CS-5112: Design and Analysis of Algorithms, Cal State LA
CS-2148: Discrete Structures, Cal State LA
CS-4962: Software Design Lab II, Cal State LA
CS-4961: Software Design Lab I, Cal State LA
CS-3114: Data Structures and Algorithms, Virginia Tech
Graduate Teaching Assistant:
CS-5114: Theory of Algorithms, Virginia Tech
CS-4104: Data and Algorithm Analysis, Virginia Tech
CS-1218323: Design and Analysis of Algorithms, Tehran Polytechnic
Senior Design Projects
Pelvic Image Analysis and Geometry Reconstruction using Artificial Intelligence (Sponsored by Department of Mechanical Engineering at Cal State LA), 2021-2022
Medical imaging is a technique of producing images of the interior of the body non-invasively and plays an essential role in allowing medical professionals to provide accurate information about a patient’s anatomy, especially when dealing with tumors. The output image, i.e. MRI image, is then processed to be more useful to medical doctors using image segmentation and 3-D model construction. Although image segmentation has been through phases of improvement over the last decade, this procedure of segmenting images and creating 3-D models of specific organs can still be tedious and repetitive. For some situations, although very rare, segmentation can require hours for a single case.
The overarching goal of this research project is to streamline the process of converting MRI images of pelvic organs into 3-D model objects. The project was separated into two learning stages: understanding basic 3-D model construction and the creation of an AI model. The goal for the Fall 2021 semester was to learn the basics of 3-D modeling using 3DSlicer, 3-D visualization software, and experimenting with Nvidia AIAA, an API (application programming interface) that allows users to conveniently create 3-D model objects using trained data to automate it. With the results obtained in the previous semester, the Spring 2022 semester focused on creating our own AI model trained using our own data– which are MRI images of pelvic organs.
Open-Source Real-Time Video Player (Sponsored by AT&T), 2020-2021
The team worked with the AT&T liaisons to create a Network PIS Video Emulator on top of the open-source Github Hls.js video player. Hls.js is a web application that streams videos while providing a lot of useful real-time metrics and graphs about the video streaming playback. In order to further improve the features provided by HLS.js, the team was given the task to implement a network throttling feature to throttle our bandwidth to any desired network conditions such as 3G, 4G, 4G LTE, Slow Wifi, Fast Wifi, etc. They also added more metrics and graphs to display the video start time, rebuffering ratio, average bitrate, and bandwidth conditions. Lastly, the users were provided with an excel sheet containing all the information about the video playback for research purposes.
Online Application for Street and Highway Pavements Design (Sponsored by Department of Civil Engineering at Cal State LA), 2020-2021
The team was responsible for the design and development of a Web Application called City Pave that deals with doing calculations for pavement design/structures. This program is able to calculate and store information on a server and be able to be accessed remotely through the internet. This program is also intuitive and easy to use for all types of users. This is established by how the program validates the information that the users have inputted/selected allowing the program to do all the calculations while the users wait for the calculations.