Email: ali-burak.uenal [at] uni-tuebingen.de
 

Research Interests

• Privacy preserving machine learning
• Kernel methods
• Machine learning
• Computational Biology
• Personalized Medicine
   

Academic Degrees

• Ph.D. in Computer Science, University of Tübingen, 2022.
  Thesis: Towards A Complete Privacy Preserving Machine Learning Pipeline
• M.Sc. in Computer Engineering, Bilkent University, Turkey, 2017.
  Thesis: Identification of Cancer Patient Subgroups via Pathway-based Multi-view Graph Kernel Clustering
• B.Sc. in Computer Engineering, Bilkent University, Turkey, 2015.
   

Publications

• Ali Burak Ünal, Mete Akgün, Nico Pfeifer
  ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare, Association for the Advancement of Artificial Intelligence (AAAI) 2021
• Yasin Tepeli*, Ali Burak Ünal*, Furkan Mustafa Akdemir, Öznur Taştan
  PAMOGK: a pathway graph kernel-based multiomics approach for patient clustering, Bioinformatics (2020)
• Huajie Chen, Ali Burak Ünal, Mete Akgün, Nico Pfeifer
  Privacy-preserving SVM on Outsourced Genomic Data via Secure Multi-party Computation, March 2020, IWSPA '20: Proceedings of the Sixth International Workshop on Security and Privacy Analytics (Association for Computing Machinery, Pages 61–69)
• Efe Bozkir*, Ali Burak Ünal*, Mete Akgün, Enkelejda Kasneci, and Nico Pfeifer.
  Privacy Preserving Gaze Estimation using Synthetic Images via a Randomized Encoding Based Framework
  Eye Tracking Research and Applications (ETRA) 2020
• Ali Burak Ünal, Mete Akgün, N. Pfeifer
  A framework with randomized encoding for a fast privacy preserving calculation of non-linear kernels for machine learning applications in precision medicine,
  CANS 2019, Lecture Notes in Computer Science book series (LNCS, volume 11829)
• Ali Burak Ünal, and Öznur Taştan
  Identification of Cancer Patient Subgroups via Smoothed Shortest Path Graph Kernel
  NIPS Workshop on Machine Learning in Computational Biology (2016)