Dr. Ömer Sezer

- Kubernetes: Creating, managing, and monitoring test, production K8s Cluster (Win, Linux) on-premise - AWS with Terraform: Provisioning EC2, ECS, VPC, EKS, Lambda, API-Gateway, ELB, S3, VPN, CI/CD pipelines (Code Pipeline, Build, Deploy). - Ansible: Creating playbooks to control servers (Linux, Win) to run commands, scripts - Dockerizing Projects, Gitlab Pipelines - Distributed Apps: Elastic Search (ELK), Prometheus/Grafana, Jenkins, Gitlab Runners - Developing Bash, Ps1, Python Scripts - Internal Trainer

- DevOps: Jfrog CPP Artifactory, Custom Conan package creation, Dockerizing the project, CMake files organization. - Automotive Test Framework Software: Implemented 3/20 subprojects in C++ Framework. (C++, Python, Cmake, Conan, Linux, Git, Jira, Confluence, Docker). - Desktop Application and API implementation for the device configuration. (Python, Google Protobuf, Linux). - Implemented Desktop Application for the Trace Replay of the Automobile Buses (CAN, FlexRay, LIN, PLP) Logs with the team. (C#, Win).

Space Technologies Research Inst: - Satellite Ground Station Equipment Control Software & Satellite Simulator Control Software: Developed 2 different desktop apps with UI and SOA using Java, Eclipse RCP, OSGI, SWT, Sqlite, JMS, JavaFx. - Production, Testing Demand and Tracking System & Material, Service Demand and Tracking System: Developed 2 different web apps with UI and DB using Bootstrap, PHP, MySql. - Telemetry Anomaly Detection App: Developed using Python, Tensorflow. - Impl. Jenkins-GitLab chain.

- Project: Proposed a new deep learning network (3D-CNN) and used transfer learning (RES-NET, 2D-CNN) in order to realise subatomic neutrino particles classification and identification in a Liquid Argon Time Projection Chamber technology which will be used for the DUNE Experiment using Python, Tensorflow (Run on GPU). - Published Deep Learning survey journals: "Financial Time Series Forecasting with Deep Learning" and "Deep Learning in Finance".

- Using Keras, Tensorflow, Matplotlib, Python, Pandas, Numpy, Java, Spark ML: - Project: Developed ETL/ML pipeline and propose new deep learning CNN methods that in the time-series financial data to predict future trends (CNN-TA and CNN-BI) - Project: Developed ETL/ML pipeline with multi-layer perceptron network and genetic algorithm. - Project: Anomaly detection method in IoT weather sensors using LSTM, Tensorflow.

- Developed on-board-satellite-computer software tasks using C. - Developed embedded programs for microcontrollers (CAN-SU) for satellite modules.

Machine Learning, Deep Learning, AI. Time Series Analysis, Anomaly Detection, 2D Image Generation, Image Classification using DL. Tech Stack: Python, Numpy, Pandas, Scikit Learn, Keras, Tensorflow, Java, SparkMl.

Computer Networks. Implementation of a new plane for Dynamic Distributed Dependable Real Time Ethernet Industrial Protocol (real time industrial communication protocol that runs over shared-medium Ethernet with COTS hardware) to achieve dependability using C, C++, Linux (Ubuntu).

Computer