Feridun Tütüncüoğlu

I successfully completed my PhD journey on June 10 with a public defense. It shed light on how to model the interaction between edge/cloud operator and users to optimize both resource utilization and operator's profit, while optimizing the users' costs. The proposed solutions are heavily based on learning user behavior and workload patterns to dynamically adapt pricing and resource allocation policies.

I joined Ericsson Research in Stockholm, Sweden, as a research intern, where I continued and extended the core ideas from my PhD work. This included the orchestration of heterogeneous edge server clusters and application placement strategies to optimize resource utilization while ensuring Quality of Service (QoS) for latency-sensitive workloads.

I joined to the Network and Systems Engineering Division at KTH Royal Institute of Technology as a PhD student, and as a researcher to TECoSA Project. My advisors were György Dán and James Gross. The research topic is the joint optimization of resource allocation and pricing in Edge Computing.

I successfully defended my Msc. thesis. My advisors were Orhan Arikan and Sinan Gezici. The research focused on improving Random Access Channel (RACH) user detection in the 5G physical layer.

I completed my BSc in Electrical and Electronics Engineering at Bilkent University, where I was first introduced to telecommunications and inspired by many leading researchers in our department.

During my BSc, I squeezed two internships. I joined Intel in Munich as a working student, focusing on channel estimation and the physical layer of LTE, and Zodiac Aerospace in Los Angeles, where I worked on the electrical wiring systems of aircrafts.

Joint Optimization of Pricing and Resource Allocation in Serverless Edge Computing, PhD. Thesis, 2025 Feridun Tütüncüoğlu

Dynamic Time-of-use Pricing for Serverless Edge Computing with Generalized Hidden Parameter Markov Decision Processes, ICDCS, 2024 Feridun Tütüncüoğlu, Ayoub Ben-Ameur, György Dán, Andrea Araldo, Tijani Chahed

Sample-efficient Learning for Edge Resource Allocation and Pricing with BNN Approximators, INFOCOM - ICCN Workshop, 2024 Feridun Tütüncüoğlu, György Dán

Joint Resource Management and Pricing for Task Offloading in Serverless Edge Computing, IEEE TMC, 2023 Feridun Tütüncüoğlu, György Dán

Optimal Service Caching and Pricing in Edge Computing: A Bayesian Gaussian Process Bandit Approach, IEEE TMC, 2022 Feridun Tütüncüoğlu, György Dán

Online Learning for Rate-Adaptive Task Offloading Under Latency Constraints in Serverless Edge Computing, IEEE/ACM ToN, 2022 Feridun Tütüncüoğlu, Sladjana Josilo, György Dán

Optimal Pricing for Service Caching and Task Offloading in Edge Computing, WONS, 2022 Feridun Tütüncüoğlu, György Dán

The following links show some research projects that I made public. Some were made and used during my PhD work, and some are just side fun projects. Yet, they are all my precious...

Bayesian Neural Network (BNN) repository

Edge-Enabled Inverted Pendulum

Throughout my journey leading to the PhD, I served as a teaching assistant for the courses Protocols and Principles of the Internet and Internetworking at KTH. Earlier in my academic path, I was the lab coordinator for the Microprocessors course, and I also worked as a tutor and grader for Algorithms and Programming (CS 101) and General Physics I (PHYS 101). Concurrently, I supervised numerous MSc students in their thesis work.

I also served as a reviewer for IEEE Transactions on Mobile Computing (TMC), IEEE Transactions on Cloud Computing (TCC), IEEE/ACM Transactions on Networking (TNSE), IEEE ICDCS, and Elsevier Computer Networks.

I had written several technical write-ups — mostly on machine learning derivations and tutorials — as well as some non-technical articles, which, for some reason, mostly revolve around Formula 1. I've now decided to re-organize and publish them all here in one place. This section is under construction.

Feridun Tütüncüoğlu

Publications

Projects

Teaching and Services

Appendix