Sepand AliMadadSoltani

Education

• Concentration: Medical Image Processing
• GPA: 15.31/20
• Courses: Magnetic Resonance Imaging (MRI), Segmentation & Registration, Artificial Intelligence in Medical Imaging, Image Reconstruction & Inverse Problems
• €10,000 Excellence Scholarship awarded for excellent academic background

• Concentration: Biomedical Engineering
• GPA: 16.33/20
• Courses: Statistical Pattern Recognition, Signals & Systems, C Programming, Engineering Math, Engineering Probability

Research Experience

• Developed non-invasive alternative to arterial sampling for PET quantification in 59 patients
• Built an accurate and automatic carotid artery segmentation pipeline on TOF-MR angiography images
• Implemented Bayesian inference model using Markov Chain Monte Carlo (MCMC) for Partial Volume Correction
• Reduced quantification bias significantly compared to standard image-derived methods (MAPE 13% vs 24%)
• Validated method using Monte Carlo PET simulations and cross-site collaboration with Paris-Saclay

• Built medical image analysis and visualization software in Python
• Implemented intelligent scissors algorithm for semi-automatic boundary detection on 2D image slices
• Integrated the algorithm into the app for fast tissue segmentation with minimal user input
• Incorporated complementary segmentation tools (polygon selection, thresholding, otsu filter)

Work Experience

• Developed custom QML components to render massive high-frequency datasets at 60 FPS without UI blocking.
• Designed a multi-threaded data acquisition backend to interface with PCIe hardware drivers.
• Implemented real-time digital signal processing (DSP) algorithms using Eigen and Boost
• Embedded a Python interpreter via pybind11 to execute ML inference on C++ data streams.

• Engineered a medical image visualization tool (PyQt, VTK, ITK) with thresholding, segmentation, and annotation capabilities.
• Created a dynamic node-based Qt UI to construct and execute image processing pipelines.
• Integrated AI algorithms into the processing pipeline in collaboration with the R\&D team.

Skills

• Programming: C++, Python, MATLAB, Bash
• Software and Tools: GNU/Linux, Git, FMRIB FSL, SPM, 3D Slicer, TPCCLIB
• Libraries: Tensorflow, PyTorch, NumPy, pandas, scikit-learn, Matplotlib, ITK, VTK, Boost, Qt
• Languages: English (C2), French (B2), Persian (Native)
• Standards IEC 62304, ISO 14971, ISO 13485

Conference Posters

Projects

• Implemented the network based on a paper using the Tensorflow library in Python
• Synthesized images of Persian text of different variety
• Applied data augmentation techniques such as rotating, translating, adding distortion, and adding noise to images
• Successfully trained the model for both languages using the self-made synthesized Persian dataset and public English datasets
• Achieved +85% accuracy for both languages

• Processed raw fMRI/MRI data from the ADNI database using FSL (motion correction, registration) to extract functional connectivity maps
• Evaluated RCNN and CNN models in Tensorflow for feature extraction to classify Alzheimer’s disease stages
• Identified critical limitations in using standard deep learning architectures for fMRI analysis

• Implemented brain extraction from structural reference MR image
• Implemented fMRI pre-processing including motion correction, slice timing correction, spatial smoothing, and co-registration
• Optimized the pipeline with parallel processing to accelerate computation on the ADNI dataset

• Developed a custom 2D graphics renderer completely from scratch using the OpenGL graphics API in C++
• Implemented user input handling, navigatable menus, and text rendering capabilities to the engine
• Designed and implemented the game of Tetris using the said engine in Object Oriented C++

• Programmed the geometric projection of a 4D hypercube onto 3D space to visualize higher-dimensional structures
• Achieved real-time rendering and interactive manipulation by wrapping VTK within a Qt GUI

• Derived the analytical magnetic field equations for a spherical solenoid
• Implemented numerical computations in MATLAB to calculate the field across multiple planes
• Designed an interactive GUI using MATLAB App Designer to visualize 3D heatmaps and vector plots