Publications

Madhavan Kalkunte Ramachandra, Hasan Kurban, M. Oguzhan Kulekci, Mehmet Dalkilic (2022). k-NN-p: A paired index structure for k-Nearest Neighbor Search Algorithms over High Dimensional Data and Large Data Sets. Information Sciences (under-review).

Hasan Kurban, Mustafa Kurban, Mehmet M. Dalkilic (2022). Rapidly Predicting Kohn-Sham Total Energy Using Data-centric AI. Nature Scientific Reports.

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Selcuk Temiz, Hasan Kurban, Salim Erol, Mehmet M. Dalkilic (2022). Regeneration of Lithium-ion Battery Impedance using a Novel Machine Learning Framework and Minimal Empirical Data. Journal of Energy Storage.

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Marcin Malec, Hasan Kurban, Mehmet M. Dalkilic (2022). ccImpute--an accurate and scalable consensus clustering based algorithm to impute dropout events in the single-cell RNA-seq data. BMC Bioinformatics.

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Parichit Sharma, Marcin Malec, Hasan Kurban, M. Oguzhan Kulekci, Mehmet Dalkilic (2022). Applying Data-Centric AI to Improve a Single-cell RNA-seq Pipeline. In IEEE International Conference on Data Mining (ICDM) (under-review).

Selcuk Temiz, Salim Erol, Hasan Kurban, Mehmet M. Dalkilic (2022). State of Charge and Temperature-Dependent Impedance Spectra Regeneration of Lithium-ion Battery by Duplex Learning Modeling. Journal of Energy Storage (under-review).

Selcuk Temiz, Hasan Kurban, Salim Erol, Mehmet M. Dalkilic (2022). Data on Machine Learning regenerated Lithium-ion battery impedance. Data in Brief (under-review).

Parichit Sharma, Hasan Kurban, Mehmet M Dalkilic (2022). DCEM: An R package for clustering big data via data-centric modification of Expectation Maximization. SoftwareX.

Hasan Kurban, Parichit Sharma, Mehmet Dalkilic (2021). Data Expressiveness and Its Use in Data-centric AI. In NeurIPS Data-Centric AI, DCAI'21.

Hasan Kurban, Mustafa Kurban (2021). Building Machine Learning Systems for Multi-Atoms Structures: CH3NH3PbI3 Perovskite Nanoparticles. Computational Materials Science.

Hasan Kurban (2021). Atom Classification with Machine Learning and Correlations among Physical Properties of ZnO Nanoparticle. Chemical Physics.

Hasan Kurban, Mustafa Kurban (2021). Rare-class Learning over Mg-Doped ZnO Nanoparticles. Chemical Physics.

Hasan Kurban, Sholeh Alaei, Mustafa Kurban (2021). Effect of Mg content on electronic structure, optical and structural properties of amorphous ZnO nanoparticles: A DFTB study. Journal of Non-Crystalline Solids.

Iskender Muz, Hasan Kurban, Mustafa Kurban (2021). A DFT Study on Stability and Electronic Structure of AlN Nanotubes . Materials Today Communications.

Hasan Kurban, Mustafa Kurban, Parichit Sharma, Mehmet Dalkilic (2021). Predicting Atom Types of Anatase TiO2 Nanoparticles with Machine Learning. Key Engineering Materials.

Hasan Kurban (2021). Measuring the Proximity of Medical Treatment Areas with Text Mining. European Journal of Science and Technology.

Hasan Kurban (2020). Practical Data Science: Examining the Correlations between Structural and Electronic Properties of Different Phases of TiO2 Nanoparticles. In Journal of Selcuk-Technic.

Hasan Kurban, Mehmet Dalkilic, Selcuk Temiz, Mustafa Kurban (2020). Tailoring the structural properties and electronic structure of anatase, brookite and rutile phase TiO2 nanoparticles: DFTB calculations. Computational Materials Science.

Hasan Kurban, Mustafa Kurban (2019). Study of Structural and Optoelectronic Properties of Hexagonal ZnO Nanoparticles. In Bilecik Seyh Edebali University Journal of Science.

Mustafa Kurban, Hasan Kurban, Mehmet Dalkilic (2019). Controlling structural and electronic properties of ZnO NPs: Density-functional tight-binding method. Bilge International Journal of Science and Technology Research.

Hasan Kurban, Mustafa Kurban, Mehmet Dalkilic (2019). Size Dependent Electronic Structure and Structural Properties of Cupric Oxide (CuO) NanoParticles. International Natural Science, Engineering and Material Technologies Conference.

Hasan Kurban, Mustafa Kurban, Mehmet Dalkilic (2019). Density-functional tight-binding approach for the structural analysis and electronic structure of copper hydride metallic nanoparticles. Materials Today Communications.

Kurt Zimmer, Hasan Kurban, Mark Jenne, Logan Keating, Perry Maull, Mehmet Dalkilic (2018). Using data analytics to optimize public transportation on a college campus. In IEEE international conference on data science and advanced analytics (DSAA).

Hasan Kurban, Mehmet Dalkilic (2017). A novel approach to optimization of iterative machine learning algorithms: Over heap structure. In IEEE International Conference on Big Data (Big Data).

Hasan Kurban, Can Kockan, Mark Jenne, Mehmet Dalkilic (2017). Improving expectation maximization algorithm over stellar data. In IEEE International Conference on Big Data (Big Data).

Hasan Kurban, Can Kockan, Mark Jenne, Mehmet Dalkilic (2017). Case Study: Clustering Big Stellar Data with EM. In IEEE/ACM International Conference on Big Data Computing, Applications and Technologies.

Hasan Kurban (2017). A NOVEL APPROACH TO OPTIMIZATION OF ITERATIVE MACHINE LEARNING ALGORITHMS: OVER HEAP STRUCTURE. Indiana University, ProQuest Dissertations Publishing.

Hasan Kurban, Mark Jenne, Mehmet Dalkilic (2017). Using data to build a better EM: EM* for big data. International Journal of Data Science and Analytics.

Hasan Kurban, Mark Jenne, Mehmet Dalkilic (2016). Em*: An em algorithm for big data. In The IEEE International Conference on Data Science and Advanced Analytics (DSAA).

Mark Jenne, Alex Zimmerman, Hasan Kurban, Claudia Johnson, Mehmet Dalkilic (2016). EMPLOYING SOFTWARE ENGINEERING PRINCIPLES TO ENHANCE MANAGEMENT OF CLIMATOLOGICAL DATASETS FOR CORAL REEF ANALYSIS. In The International Workshop on Climate Informatics (CI).

Hussein Mohsen, Hasan Kurban, Kurt Zimmer, Mark Jenne, Mehmet Dalkilic (2015). Red-RF: Reduced random forest for big data using priority voting & dynamic data reduction. In IEEE International Congress on Big Data (IEEE BigData).

Hussein Mohsen, Hasan Kurban, Mark Jenne, Mehmet Dalkilic (2014). A new set of Random Forests with varying dynamic data reduction and voting techniques. In The IEEE International Conference on Data Science and Advanced Analytics (DSAA).

Mark Jenne, Owen Boberg, Hasan Kurban, Mehmet Dalkilic (2014). Studying the milky way galaxy using paraheap-k. IEEE Computer.