Dr. Roger S. Gaborski

Professor, Department of Computer Science                 Roger Gaborski
Director, Laboratory of Computational Studies
Rochester Institute of Technology
102 Lomb Memorial Drive
Rochester, New York  14623-5608

Email: rsg@cs.rit.edu
Office: GOL-3647
Lab: GOL-3400
Phone: 585-475-4931
Fax: 585-475-7100

Research interests:

Image Understanding

Biologically inspired machine learning

Evolutionary algorithms

Pattern recognition

Signal Analysis

Biological modeling

Cognitive-based image scene understanding

Entity resolution

Financial time series analysis and forecasting


STUDENT RESEARCH OPPORTUNITIES

 



Studying Aesthetics in Photographic Images and Artwork

It is a relatively easy task for a human to judge the aesthetic quality/value of an image we know if we like an image or not. The purpose of this project is to develop a computational algorithm that can make the same judgment with a rating between 1 and 10.

This project is suitable for an independent study (either undergraduate or graduate), MS project or thesis. Student funding is not available at this time, but funding may become available in the future.

 

Interested students should contact Dr. Roger S. Gaborski, Department of Computer Science, rsg@cs.rit.edu


Evolving Cellular Automata with Genetic Algorithms


The goal of this project is to evolve cellular automata (CA) rules to perform complex tasks using a genetic algorithm.

This project is suitable for an independent study (either undergraduate or graduate), MS project or thesis. Student funding is not available at this time, but funding may become available in the future.

 

Interested students should contact Dr. Roger S. Gaborski, Department of Computer Science, rsg@cs.rit.edu


Financial Time Series Prediction using an Evolved Fuzzy Rule Base System

Financial time series prediction, such as, index funds or individual stocks, is a very active area of research. The goal of this project is to develop an evolved fuzzy rule base system based on technical indicators to predict the next trading day price movement of an individual stock or index fund.

This project is suitable for an independent study (either undergraduate or graduate), MS project or thesis. Student funding is not available at this time.

 

Interested students should contact Dr. Roger S. Gaborski, Department of Computer Science, rsg@cs.rit.edu

 

Curriculum Vitae

Teaching (Fall Semester):

   FALL
CSCI-431
Introduction to Computer Vision Rm (GOL) -1610  Tu/Th 8:00-9:15
CSCI-631
Foundations of Computer Vision
Rm (GOL) - 3445 Tu/Th 9:30 - 10:45




Semester Courses - tentative description and schedule (see course links above for this quarter's updated information):

CSCI-431 Introduction to Computer Vision Syllabus
CSCI-431 Introduction to Computer Vision Schedule

CSCI-631 Foundations of Computer Vision Syllabus
CSCI-631 Foundations of Computer Vision Schedule

CSCI-731 Advanced Computer Vision Syllabus
CSCI-731 Advanced Computer Vision Schedule

CSCI-633 Biologically Inspired Intelligent Systems Syllabus
CSCI-633 Biologically Inspired Intelligent Systems Schedule


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