A. Çeçen

发表

Material structure-property linkages using three-dimensional convolutional neural networks

Yuksel C. Yabansu, Le Song, H. Dai, 2018 .

Structure–property linkages using a data science approach: Application to a non-metallic inclusion/steel composite system

Surya R. Kalidindi, Akash Gupta, Ahmet Cecen, 2015 .

Development of high throughput assays for establishing process-structure-property linkages in multiphase polycrystalline metals: Application to dual-phase steels

A. Çeçen, S. Kalidindi, A. Khosravani, 2017 .

3-D Microstructure Analysis of Fuel Cell Materials: Spatial Distributions of Tortuosity, Void Size and Diffusivity

Surya R. Kalidindi, Emin Caglan Kumbur, Ahmet Cecen, 2012 .

Exploration of data science techniques to predict fatigue strength of steel from composition and processing parameters

Parijat Deshpande, Ankit Agrawal, Alok Choudhary, 2014, Integrating Materials and Manufacturing Innovation.

Supplementary Material For Kdd2017: Efficient And Accurate Materials Structure-Property Linkages Using 3D Convolutional Neural Networks

Le Song, Surya R. Kalidindi, Hanjun Dai, 2017 .

Context and Space as the Tools to Legitimize and Produce Violence

A. Çeçen, 2021 .

Analytics on large microstructure datasets using two-point spatial correlations: Coarsening of dendritic structures

P. Voorhees, A. Çeçen, S. Kalidindi, 2017 .

Versatile algorithms for the computation of 2-point spatial correlations in quantifying material structure

Surya R. Kalidindi, Ahmet Cecen, Tony Fast, 2016, Integrating Materials and Manufacturing Innovation.

Some Chemical Characteristics of Butters Obtained from Van Market

A. Çeçen, S. Andiç, İ. Altun, 2011 .

A Generalized and Modular Framework for Digital Generation of Composite Microstructures

Surya R. Kalidindi, Ahmet Cecen, Berkay Yucel, 2021, Journal of Composites Science.

A new framework for rotationally invariant two-point spatial correlations in microstructure datasets

Surya R. Kalidindi, Ahmet Cecen, Yuksel C. Yabansu, 2018, Acta Materialia.

Exploration of data science techniques to predict fatigue strength of steel from composition and processing parameters

A. Choudhary, Ankit Agrawal, A. Çeçen, 2014, Integrating Materials and Manufacturing Innovation.

Discussing Facebook Algorithm and Ads in the Context of Political Manipulation and Negative Campaign

A. Çeçen, 2019, Advances in Marketing, Customer Relationship Management, and E-Services.

Process-Structure Linkages Using a Data Science Approach: Application to Simulated Additive Manufacturing Data

Xinyi Gong, Ahmet Cecen, Evdokia Popova, 2017, Integrating Materials and Manufacturing Innovation.

Application of Statistical and Machine Learning Techniques for Correlating Properties to Composition and Manufacturing Processes of Steels

Parijat Deshpande, Ankit Agrawal, Alok Choudhary, 2013, ICME 2013.

Selection of representative volume elements for pore-scale analysis of transport in fuel cell materials

Surya R. Kalidindi, Emin Caglan Kumbur, Ahmet Cecen, 2012 .

Resolving macro- and micro-porous layer interaction in polymer electrolyte fuel cells using focused ion beam and X-ray computed tomography

E. A. Wargo, V. Schulz, A. Çeçen, 2013 .

Role of materials data science and informatics in accelerated materials innovation

Surya R. Kalidindi, Ahmet Cecen, Aleksandr Blekh, 2016 .

A data-driven approach to establishing microstructure–property relationships in porous transport layers of polymer electrolyte fuel cells

Surya R. Kalidindi, Emin Caglan Kumbur, Ahmet Cecen, 2014 .

Calculation, utilization, and inference of spatial statistics in practical spatio-temporal data

A. Çeçen, 2017 .