
About
Burak Tagtekin is a researcher in computer science with significant contributions to optimization algorithms, recommender systems, and machine learning applications. His work spans both theoretical and practical domains, including evolutionary algorithms for compiler flag tuning, Bayesian personalized ranking models for recommendation systems, and genetic algorithm-based approaches to job scheduling and resource allocation challenges.
- Key Research Areas: Optimization Algorithms, Recommender Systems, Machine Learning, Compiler Engineering, Scheduling Problems
- Collaborations: Frequently collaborates with researchers like Tuna Çakar, Mahiye Uluyagmur Öztürk, and M. Sezer
Recent Publications (2021-2024) demonstrate expertise in genetic algorithms, particle swarm optimization, and Bayesian modeling, achieving notable improvements in execution time and resource efficiency across diverse applications such as C++ compilation, job prioritization, and implicit feedback-based recommendation systems.
Co-Author Network includes 18+ collaborators across computer science and engineering fields, with institutional connections to IEEE conferences and academic research communities.
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