My research and teaching interests include machine learning (ML), data mining, big data, data science and artificial intelligence (AI). I theoretically work on data-centric ML/AL and also build ML systems over various domains such as material science , chemistry, bioinformatics, to help accelerate scientific discoveries. For example, we use ML to develop long standing traditional quantum modeling techniques, particularly Density-functional theory (DFT), a computational method developed in the 1970s, for modelling quantum mechanics that is among the most popular tools of the material scientists.
Ph.D., Computer Science, Sep 2017
Indiana University Bloomington, IN, USA
M.Sc., Computer Science, May 2012
Indiana University Bloomington, IN, USA
EAP, July 2010
University of Connecticut, CT, USA
EAP, June 2009
Marmara University, Istanbul, Turkey
B.Sc., Mathematics, June 2008
Inonu University, Malatya, Turkey
FEATURED PUBLICATIONS
Applying Data-Centric AI to Improve a Single-cell RNA-seq Pipeline
A paired index structure for k-Nearest Neighbor Search Algorithms
An Efficient and Novel Approach for Predicting Kohn-Sham Total Energy–Bootstrapping a Cooperative Model Framework with Minimal Viable Theoretical Data
ccImpute–an accurate and scalable consensus clustering based algorithm to impute dropout events in the single-cell RNA-seq data
Regeneration of Lithium-ion Battery Impedance using a Novel Machine Learning Framework and Minimal Empirical Data
Data Expressiveness and Its Use in Data-centric AI
CH3NH3PbI3 Perovskite Nanoparticles
Rare-class Learning over Mg-Doped ZnO Nanoparticles
Predicting Atom Types in Different Temperatures
Hospital Appointment System
Data Science
DFTB calculations
Data Clustering with EM (DCEM) for Big Data, an R package
Density-functional tight-binding approach for the structural analysis and electronic structure of copper hydride metallic nanoparticles
Using Data Analytics to Optimize Public Transportation on a College Campus
A Novel Approach to Optimization of Iterative Machine Learning Algorithms
An Expectation Maximization Algorithm for Big Data
EMPLOYING SOFTWARE ENGINEERING PRINCIPLES TO CLIMATOLOGICAL DATASETS
Reduced random forest for big data using priority voting & dynamic data reduction
Studying the milky way galaxy using paraheap-k