I’m a Software Engineer at Uber, working to improve system efficiency, reliability, and developer productivity. My work spans program analysis, compiler technology, and AI-assisted developer tooling.
Previously, I obtained my PhD in Computer Science from Aarhus University, advised by Andreas Pavlogiannis. My research focused on efficient data structures and algorithms for dynamic analysis of concurrent programs.
Publications
- PLDI 2026
- TOCS 2026Efficient Dynamic Concurrency Analysis with Collective Sparse Segment Trees.
Hünkar Can Tunç, Yifan Dong, Ameya Prashant Deshmukh, Berk Cirisci, Constantin Enea, Andreas Pavlogiannis.
- PhD Thesis
- ASPLOS 2024
- PLDI 2023
- PLDI 2023
- ASPLOS 2022
- FoSSaCS 2022DyNetKAT: An algebra of dynamic networks.
Georgiana Caltais, Hossein Hojjat, Mohammad Reza Mousavi, Hünkar Can Tunç.
- TASE 2022A language-based causal model for safety.
Marcello Bonsangue, Georgiana Caltais, Hui Feng, Hünkar Can Tunç.
- JLAMP 2021
- MBEC 2020Estimation of Parkinson’s Disease Severity Using Speech Features and Extreme Gradient Boosting.
Hünkar Can Tunç, Cemal Okan Sakar, Hulya Apaydin, Gorkem Serbes, Aysegul Gunduz, Melih Tutuncu, Fikret Gurgen.
Best Paper Award
- ASC 2019A comparative analysis of speech signal processing algorithms for Parkinson’s disease classification and the use of the tunable Q-factor wavelet transform.
Cemal Okan Sakar, Gorkem Serbes, Aysegul Gunduz, Hünkar Can Tunç, Hatice Nizam, Betul Erdogdu Sakar, Melih Tutuncu, Tarkan Aydin, Muhammed Erdem Isenkul, Hulya Apaydin.
- DATA 2019Detection of e-Commerce Anomalies Using LSTM-Recurrent Neural Networks.
Merih Bozbura, Hünkar Can Tunç, Miray Endican Kusak, Cemal Okan Sakar.
