Data Scientist
Resume:
E R E N B O Z A R I K
D a t a S c i e n t i s t & A n a l y s t
Statistical Learning
by Stanford University
Deep Learning Specialization
by deeplearning.ai
IBM Data Science Professional
TensorFlow Professional Developer
by deeplearning.ai
AI for Medicine Specialization
by deeplearning.ai
Summer 2016
2018
Summer 2018
I organized twice a summer technology
camp for high school students. In this camp, I
teach many computer science courses.
Introduction to CS, Introduction to Python,
Fundamentals of Machine Learning,
Entrepreneurship 101, Arduino 101
I developed the Turkey National Robotics
Conference’s (ToRK) official website. I
developed this website using the WordPress
infrastructure.
I worked on a 3D object scanning and
modeling project. I developed this system
using Raspberry Pi and Arduino.
Machine Learning
by Stanford University
***********@*****.***
Certificates
Contact
Bağcılar, İstanbul, TR
@erenbozarik
@erenbozarik
WORK EXPERIENCE
İstanbul Medipol University - İstanbul
Lecturer
ToRK.org.tr
Web Developer
Kovan Research Lab (METU) - Ankara
Software Developer
Summer 2019
İstanbul Medipol University - İstanbul
Business Development Intern
International Office
I have worked on digital marketing
techniques, data reporting, translation and
social media management to reach
international students.
Within this research group, I worked on
image processing-centered projects such as
object detection, fake image data
generation (GAN), and style transfer.
I developed a style transfer project to apply
the styles of works made with the marbling
technique on real-world objects.
Deep Science Lab
Deep Learning Researcher
2018 - 2019
Feb 2021
Nov 2020
2020
2017-2021
Apr - Jun 2016
2019
2019
Vice President
Statistics and Computer Science Society
Member
IEEE KTU Student Branch
SMLR is an initiative based on artificial
intelligence research. My goal to write articles
and develop projects about AI and Data Science.
EDUCATION
Karadeniz Technical University - Trabzon
B.Sc. - Statistics and Computer Science
ARTICLES
SMLR.CENTER
Statistics and Machine Learning Research Center
Personal Blog
I developed software to calculate the price
and weight of the models that the users
want to be produced as 3D models.
3Durak - 3D Printing House - İstanbul
Software Developer
Tasdelen A., Bozarık E., Umay C., Komecoğlu Y.,
Ozdemir S. (2019). Triggering Diversity of
Artificial Intelligence Based Art Research by
using Turkish-Ottoman Art Genre, Journal of
Data Science and Applications (DataSCI), 2(1).
PUBLICATIONS
IEEE Computer Society Machine Learning
Conference at Medipol University
INVITED TALKS
2019 IEEE Computer Society Python Programming
Workshop at Medipol University
2018 Algorithm Age : AI / Uskudar Cagribey Anatolian High School
2018 Algorithm Age : AI / Women Techmakers by
Google Developer Group at Trabzon
SPSS, Rapid Miner, MSSQL
Keras, TensorFlow, Numpy, Pandas,
H2O, SciKit Learn, Django, Asp.Net
Skills
Python, C#, C++
Google Data Studio, Google Cloud
Languages
Turkish : Native
English : Advanced
Eyüpoglu Foundation Scholarship
(During all BSc. education)
Scholarship
Bertelsmann Tech Scholarship
Activities
Visual Studio, Tableau, Microsoft
Office
Data Visualization, Data Reporting
2019
2020
This study has been prepared for contributing to
that cultural competition by emphasizing one of
the Turkish-Ottoman art genres, called Ebru. In
order to fulfill that contribution, an unique data set
(Deep Novice Ebru-DNE) with 5 classes have
been prepared and a style transfer algorithm has
been applied on it. Thus a different art genre was presented to triggering diversity of AI based art
research.
In this study, a neural network automatically
segments tumor regions in the brain, using MRI
(Magnetic Resonance Imaging) scans. I using the
data from the Decathlon 10 Challenge and 3D U-
Net as a model. The advantage of the volumetric
shape of MR images and is one of the best
performing models for this task.
In this study, the detection of the runway areas
called the heliport via satellite images was carried out with deep learning techniques. By using
Faster-CNN architecture and a modified model,
99% successful determinations were performed
on the data set created by the researchers.
This project’s goal to diagnose chest diseases
from chest X-Ray scans using Deep Learning
and ChestX-ray8 dataset.
SELECTED PROJECTS
Brain Tumor Auto-Segmentation for MRI
Diagnosis from X-Ray Images
Heliport Detector
Deep Novice Ebru Dataset
AI in Art
AI in Medicine
AI in Medicine
AI in Military
2019
Ali Emre Turgut 2020
Middle East Technical University
Mehmet Kemal Özdemir
İstanbul Medipol University
References
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Şebnem Özdemir
İstinye University
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