Hasan Kurban

Hasan Kurban

Computer & Data Scientist

About me

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.

Interests

  • Data Science, Data Mining, Machine Learning, Big Data

Education

  • Ph.D., Computer Science, Sep 2017

    Indiana University Bloomington, IN, USA

Projects

FEATURED PUBLICATIONS

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Applying Data-Centric AI to Improve a Single-cell RNA-seq Pipeline

Applying Data-Centric AI to Improve a Single-cell RNA-seq Pipeline

Applying Data-Centric AI to Improve a Single-cell RNA-seq Pipeline

A paired index structure for k-Nearest Neighbor Search Algorithms

A paired index structure for k-Nearest Neighbor Search Algorithms

A paired index structure for k-Nearest Neighbor Search Algorithms

Cooperative Model Framework with Minimal Viable Theoretical Data

Cooperative Model Framework with Minimal Viable Theoretical Data

An Efficient and Novel Approach for Predicting Kohn-Sham Total Energy–Bootstrapping a Cooperative Model Framework with Minimal Viable Theoretical Data

ccImpute algorithm to impute dropout events in the single-cell RNA-seq data

ccImpute algorithm to impute dropout events in the single-cell RNA-seq 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

Regeneration of Lithium-ion Battery Impedance

Regeneration of Lithium-ion Battery Impedance using a Novel Machine Learning Framework and Minimal Empirical Data

Data-centric AI

Data-centric AI

Data Expressiveness and Its Use in Data-centric AI

Machine Learning Systems for Multi-Atoms Structures

Machine Learning Systems for Multi-Atoms Structures

CH3NH3PbI3 Perovskite Nanoparticles

Rare-class Learning

Rare-class Learning

Rare-class Learning over Mg-Doped ZnO Nanoparticles

Atom Type Prediction

Atom Type Prediction

Predicting Atom Types in Different Temperatures

R Package

R Package

Data Clustering with EM (DCEM) for Big Data, an R package

Structural Analysis

Structural Analysis

Density-functional tight-binding approach for the structural analysis and electronic structure of copper hydride metallic nanoparticles

Public Transportation Optimization

Public Transportation Optimization

Using Data Analytics to Optimize Public Transportation on a College Campus

Iterative Machine Learning

Iterative Machine Learning

A Novel Approach to Optimization of Iterative Machine Learning Algorithms

Clustering Big Data

Clustering Big Data

An Expectation Maximization Algorithm for Big Data

Coral Reef Analysis

Coral Reef Analysis

EMPLOYING SOFTWARE ENGINEERING PRINCIPLES TO CLIMATOLOGICAL DATASETS

Random Forest

Random Forest

Reduced random forest for big data using priority voting & dynamic data reduction

Studying the Milky Way

Studying the Milky Way

Studying the milky way galaxy using paraheap-k

Contact

  • 700 N Woodlawn Ave, Bloomington, IN 47408