About Me

I am Shayan Kebriti, a Computer Engineering undergraduate at Shahid Beheshti University in Tehran, Iran.
My research interests include Machine Learning, Computer Vision, Medical Image Computing, and Computational Modeling.
I am open to working on projects in these areas and I would love to contribute. I am also seeking Master’s or PhD opportunities.

Email: shayankebriti@gmail.com

Publications

Under Review ( Medical Image Analysis ) FractMorph figure

FractMorph: A Fractional Fourier-Based Multi-Domain Transformer for Deformable Image Registration

Shayan Kebriti1, Shahabedin Nabavi1 🎓 , Ali Gooya2,3 🎓

FractMorph is a novel 3D dual-parallel transformer for deformable image registration. Its Fractional Cross-Attention blends multi-scale spectral–spatial features via fractional Fourier transforms, achieving state-of-the-art results on intra-patient cardiac and atlas-to-patient cerebral MRI benchmarks.

1 Faculty of Computer Science and Engineering, Shahid Beheshti University, Tehran, Iran
2 School of Computing Science, University of Glasgow, Glasgow, UK
3 Alan Turing Institute, London, UK

Manuscript in Preparation Perfusion software overview

Design and Implementation of a Software for Measurement of Brain Perfusion Using an Optimized Model

This work is carried out under the supervision of Dr. Oghabian1,2 🎓 🔗, in collaboration with Dr. Mohammadi1,2 🎓 🔗, Dr. Irandoost1,2 🔗 and Dr. Zare1,2 🔗

Project Description

The NIAG perfusion software is developed for the quantitative analysis of brain perfusion MRI. It supports standard medical image formats, provides preprocessing tools such as motion correction, denoising, segmentation, and slice-time correction, and computes key DSC perfusion parameters (CBF, CBV, MTT, AUC). It also offers advanced visualization features like mirror-mode maps and customizable ROI definition for detailed regional assessment of cerebral hemodynamics. The software is intended for real clinical use in the most reputable hospitals in Iran, under the supervision of Tehran University of Medical Sciences.

My Contributions

My current contributions have focused on enhancing the software’s analytical pipeline, including the refinement of brain segmentation methods for complex tumor cases, improvements in preprocessing routines, and extension of manual ROI handling and visualization modules. I have also increased the quality and resolution of perfusion MRI images while ensuring precise metric calculations, and carried out the implementation and debugging of perfusion parameter calculations.

1 Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
2 Neuroimaging and Analysis Group, Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Equipment Institute, Tehran University of Medical Sciences, Tehran, Iran

Bachelor Thesis

In Progress Anatomical mesh generation framework

A Framework for Anatomical Mesh Reconstruction From Medical Images for In-Silico Simulations

This ongoing work aims to develop a novel deep learning framework for anatomical mesh generation from medical images without requiring manual annotations. The framework consists of an anatomical structure segmentation network, GNN-based mesh control-handles displacement prediction, and a final deformation stage. The generated meshes are designed for use in in-silico simulations for multiple modalities such as CT, MR, and US scans, enabling virtual experiments and computational modeling of anatomy for surgical planning, medical device testing, and further researches. More updates coming soon!

Projects

You can browse a categorized list of my open-source projects on my Github profile. Here is a selection of them:

demo

MedMesh: An easy to use, lightweight tool for converting medical images into 3D meshes

GitHub
demo

Multi-Asset Trading with TD3 RL Agent and Wavelet-Coherence Graph Neural Networks

GitHub
demo

Conditional Diffusion with Simple and Attention-Based U-Nets for CIFAR-10 Image Generation

GitHub
demo

HIV Inhibitors Classification with Multiple GNN Message Passing Methods

GitHub
demo gif

Rock–Paper–Scissors Automation with YOLOv11 and Cheat/Win Overlays

GitHub
demo

Variational Autoencoder (VAE) Analysis & Denoising GAN

GitHub
demo

Fashion Product Multilabel Classification & Image-to-Text Title Generation Using RNNs

GitHub
demo

Siamese Face Recognition Network Featuring A Graphical Web Interface

GitHub
demo

A puzzle-solving game implementing DFS, BFS, and A* search agents (designed as a TA assignment)

GitHub
demo

Image Compressing & Watermarking Using Spatial and Spectral (DCT, DFT and DWT) Methods

GitHub
demo

Classical Image Processing & Non Local Means (NLM) Filter CPU and GPU Implementations

GitHub
demo

My Deep Reinforcement Learning Assignments

GitHub
demo

My Machine Learning Assignments

GitHub

Education

Sep 2021 - Jan 2026
Bachelor, Computer Engineering, Shahid Beheshti Univeristy, Tehran, Iran
GPA: 3.86/4.00 Last two years: 4.00/4.00
Relevant 4/4 Courses: Computer Vision Machine Learning Deep RL (Graduate Course | My Seminar) Data Mining Artificial Intelligence Algorithms Design Data Structures Linear Algebra Probability & Statistics Signal & Systems Fundamentals of Robotics
Sep 2019 – Jan 2021
Diploma, Mathematics & Physics, National Organization for Development of Exceptional Talents (Sampad), Iran
GPA: 4.00/4.00 Ranked 1st in the school

Experience

For additional details about each experience, please see my CV or contact me.

