Bio

Affiliation: Assistant Professor (Teaching) in the Department of Computer Science, part of the School of Computing at George Mason University. Previously a Postdoctoral Fellow at the School of Interactive Computing part of the College of Computing at Georgia Tech.
Research: Multiagent Systems, Machine Learning.
CV: cv (05-SEP-2024)

Teaching

Current

Fall 2024
CS 211 - Object Oriented Programming (link on department page)
CS 480 - Introduction to Artificial Intelligence

Previous

Spring 2024
CS 211 - Object Oriented Programming (link on department page)
CS 391 - Advanced Programming Lab
CS 480 - Introduction to Artificial Intelligence

Fall 2023
CS 211 - Object Oriented Programming (link on department page)
CS 480 - Introduction to Artificial Intelligence

Spring 2023
CS 504 - Principles of Data Management and Mining
CS 580 - Introduction to Artificial Intelligence

Fall 2022
CS 211 - Object Oriented Programming
CS 580 - Introduction to Artificial Intelligence

Spring 2022
CS 112 - Introduction to Computer Programming
CS 580 - Introduction to Artificial Intelligence

Fall 2021
CS 211 - Object Oriented Programming
CS 480 - Introduction to Artificial Intelligence

Spring 2021
CS 504 - Principles of Data Management and Mining
CS 112 - Introduction to Computer Programming

Fall 2020
CS 504 - Principles of Data Management and Mining
CS 211 - Object Oriented Programming

Spring 2020
CS 4641 - Machine Learning
CS 3600 - Introduction to Artificial Intelligence

Fall 2019
CS 4641 - Machine Learning
CS 3600 - Introduction to Artificial Intelligence

Spring 2019
CS 4641 - Machine Learning
CS 3600 - Introduction to Artificial Intelligence

Exam Clock

Dead Simple ANN

A simple implementation of the Perceptron and a Feed-Forward Two-Layer ANN. A tarball of the whole thing is here. If you just need the source code, the header file is ann.h, the implementation is ann.c, and here is an example of how to use it. You need some data for it to run, which has this nice vizualization.

Dead Simple PSO

A simple implementation of the Particle Swarm Optimization algorithm, as described in this book: Essentials of Metaheuristics. A tarball of the three files is here, the well documented header file is pso.h, the implementation is pso.c, and here is an example of how to use it. Real test problems and data with visualizations to follow.

Some Slides

on RNNs
on using PSO for motion planning

Misc.

tkinter_tester.py
xmms2-scrobbler-py