Deniz Akkaya
"Mathematics is the language of the universe." ~ Galileo Galilei
Ph.D. Candidate and Research Associate in Industrial Engineering specializing in sparse optimization, robust regression, and mathematical programming. Seeking academic opportunities in applied mathematics, operations research, or related quantitative disciplines.
Research Interests
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Strengthening the theory of sparse optimization in both deterministic and stochastic settings,
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Developing efficient algorithms—exact, heuristic, and hybrid—for high-dimensional problems,
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Applying these methods to finance, signal recovery, and healthcare,
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Exploring sparsity in machine learning for interpretability and structured feature selection.
Publications
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D. Akkaya, M. Ç. Pınar, Critical Point Theory for Sparse Huber Recovery. Optimization. (2025, Submitted)
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B. Çetin, D. Akkaya, M. Ç. Pınar, Sparsity Constrained Minimax Optimization with Applications to Sparse Boosting and Game Theory. SIAM Journal on Optimization. (2025, Submitted)
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D. Akkaya, M. Ç. Pınar, Minimizers of Sparsity Regularized Least Absolute Deviations. Journal on Global Optimization. (2025, Submitted)
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B. Şen, D. Akkaya, M. Ç. Pınar, Sparsity Penalized Mean–Variance Portfolio Selection: Analysis and Computation. Mathematical Programming. 211, 281–318 (2025)
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M. Ç. Pınar, D. Akkaya. Problems and Solutions for Integer and Combinatorial Optimization: Building Skills in Discrete Optimization, Philadelphia: SIAM. (2023)
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Ö. Ekmekcioğlu, D. Akkaya, M. Ç. Pınar, Subset Based Error Recovery. Signal Processing, 191, 108361. (2022)
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D. Akkaya, M. Ç. Pınar, Minimizers of Sparsity Regularized Huber Loss Function. Journal of Optimization Theory and Applications , 187, 205–233 (2020)