Doctoral Candidates / Projects

Our approx. 50 doctoral candidates are at the heart of our graduate school. Get to know our doctoral candidates on their profiles below and learn more about their research projects. 

Additionally, the GSB Graduate Council is the voice of our doctoral candidates in academic administrative matters for the Graduate School of BioEngineering (GSB) at the Technical University Munich. We are the channel through which doctoral candidates concerns are brought to the attention of the project leaders, mentors and administrative staff of the GSB. 

It is essential that we hear the concerns of the doctoral candidates within the GSB, and we welcome any of your suggestions, comments or complaints!

Our current doctoral students representatives are Amal Lahiani and John LaMaster. 
The Graduate School of BioEngineering (GSB) provides a highly stimulating environment for doctoral research. Our graduate centre attracts outstanding candidates from a variety of academic backgrounds. At the moment, the doctoral candidates are working on the following topics:


Afshari, Parastoo

Development of hybrid optical resolution optoacoustic, ultrasound and Life-time/Auto fluorescent imaging for early detection and staging of the esophagus cancer

Ali, Zakiullah

Development of a hybrid OCT/MSOT endoscope based on rotational illumination and detection operation 

Basak Chowhury, Kaushik

Modeling transducer properties for optoacoustic image reconstruction 

Bild, Raffael

Differentially Private Processing of Biomedical Data

Busam, Benjamin

Multi-Modal Pose Computation and Sensor Fusion for High Performance 3D Vision Systems 

Coello, Eduardo

Accelerated Magnetic Resonance Spectroscopic Imaging

Cömert, Suat

Mechanisms for a Continuum-Robot Type Motion of a Catheter or Guidewire

Das, Dhritiman

Next-generation compressed sensing techniques for a fast- and data- driven reconstruction of multi-contrast MRI 

de la Rosa, Ezequiel

Rapid detection of the extent of ischemic stroke on clinical CT images



Dionisio Parra, Beatriz

MR Imaging of the brain: Quantitative white matter metrics to study neurodegenerative disorders

Duliu, Alexandru 

3D muitispectrai reconstruction and visuahzation for skin cancer detection

Eisawy, Rami

Unsupervised anomaly detection for clinical imaging

El-Rewaidy, Hossam

Image Reconstruction Methods for Magnetic Resonance Imaging

Endt, Sebastian 

Fast acquisition of multi parametric physiological maps via MR imaging of the brain 

Esposito, Marco

Collaborative Robotic Imaging

Feldotto, Benedikt

Biomimetic Learning with a Neurorobotic Infant Model 

Göbl, Rüdiger

Advanced ultrasound processing in neurosurgery

Golkov, Vladimir

Variational methods and deep learning for high-dimensional and non- Euclidean medical data 

Gutjahr, Ralf

Predevelopment of Multi-Energy Algorithms for Photon Counting Computed Tomography 

Hafalir, Fatih

Phase Contrast MRI for the Application of Cardiovascular Flow Measurement

Hariharan, Sai Gokul

Enhancement of Biomedical Images

Hehn, Nicolas

Development and Evaluation of an MRI spatial distortion correction tool for the PRONIA prognostic prototype 

Jang, Jihye

Cardiovascar MR imaging of scar and diffuse fibrosis in patients with ventricular arrhythmia 

Kaushik, Sandeep

Deep Learning Based Image Processing in the Context of MR-Only Radiation Therapy

Kubala, Eugen

13C Metabolic Magnetic Resonance Imaging with Hyperpolarized 13C- labelled Metabolics 

La, Tai Anh

Development of Optical Ultrasound Sensor for Optoacoustic Imaging 

Lahiani, Amal

Enabling medical diagnosis in oncology using deep learning methods from digital pathology

LaMaster, John

Assessment of Brain Tumors via Radiogenomic Analysis of Multiparametric MR Images using Deep Learning Methods 

Lingg, Jakob

Three-Dimensional Microscope for Studying Blood Flow in vivo

Liu, Shufang

Modeling of Cardiac Motion Patterns by Reconstruction of Temporal Dynamic Deformation Sequences

Liu, Xin

Development of Silent Diffusion MR Acquisition Schemes with Reduced Distortion

Löb, Rebekka

Resolution modeling and anatomically regularized parametric reconstruction for simultaneous PET/MR data

Malekzadeh, Jaber

Development of Combined Ultrasound-Optoacoustic Endoscope and External Probe for Clinical Applications

Muhammad, Marwan

Investigation of Hyprid Ultrasound - Optoacoustic Imaging

Ostler, Daniel

Advanced Sensing and Computation for Computer-assisted Surgery

Paetzold, Johannes

Whole brain vasculature analysis using advanced learning models

Salehi, Mehrdad

Advanced Medical Ultrasound Imaging 

Sandurkov, Bojan

High Frequency Monophasic Transcranial Magnetic Stimulation of the Human Motor Cortex in a Closed Loop Setting

Schultheiß, Manuel

Machine Learning and Convolutional Networks Applied on Biomedical CT Data

Sekuboyina, Anjany Kumar

iBack: Individualized treatment planning in chronic back pain patients by advanced imaging and multi-parametric biomechanical models 

Shah, Amitkumar

Tracking and Navigation in Intra-operative Imaging 

Shit, Suprosanna

Physics aware deep learning and its application in medical image analysis

Spengler, Helmut

Anonymisierung biomedizinischer Daten mittels statistischer Methoden 

Stefan, Philipp

Multidisciplinary Team OR Simulation: Training, Assessment, Technology Evaluation

Tetteh, Giles

Analyzing Vascular Networks extracted from clinical Magnetic Resonance Angiographic Images 

Ülgen, Okan

Optical Detectors of Ultrasound for Endoscopy Applications

Ulas, Cagdas

Advanced Reconstruction Techniques for Perfusion MR Imaging

Vivar, Gerome

Deep Learning and Big Data Mining of Multimodal Imaging and Spatio-Temporal Sensor Data in Vestibular and Balance Disorders

Walter, Florian

Brain-Derived Modular Neural Networks 

Weiss, Jakob

Real-Time Processing and Visualization of Live OCT Data for Augmented Reality Ophthalmology

Wolf, Johannes

Modelling of X-Ray Phase-Contrast Mammography 

Wu, Mingming

MR Thermometry Applications of MR Image Guided Therapy 

Zimmermann, Judith

Quantitative image analysis of velocity encoded flow magnetic resonance Imaging in patients with congenital heart defects