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Mustafa Misir

Associate Professor of Computational Science at Duke Kunshan University
DKU Faculty

Overview


Mustafa MISIR is an Associate Professor of Data and Computational Science at Duke Kunshan University (China). He completed his Ph.D. in Computer Science at KU Leuven (Belgium) in 2012. After graduation, he worked as a postdoctoral researcher at INRIA Saclay - Universite Paris Sud XI (France), Singapore Management University (SMU) and University of Freiburg (Germany) respectively. He was also a visiting researcher at University of Zurich (Switzerland) and Universitat Politècnica de Catalunya (UPC) / BarcelonaTech (Spain) during his stay at INRIA. Afterwards, he moved to Nanjing University of Aeronautics and Astronautics (China) as a faculty member at the College of Computer Science and Technology. Prior to joining Duke Kunshan University, he was a faculty member in Computer Engineering at Istinye University (Turkiye). His main research interests include automated algorithm design (machine learning + algorithm design), data science and operations research.

Current Appointments & Affiliations


Associate Professor of Computational Science at Duke Kunshan University · 2021 - Present DKU Faculty

Recent Publications


Deep reinforcement learning for solving the stochastic e-waste collection problem

Journal Article European Journal of Operational Research · November 16, 2025 With the growing influence of the internet and information technology, Electrical and Electronic Equipment (EEE) has become a gateway to technological innovations. However, discarded devices, also called e-waste, pose a significant threat to the environmen ... Full text Cite

Algorithm Selection for Protein Structure Prediction on 2D AB Off-lattice Model

Conference Iccbb 2024 Proceedings of the 2024 8th International Conference on Computational Biology and Bioinformatics · June 4, 2025 The present study performs Algorithm Selection for Protein Structure Prediction. The idea is to automatically determine the best algorithm for each given instance through performance prediction. The Protein Structure Prediction problem is concerned with ex ... Full text Cite

Enhancing Molecular Docking Performance with a GNN-Based Algorithm Selection Model

Conference Iccbb 2024 Proceedings of the 2024 8th International Conference on Computational Biology and Bioinformatics · June 4, 2025 Molecular docking is a critical process in drug discovery and design with various algorithms to predict how small molecules, or ligands, interact with proteins. The present study introduces a novel use of using Graph Neural Network (GNN) to build effective ... Full text Cite
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Education, Training & Certifications


Catholic University of Leuven (Belgium) · 2012 Ph.D.