Dr. rer. nat. Hamza Aziz Ahmad Gardi
- postdoc / lecturer
- office hours:
by appointment
- room: 115
CS 06.35 - phone: +49 721 608-44519
- hamza gardi ∂does-not-exist.kit edu
Hertzstraße 16
Geb. 06.35
76187 Karlsruhe
| title | type | semester | place |
|---|---|---|---|
| Practical Machine Learning | Lecture / Practice (VÜ) | SS 2026 | Hybrid: - In-person attendance: Seminar Room 120.1, Building 06.35 - Online attendance: Live stream via Zoom |
| Quantum Machine Learning | lecture | winter semester | Hybrid: - In-person attendance: Seminar Room 120.1, Building 06.35 - Online attendance: Live stream via Zoom |
| Titel | Typ | Forschungsthema |
|---|---|---|
| Exploring the Power and Potential of Grover's Algorithm in Quantum Computing | MA | Quantum Computing, Implementation of quantum algorithms, Comparison of algorithms |
| Neural Ghost Imaging: Implicit Representations | MA | Ghost Imaging & Compressed Sensing, Implicit Neural Representations (INR), Physics-Informed Reconstruction, Quantum Optics (Two-Mode Squeezed Vacuum), Covariance-based learning |
| Reference-Calibrated Open-Vocabulary Anomaly Segmentation with Vision-Language Models | MA | Computer Vision; Machine Learning, Vision-Language Models, Industrial Anomaly Detection, Dense Prediction / Segmentation, Model Calibration and Reliability |
| Adaptive Frequency-Domain Supervision for Generative Image Reconstruction | MA | Image Processing; Computer Vision, Generative Models, Diffusion Models, Inverse Problems, Frequency-Domain Learning |
| Physics-Informed Neural Receivers for Quantum Illumination | MA | Quantum Machine Learning & Sensing, Physics-Informed Deep Learning, Signal Detection in low SNR regimes, Synthetic Data Generation from physical models, Covariance-based feature extraction |
| Safe Reinforcement Learning for Autonomous Quantum Calibration | MA | Safe Reinforcement Learning, Quantum Control (OPO Stabilization), Sim-to-Real Transfer strategies, Hybrid Control Systems, Robotics and Autonomous Calibration |
| Adapting Foundation Models (SAM) for Quantum Microscopy | MA | Foundation Models/Generative AI, Parameter-Efficient Fine-Tuning (PEFT), Quantum Phase Microscopy, Zero-Shot and Few-Shot Learning, Domain Adaptation (Natural to Physics images) |
| Camera-Uncertainty-Aware Metric Monocular Depth Estimation | MA | Computer Vision; 3D Vision, Monocular Depth Estimation, Robust Machine Learning, Camera Geometry, Metric Scene Understanding |
| Semantic Segmentation at the Shot-Noise Limit | MA | Computational Photography/Low-Light Vision, Quantum Imaging (Squeezed Light statistics), Semantic Segmentation & Edge Detection, Noise-aware Deep Learning, Synthetic Microscopy Data Generation |
| Closed-Loop Data Synthesis for Long-Tail Detection | MA | Generative AI for Computer Vision, Long-Tail Object Detection, Closed-Loop/Feedback-driven Learning (CNNs), Synthetic Data Generation, Uncertainty Estimation |
Auf Anfrage interessante Themen im Bereich Machine Learning möglich. |
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