Bayazit Karaman

Visiting Assistant Professor of Computer Science
Hendrix College · Conway, AR · karaman@hendrix.edu

Hello! I graduated from Istanbul Kultur University (TURKEY) with a B.E. in Computer Engineering, and I earned my M.S. and PhD in Computer Science from University of Arkansas at Little Rock in May 2015 and May 2018, respectively.

My main research interests are in Signal Processing, Brain Functions and Disorders, Machine Learning and Brain Research Development Tools.

Please feel free to check out my CV.


Teaching

Current Teaching

Students study problems arising from the physical, biological, and/or social sciences and the algorithms and theory used to solve them computationally. Included among the problems are numerical methods for maximizing a function and solving a differential equation.

An introduction to recent tools and algorithms for building interactive games. Students will learn fundamental design mechanics and implement a substantial development project. Topics may include steering and flocking behaviors, path finding algorithms, finite state machines, behavior trees, alpha-beta pruning, Monte Carlo Tree Search, shaders, 3D modeling, animation, procedural content generation, and the intersection of games and society. Content varies according to the interests of the participants and instructor.

Introduction to solving computational problems, including the fundamentals of computer programming. Topics include imperative programming constructs (variables, loops, conditionals, functions, recursion), basic object-oriented constructs (classes, objects), and some fundamental algorithms and data structures (dictionaries, arrays, linked lists). Student learn these concepts through studying the Python programming language.

Spring 2019

Teaching History

Hendrix College

CSCI 230 - Computing Systems Organization (Fall 2018)

This course is a study of the layers of abstraction composing the design of modern computing systems. Topics include numeric representation, digital logic, CPU design, machine and assembly language, the program stack, virtual machines, compilers, assemblers, memory management and device drivers.

CSCI 151 - Data Structures with Lab (Fall 2018)

Building on the skills acquired in CSCI 151, this course introduces data structures such as lists, stacks, queues, trees, and graphs, in the context of object-oriented software design. We will program using the Java language.

CSCI 410 - Senior Seminar (Fall 2018)

A combination of readings, writing assignments, oral presentations, and independent project work integrates the lessons from each student's undergraduate studies. Students assess the content of formal writing about computing subjects, investigate ethical and social issues in computing, and complete a substantial independent capstone project. Students also prepare themselves for professional work by resume writing and the creation of a professional portfolio.

University of Arkansas at Little Rock

CPSC 1370 - Computer Literacy (Fall 2017, Spring 2018)

This is a hands-on course in which you will learn to use a computer to practice the four most popular programs within the Microsoft Office Suite (Word, Excel, Access, and PowerPoint). You will learn to be an intermediate level user of the Microsoft Office Suite. Within the Microsoft Office Suite, you will use Word, Excel, Access, and PowerPoint.

Fall 2017 - Fall 2019

Research

STRUCTURAL AND FUNCTIONAL CONNECTIVITY OF THE BRAIN

ANTIPODAL CONNECTIVITY STRUCTURE OF NEURAL COMMUNITIES

Functional and structural networking of neurons governed with a set of organizational principles forms a modular/colonial structure that controls the information processing behaviour of human. The structures in this environment are hierarchical in nature and connections are established through the mutually exclusive nodes. Therefore, it is safe to hypothesize that the decision mechanism behind a cognitive process takes place at the highest hierarchical and spatial level. In order to conduct the necessary experimentation to support the hypothesis, a non-invasive method called Electroencephalography (EEG) is used to monitor and record the electrical activity of the brain for detecting and analyzing the cognitive functions and mental disorders. One innovative finding of this study is the use of EEG to find Antipodal Hub Nodes (AHNs) which are dynamic and provide collaborative information.

Neural Activity Monitoring System (NAMS)

The NAMS is an interactive software environment to analyze and monitor the coordinated complex network structures of the neural communities. The purpose of a toolbox-oriented system is to support scalability and minimally invasive enhancement for behavioural pattern identification and analysis.

August 2011 - Present

Understanding of the Brain Disorders

Obsessive Compulsive Disorder (OCD)

The cortical behavior at neural level could be originated from specified disorder such as Obsessive-Compulsive Disorder (OCD). OCD is a commonly encountered long-lasting mental health disorder that affects the daily activities of the people in all ages with a cycle of obsessions and compulsions. It is known to be the fourth most common mental illness. Despite of the research being conducted on the condition, the exact cause, other than having neurobiological base and different neurological patterns in people with the disorder, is yet to be identified. Although OCD abnormalities are associated with the imbalance in neurotransmitters or brain chemicals, it is necessary to classify the behavioural patterns of the brain for understanding cause and effect related details. Therefore, the objective of this study is to develop an algorithm to analyze EEG data to obtain significantly improved classification accuracy, which could sufficiently contribute to the identification of dysfunctional lobes of OCD.

May 2014 - Present

Publications

Journals

Published
  • Modeling the Antipodal Connectivity Structure of Neural Communities (Bayazit Karaman, R. Murat Demirer, Coskun Bayrak, M. Mert Su. AIMS Neuroscience. 2016;3(2):163-180 DOI 10.3934/Neuroscience.2016.2.163)
  • Video Enhanced RFID Tracking System (Arica, Nafiz, Anil Celik, Bayazit Karaman, Coskun Bayrak, and Onur Kececi. International Journal of Applied Mathematics, Electronics and Computers 3, no. 4 (2015): 226-231.)
Under Review
  • Classification of Obsessive Compulsive Disorder by Fractal Dimension Complexity of EEG (Bayazit Karaman, Coskun Bayrak, Serap Aydin, Nafiz Arica, Oguz Atay)
  • Antipodal Connectivity Structure in Neural Activities based on Riemann Sphere (Bayazit Karaman, Coskun Bayrak, R. Murat Demirer)
  • The Role of Antipodal Hub Nodes on Cognitive Functions (Bayazit Karaman, Coskun Bayrak, Kamran Iqbal)

Conferences

Under Review
  • NAMS: An Environment for Visualization of Hidden Structures in Neural Activities (Bayazit Karaman, Coskun Bayrak)