Hasan Kurban

Machine Learning in Materials Science Topic Modeling Advanced Clustering Algorithms Research Face and Expression Recognition ZnO doping and properties

Publications

Citations

517

Est. group size

—

Recurring co-author estimate

Active years

Publishing since 2014

Research summary

AI-generated

Hasan Kurban works at the intersection of machine learning and materials science, developing computational methods such as clustering algorithms, neural networks, and large language model techniques. Recent projects span physics-informed neural networks for solving equations, time-series forecasting (for example electricity load), anomaly detection in dynamic networks, and reliability of large language models. The work is largely methodological, applying artificial intelligence and data-analysis tools across scientific and engineering problems.

Machine learning for materials and physical systemsLarge language models and their reliabilityTime-series forecasting and anomaly detectionPhysics-informed and simulation-embedded neural networksClustering and data representation methods

Publication activity has grown sharply in recent years, rising from a few papers per year in 2017-2023 to over 30 in 2025.

Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026

Publication cadence

Publications per year over the last 10 years — averaging 12.4/year recently

Recent publications

Embedding Consistent Recurrent Neural Networks in Finite Element Simulations for Path-Dependent Damage Prediction
Zenodo (CERN European Organization for Nuclear Research) · 2026
Embedding Consistent Recurrent Neural Networks in Finite Element Simulations for Path-Dependent Damage Prediction
Zenodo (CERN European Organization for Nuclear Research) · 2026
Intrinsic 4D Gaussian Segmentation from Scene Cues
arXiv (Cornell University) · 2026
Lightweight Defense Against Data Consistency Attacks in Distributed DC Optimal Power Flow
IEEE Transactions on Automation Science and Engineering · 2026
Intrinsic 4D Gaussian Segmentation from Scene Cues
arXiv (Cornell University) · 2026
Topical Phase Transitions in Artificial Intelligence Research: Large-Scale Evidence and an Early-Warning Signature for Emerging Topics
arXiv (Cornell University) · 2026
Topical Phase Transitions in Artificial Intelligence Research: Large-Scale Evidence and an Early-Warning Signature for Emerging Topics
Zenodo (CERN European Organization for Nuclear Research) · 2026
Theorem-of-Thought: A Multi-Agent Framework for Abductive, Deductive, and Inductive Reasoning in Language Models
arXiv (Cornell University) · 2025
Audit-of-Understanding: Posterior-Constrained Inference for Mathematical Reasoning in Language Models
arXiv (Cornell University) · 2025
PhysicsNeRF: Physics-Guided 3D Reconstruction from Sparse Views
arXiv (Cornell University) · 2025
EMPATHIA: Multi-Faceted Human-AI Collaboration for Refugee Integration
arXiv (Cornell University) · 2025
Exploring Various Sequential Learning Methods for Deformation History Modeling
arXiv (Cornell University) · 2025
SAFE: A Sparse Autoencoder-Based Framework for Robust Query Enrichment and Hallucination Mitigation in LLMs
arXiv (Cornell University) · 2025
SAFE: A Sparse Autoencoder-Based Framework for Robust Query Enrichment and Hallucination Mitigation in LLMs
2025
Evaluating Multilingual and Code-Switched Alignment in LLMs via Synthetic Natural Language Inference
arXiv (Cornell University) · 2025

Publishes in

arXiv (Cornell University)×18
Zenodo (CERN European Organization for Nuclear Research)×5
Computational Materials Science×4
Scientific Reports×4
Machine Learning Science and Technology×3

This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 11, 2026.

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