Experience
Here, you can find details regarding my internship positions in the industry, as well as my research experience since my arrival at ETH Zurich.
Research Experience
Research Assistant, Social Networks Lab - ETH Zurich ![](/images/eth_z_logo.png)
I have been affiliated with the Social Networks Lab at ETH Zurich, since November 2021, under the supervision of Prof. Dr. Ulrik Brandes. I have been working with soccer data, more concretely, spatio-temporal network data, gathered from player locations in matches. I have also been using event data, timestamped occurences of events and details about them throughout the match. I am the principal researcher for the passing events, we are trying to identify what makes a pass interesting and unusual, and answer the question “do certain players and teams have tendencies for these kinds of passes?”. I have also been assisting a different research trajectory as a secondary researcher, for creating algorithms that detect in-game formations automatically, using edge and vertex attributes of these networks.
Student Researcher, Learning and Adaptive Systems Group - ETH Zurich ![](/images/eth_z_logo.png)
I have assisted the large project for investigating the usage of Bayesian Optimization, Reinforcement Learning and Machine Learning in Agriculture, as a student researcher (counted for my “Research in Data Science” course at ETH Zurich), under the supervision of Prof. Dr. Andreas Krause. For more details, feel free to check the Projects tab!
Student Researcher, Computational Social Science Lab - ETH Zurich ![](/images/eth_z_logo.png)
As a team of 3, under the supervision of Dr. Nino Antulov-Fantulin and Dr. Vaiva Vasiliauskaite, we investigated how social media sensing can improve cryptocurrency portfolios, through volatility forecasting of Bitcoin (counted for my “Data Science Lab” course at ETH Zurich). We applied and compared state-of-the-art deep learning techniques for time-series data, and observed that the user information is statistically most valuable, in terms of increasing forecasting performance of such tools. This resulted in a conference paper in ACM WSDM 2023, for more details and the paper, feel free to check the Publications tab!
Industry Experience
Computer Vision Engineer Intern, Karel Electronics ![](/images/karel_logo.png)
For my summer internship in 2019, I was at Karel Electronics, Ankara, working in the R&D department. My task was to implement a full-stack application to be deployed in the conveyor belt in Karel’s main factory, that would detect soldering defects in PCBs to be used in their devices, through their images. The images were taken using 4K cameras, and the application needed work seemlessly without the need of a supervisor to inspect the PCBs manually, or the software. I applied CV techniques and used CNNs to successfully detect these defects.
Software Engineer/Consultant Intern, Deloitte ![](/images/deloitte_logo.png)
For my summer internship in 2018, I was at Deloitte, Istanbul. I was working with the Digital Consulting team, who have been working with a client for 4 months to build a efficient system for high-power phone centrals. One of their sub-tasks was to also build a displaying system, so that the client employees can verify and monitor the usage of the proposed system and it’s statistics through their smartphones. I mainly worked on the front-end side, building UI of the application on Android Studio, with some back-end side as well for logging in, and reporting (I basically implemented some standart SQL protocols).
Electronics Engineer Intern, Stigma Electronics
As a voluntary internship, in the winter break (2017) of my freshman year in Bilkent University, I joined a start-up company who were building hardware for elevators that were going to be mainly used in large buildings. They were optimizing the circuitry for idleness and power-saving. I helped the Electronics Engineers there writing some subroutines in Embedded C. It was a valuable experience for me, as this was the first time I saw how software goes hand-in-hand with hardware.