-over were implemented as fast and effective as possible, as well as the application of practical techniques like eliminating stop words to obtain more accurate result. It has been developed as a student project for Artificial Intelligence course.

Machine Learning

Price Estimation

Price Estimation with Regression

Project Description

A Regression Model was implemented to processing a dataset containing spoken text data about second-hand mobile devices and their prices to estimate new entries' price using different Python libraries such as Numpy, Pandas, and SciKit-Learn in Jupyter notebook.

As well as bag of words, various techniques were used to preprocess text messages. Pre-processing was the critical part of the projects, since text data was consisted of both English and spoken Persian words with spelling problems. It has been developed as a student project for Artificial Intelligence course.

Machine Learning

Search Problems

Informed and Uninformed Search Algorithm

Project Description

Various search algorithms were implemented from scratch to find best route for an agent in a givan play ground with obstacles using Python in Jupyter notebook.

Uninformed search algorithms like BFS and DFS as well as informed one like A* were implemented. I also compared their performance based on problem. It has been developed as a student project for Artificial Intelligence course.

Web Application

Loghme

Loghme, Online Food Delivery Web Application

Project Description

Loghme is a Persian online food delivery web application similar to waiter.com and other food delivery cooperations. It has been developed during 8 phases as a student project for Internet Engineering course.

Loghme's Back end : Implemented with Java in IntelliJ IDEA using various tools and technologies such as Maven, Apache Tomcat, Spring MVC, MySQL as database, etc. and deployed using Kubernetes and Docker.

Loghme's Front end : Implemented using HTML, CSS, JavaScript, React.js, Nginx (with Kubernetes and Docker for deployment), etc.

Web Application

Jeek Jeek

Jeek Jeek, Twitter-like Local Web Application

Project Description

Jeek Jeek is a Twitter-like local web application by which you can tweet, have your own profile, like other's tweets and leave comments for them.

It has been developed during 2 phases with C as its back-end programming language as a student project for Advanced Programming course.

CSS, HTML, and JS were used to design front-end pages as well.

Hardware Programming

Linear Classifier

Linear Classifier with Verilog

Project Description

A linear classifier was implemented by designing datapath and controller with Verilog as a hardware programming language in Modelsim. The classifier was tested with a dataset and a similar one was implemented using MATLAB to evaluate their performance.

It has been developed as a student project for Computer Architecture course.

Hardware Programming

MIPS Processor

Implementation of MIPS Processor with Various Architecture

Project Description

MIPS is a reduced instruction set computer instruction set architecture. A simplified version of MIPS was implemented with various architecture with Verilog in Modelsim.

It has been developed as a student project for Compiler Design and Programming Languages course.

Single-Cycle MIPS: A single-cycle MIPS architecture in a minimal system was implemented with an ALU supporting various operators.

Multi-Cycle MIPS: A multi-cycle MIPS architecture was implemented which works based on stack providing more operators.

Pipeline MIPS Architecture: A MIPS processor with pipeline architecture was implemented as well as determining and resolving possible hazards.

Hardware Programming

ARM Processor

Implementation of ARM Processor with Pipeline Architecture

Project Description

Pipeline ARM Architecture: An ARM instruction set with pipeline architecture was implemented in Computer Architecture Laboratoy with Verilog in Modelsim. It supports both forwarding and hazard units.

Operating Systems

XV6 Operating System

Working woth XV6

Project Description

XV6 is a teaching operating system which was edited and improved as a student project for Operating Systems course. Having implemented various features, I have been familiar with technical aspects of operating systems.

Introduction to Xv6 OS: I got familiar with Xv6, its execution, debugging, improving its console by adding some features, and implementing new program to copy text data from a file to another one.

XV6 System Calls: Several new system calls were implemented and added to the OS which enable XV6 to run commands out of the directory in which their execution file exists, sleep a process for an arbitrary period using Xv6's ticks, and obtain current process's pid and its children and grandchildren.

Process Scheduling: A multilevel feedback queue scheduler (MFQ) was implemented which includes lottery, HRRN, and SRPF methods as its scheduling levels in Xv6.

Process Synchronization Mechanisms: Two synchronization mechanisms were added to prevent out-of-order execution of processes, and use mutex more than once in recursive programs.

Operating Systems

Monitors

Solving a Simulated Problem using Monitors

Project Description

Monitors are exploited to achieve process synchronization in operating system. Having used its feature, I tried to solve a simulated traffic problem to minimize the air pollution caused by cars. This means that by receiving information about cars' pollution and a map of the city as well as using monitors, the program tries to find the best schedule for cars to move across the streets. The monitors are implemented from scratch.

It has been developed as a student project for Operating Systems course.

I am Shakiba Bolbolian Khah

About Me

My Education

Bachelor of Science in Computer Engineering

High School Diploma in Mathematics

My Experiences

Teaching Assistant at the University of Tehran

Software Intern at Mobile Communications Laboratory

Vice-chair at the University of Tehran's ACM Student Chapter

My Skills

Honors & Scores

Among 15 percent

Winner

Member

Ranked 305^th

IELTS

Academic Projects

I am Shakiba Bolbolian Khah

About Me

My Education

Bachelor of Science in Computer Engineering

High School Diploma in Mathematics

My Experiences

Teaching Assistant at the University of Tehran

Software Intern at Mobile Communications Laboratory

Vice-chair at the University of Tehran's ACM Student Chapter

My Skills

Honors & Scores

Among 15 percent

Winner

Member

Ranked 305th

IELTS

Academic Projects

Ranked 305^th