Cem Nurlu
Quantum Physics • Machine Learning • Nanofabrication
About Me
I'm a Master's student in Applied Physics at TU Delft, specializing in Physics for Quantum Devices and Quantum Computing. My research focuses on semiconductor-superconductor hybrid structures for topologically protected Majorana qubits at QuTech's Kouwenhoven Lab.
With a background in computational physics from Bogazici University and experience in machine learning for earthquake detection, I bridge theoretical physics with practical applications in quantum computing and AI.
My Journey
Research
Quantum Computing
My research focuses on semiconductor-superconductor hybrid structures for topologically protected Majorana qubits. These exotic quasiparticles offer a promising platform for fault-tolerant quantum computing.
Hover over gates to see details or click "Run Circuit" to animate
Machine Learning
I've applied machine learning techniques to analyze seismic data for earthquake detection and prediction. My work combines signal processing with deep learning to identify patterns in complex time-series data.
Featured Projects
Quantum Finite Automata on NISQ Devices
Implemented and analyzed quantum finite automata algorithms on noisy intermediate-scale quantum computers, demonstrating potential advantages in language recognition tasks despite hardware limitations.
ML-Enhanced Seismic Data Analysis
Developed a machine learning pipeline for processing and analyzing seismic waveform data, improving earthquake detection accuracy by 27% compared to traditional methods.
Teaching
QTurkey Workshops
As a co-founder of QTurkey, I've led numerous workshops introducing quantum computing concepts to students and professionals. These hands-on sessions cover quantum gates, algorithms, and practical implementations using Qiskit.
200+ Students
Trained across multiple institutions
QWorld Bronze
I've served as an instructor for QWorld's Bronze program, a comprehensive introduction to quantum computing and quantum algorithms designed for undergraduate students with programming experience.
5 Workshops
Delivered in international settings
Teaching Philosophy
I believe in making complex quantum concepts accessible through visual explanations and hands-on exercises. My teaching approach combines theoretical foundations with practical applications to help students build intuition for quantum phenomena.
By connecting quantum computing to By connecting quantum computing to real-world problems, I help students understand not just how quantum algorithms work, but why they matter and where they can provide computational advantages.
Teaching Materials
- Quantum Computing Fundamentals
- Qiskit Programming Tutorials
- Quantum Algorithms Workshop
- Quantum Hardware Overview
Publications
Quantum Finite Automata on NISQ Devices
Journal of Quantum Information Processing, 2023
This paper explores the implementation of quantum finite automata on noisy intermediate-scale quantum computers, analyzing their performance and error resilience compared to classical counterparts.
Machine Learning Approaches for Seismic Data Analysis
Conference on AI in Geophysics, 2022
This conference paper presents a novel deep learning architecture for processing seismic waveform data, demonstrating improved accuracy in earthquake detection and classification.
Contact
Get In Touch
I'm always open to discussing research collaborations, teaching opportunities, or interesting projects in quantum computing and machine learning.