Zikri Bayraktar, Ph.D., CAPMWelcome to my portfolio! Currently, I work as a senior research scientist at the Schlumberger-Doll Research Center in the field of computational electromagnetics, optimization and inversion. Before that, I was an Advisory Engineer at the IBM SRDC (Semiconductor Research and Development Center) focusing on computational lithography modeling for IBM server microchips. Since my background is in computational science and engineering, it was a natural extension for me to learn more about the data science and machine learning. I will keep this page updated as I sharpen my data science and machine learning skills through formal education, MOOC courses and practical projects. In addition to my graduate level course work in computational EM methods, I have also completed the Computational Science Ph.D. minor at Penn State, yet there is more to be learned and implemented. My publications can be easily accessed through Google Scholar from the links provided at the top of the page.
EDUCATIONI received my B.Sc. (Honors), M.Sc. and Ph.D. in Electrical Engineering focusing on Computational Electromagnetics and Optimization from the Pennsylvania State University. Along with my Ph.D., I completed a Ph.D. Minor in Computational Science. As part of my Computational Science Ph.D. minor requirements, I took the following courses at Penn State University:
I successfully completed the online Machine Learning course from Stanford University by Prof Andrew Ng. along with the IBM's Deep Learning 101 and IBM's Deep Learning with TensorFlow.
I also completed the Udacity Deep Learning Foundation Nanodegree as well as more advanced Udacity Deep Learning MOOC by Google.
Self Driving Car Engineer Nanodegree
I recently started the Udacity's Self Driving Car Engineer Nanodegree.
R Programming Language
I completed the Johns Hopkins University R Language as well as the UC Irvine R Programming course.
Python Programming Language
I completed the Code Academy - Python course, Udemy Intro to CS with Python as well as the Google's Python Class.
Other Programming Languages
I also use Matlab on a daily basis, and I used Fortran in graduate school, TCL at IBM, HTML personally, and C++ during my undergraduate studies.
I took following courses from Johns Hopkins University, focusing on data wrangling in R language:
Optimization and Inversion
One of my passions is heuristic optimization methods. They are also called global optimization algorithms and some are nature-inspired optimization methods. Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Clonal Selection Optimization Algorithm (Clonalg), and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) are few of the methods that I studied, utilized and published on.
I also invented and published a novel optimization algorithm called the Wind Driven Optimization (WDO), you can visit at this link to learn more about it. You can also find sample WDO codes written in Matlab, R, and TCL. Fortran and Python codes are in progress.
Here are some of my journal articles. For full list of my publications, please refer to my Google Scholar profile.
 Fast optimization of electromagnetic design problems using the covariance matrix adaptation evolutionary strategy, MD Gregory, Z Bayraktar, DH Werner, Antennas and Propagation, IEEE Transactions on 59 (4), 1275-1285
 The design of miniature three-element stochastic Yagi-Uda arrays using particle swarm optimization, Z Bayraktar, PL Werner, DH Werner, Antennas and Wireless Propagation Letters, IEEE 5 (1), 22-26
 A real-valued parallel clonal selection algorithm and its application to the design optimization of multi-layered frequency selective surfaces, Z Bayraktar, JA Bossard, X Wang, DH Werner, Antennas and Propagation, IEEE Transactions on 60 (4), 1831-1843
 The Wind Driven Optimization Technique and its Application in Electromagnetics, Z Bayraktar, M Komurcu, J Bossard, D Werner, IEEE Transactions on Antennas and Propagation, 2013.
 GA optimized reconfigurable frequency selective surfaces for passive standoff detection of chemical agents, Z Bayraktar, MG Bray, DH Werner, Antennas and Propagation Society International Symposium, 2008. AP-S 2008. IEEE
As someone working in industry, I found it to be invaluable to attain certain business skills. To this extend, I completed following certifications and online courses.
1. Amazon Web Services (AWS):
I took on learning what the AWS has to offer and experiment with each of the services to become proficient at it. AWS offers a wide range of cloud computing tools and this will be quite exciting. Using the AWS Free Usage Tier, we will try to experiment with AWS as much as I can.
IAM provides capability to define access groups and assign users to each group to control the access permission and what they can do on the AWS. It is not recommended to login to your AWS console with the email address that you used to create the AWS account, because it gives a root access to all services creating a security vulnerability. It is preferred that you define an 'Administrator' group, create Admin user and access your services through that user. One can follow the short AWS IAM video to achieve this simple task.
S3 offers a simple storage capability for static files and I migrated this website, i.e. the PadawanDataScientist.com to S3 for static website hosting. It is running from AWS S3 right now! Since I am already paying GoDaddy for domain name hosting, I did not bother to make any changes to the DNS setup through Route 53. Maybe in the future.
Glacier offers long term storage that is not easily accessible. Note that the content stored in Glacier is frozen and stored, and once access is requested it requires time to restore it. According to Amazon this might be 20min to 1 hour to de-freeze your data and allow you access it. Then, there is only 24 hours to copy/download it. This is a good place to freeze your data for long term storage like the external hard-drives.
Tweets by zikribayraktar