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Furkan Akkurt

Cloud Devops Engineer

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About Me

Hey there! I'm Furkan Akkurt, a Cloud DevOps Engineer with Full Stack development background and academic foundation. My journey in the tech world has been quite the adventure. Academically, I have worked on Medical Image Reconstruction and Analysis using Deep Learning and Privacy-Preserving Federated Learning where I cultivated a rich knowledge base. From optimizing cloud infrastructure to building robust backend systems, I have been working on developing, building, and deploying mid to large scale systems, and ensuring their high-availability, optimizing performance, scalability, and reliability in the ever-evolving cloud environment, using IaC and DevOps tools. I have also been working on MLOps and DataOps to build and deploy machine learning models and data pipelines.

Experience

Lyrebird Studio

Cloud DevOps Engineer

Manage and deploy scalable infrastructure solutions on Amazon Web Services (AWS) using Cloud Development Kit (CDK), ensuring optimal performance, reliability, and security. Contribute to the development and maintenance of high-traffic applications, receiving millions of requests on a daily basis. Contribute to the development of MLOps pipelines and processes, enabling the seamless deployment and monitoring of machine learning models in production.

Commencis

Cloud Engineer

Responsible for managing the cloud infrastructures of both our customers and our own. I manage environments in Google Cloud and mostly in AWS. Applying DevOps practices in order to deliver better software products. Using CI/CD methods to automate the process of software delivery.

CryptoIndexSeries

Software Engineer

At CryptoIndexSeries, I was responsible for developing both backend and frontend applications using JavaScript. I have written microservices for our web application, using NodeJS. For frontend, I contributed to the company's codebase by improving the UI features using ReactJS. Other technologies I have used were AWS Lambda functions, WebSockets, PostgreSQL, and more.

Istanbul Technical University

Undergraduate Researcher

Under the supervision of Associate Professor Ilkay Oksuz, I have worked on the research project Interpretable Deep Learning for Fast Medical Image Reconstruction and Analysis. I specifically worked on Bone Segmentation. Contributed to the project with literature reviews, presentations, and my coding skills. I created and trained several DL models to apply image segmentation on x-ray images, using Python, Keras, Numpy, imgaug and several more tools.

Koc University

Summer Intern

I have worked for two months on Artificial Neural Networks, Deep Learning, and Convolutional Neural Networks. Implemented different Deep Learning models such as object detection, face recognition, and neural style transfer. Used tools like Tensorflow, Keras, and Numpy.

Education

University of California, Riverside

August 2022 - February 2023

PhD in Electrical and Computer Engineering

Worked on Privacy-Preserving Federated Learning and Differential Privacy for a while. Dropped out of the program to pursue my career in the industry.

Bilkent University

September 2017 - June 2022

B.S. in Computer Science

Graduated with a GPA of 3.48/4.00. Some of the courses i took are; Data Structures, Algorithms, Operating Systems, Computer Networks, Database Systems, Computer Architecture, Machine Learning.

Projects - Talks

Innovating with Generative AI on AWS

October 3rd 2023 - Istanbul, Turkiye

Gave a presentation on Innovating with Generative AI on AWS at AWS Cloud Day Turkiye 2023. Talked about GenAI and how our company used AWS to serve our users efficiently.

Talk

Plantify

Graduation Project

Cross-platform mobile application that provides users with a better hobby-gardening experience. The application includes plant detection using Machine Learning, social media tab, soil, water, humidity tracking with Arduino, and more. Main technologies: Flutter, NodeJS, PyTorch, Docker.

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American Sign Language Detector

Course Project

Using American Sign Language (ASL) dataset, implemented two different machine learning models using Convolutional Neural Networks (CNNs) and Decision Trees (DTs). On top of those models, built a system with Python cv2 to capture letters from the video and predicts them.

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Medical Image Reconstruction and Analysis using UNet

Project

Segmentation of x-ray images using UNet architecture.

View Project

Achievements

Skills & Languages

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