CNCH Competition
Cognitive Neuroscience & AI Research Mentor
July 2025 - Now
Medical Image Computing Engineer & Researcher
Nov 2024 - Now
Shahid Beheshti University
Undergraduate Researcher
June 2024 - Now
Shahid Beheshti University
Teaching Assistant (14 Courses)
Sep 2022 - Now
Roshan AI
Machine Learning Engineer (Computer Vision and Trading Models)
Jul 2024 - Nov 2024
AI Research Intern (Deep Learning for Perspective Transformation)
Jun 2024 - Aug 2024
Collegiality UG (haftungsbeschränkt), Germany
Software Developer
Sep 2022 - Dec 2023

Endorsements

Here is what colleagues and supervisors have said about working with me:

Portrait of Shahabedin Nabavi

Shahabedin Nabavi, Ph.D. in Artificial Intelligence and Cognitive Computing

Shahid Beheshti University • Medical Image Analysis
“It is my pleasure to strongly recommend Mr. Shayan Kebriti, one of my undergraduate students, for his exceptional academic performance, research contributions, and outstanding personal qualities. I had the privilege of teaching Shayan in two courses: Computer Vision with Deep Learning, in which he achieved a perfect score of 20 out of 20, and Operating Systems Lab, where he ranked in the top 5% of the class. His performance in both courses demonstrated not only his deep understanding of the material but also his remarkable ability to apply theoretical concepts to practical challenges. Beyond coursework, Shayan worked under my supervision on a research project in deformable image registration, which is currently under review in a reputable journal. His contributions to this work were significant, showing creativity, strong problem-solving skills, and a clear passion for advancing the field of artificial intelligence and medical image computing. Shayan is a delighted, talented, and hardworking individual who consistently surprises me with his intellectual curiosity and eagerness to learn new concepts. He is particularly enthusiastic about exploring new developments in AI and medical imaging, a quality that makes him an ideal candidate for advanced research and professional growth. On a personal level, Shayan is polite, understanding, and highly reliable. His positive attitude, professionalism, and strong interpersonal skills make him a pleasure to work with, both in academic and research settings.
In summary, I have no doubt that Shayan will excel in any academic or professional environment he chooses to pursue. I wholeheartedly recommend him and am confident that he will make valuable contributions wherever he goes.”
Portrait of Mohammadreza, Mahdi, Mohammadi

Mahdi Mohammadi, Assistant Professor, Ph.D. in Medical Physics

Tehran University of Medical Sciences • NIAG
“I have known Shayan since 2024 and have worked with him on NIAG’s perfusion MRI toolkit. As a computer engineering student, he showed exceptional eagerness to master medical imaging with a strong focus on perfusion MRI and became productive very quickly. He is organized and meticulous, with sharp attention to detail. His reports are clear, thorough, and actionable. Shayan communicates effectively with clinicians, actively seeks feedback, and turns it into practical improvements. He brings strong image processing expertise, programming skills, and the ability to research imaging methods and adapt them to clinical applications. He applies this knowledge creatively to solve difficult cases while maintaining scientific rigor. He is always on time, consistent in his execution, and shows strong responsibility for his work. I recommend Shayan for roles in medical image computing and I am confident he will elevate any project or team he joins.”
Portrait of Amin Azirani

Amin Azirani, Solutions Engineer

cplace • Collegiality UG
Working with Shayan from 2022-2024 on our personalized guide creation app, I witnessed a software engineer who excelled at turning complex challenges into elegant solutions through creative problem-solving and systematic organization. His pre-AI era code showcased genuine innovation and craftsmanship, while his passionate advocacy for agile practices and thorough code reviews elevated our entire team's performance. Shayan's rare combination of technical creativity, structured execution, and unwavering reliability made him the engineer we trusted with our most critical features—any team would be fortunate to have him.”

Courses

CS224W: Machine Learning with Graphs
Stanford Online, March 2025
Topic: Graph Neural Networks
Perfusion MRI
Tehran University of Medical Sciences, Dec 2024
Topic: A PhD-level course taught by Dr. Mohammadi on DSC, DCE, and ASL perfusion MRI techniques.
How Diffusion Models Work
DeepLearning.AI, Dec 2024
A/B Testing in Python
365 Data Science, Aug 2024
Extreme Gradient Boosting with XGBoost
DataCamp, Aug 2024
MLOps Concepts
DataCamp, Aug 2024
ML mini-courses
Kaggle, Aug 2024
Topics: Pandas, Computer Vision, Time Series, Geospatial Analysis, Feature Engineering, Data Visualization, ...
Deep Learning Specialization (5 Courses)
DeepLearning.AI, May 2024
Scrum Foundations Workshop
Scrum Alliance, Dec 2023
Machine Learning Specialization (3 Courses)
DeepLearning.AI, Sep 2023
Python for Data Science, AI & Development
Coursera, Jul 2023

Hobbies

The motto I live by is “Carpe Diem”, which means “Seize the Day”.
I believe the most valuable asset we have is the present moment, which is why I consider myself adventurous in all aspects of life, from work to personal experiences. I almost never say no to new opportunities, experiences, or challenges.

In my free time, I love doing sports, going trekking in nature, and capturing photographs.
Here are some of my works:

In case you’re curious, you can explore more of my adventures and photography on Unsplash.