Reza Karimzadeh

Computer Scientist

Professional Summary

Machine learning engineer and PhD in Computer Science with industry experience in computer vision. Strong background in Python, PyTorch, medical image analysis, and statistical analysis with experience building data pipelines, developing, validating, and deploying models. Worked with complex clinical datasets and collaborated across universities and hospitals to translate domain expertise into practical modeling tasks. Seeking to bring rigorous experimentation and hands-on development to ML products that solve real-world problems.

If you are interested, please reach out to collaborate 😃

Outside of research, I enjoy solving puzzles, exploring new technologies, and studying psychology and human behavior. Currently, I am reading evolutionary biology (mostly Richard Dawkins books) out of curiosity about complex adaptive systems and the evolution behind them.

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Education

PhD Computer Science

Copenhagen University

MS in Biomedical Engineering

Sharif University of Technology

BS in Biomedical Engineering

Amirkabir University of Technology

Interests

Image Segmentation Medical Data Analysis Explainable AI Self-Supervised Learning Object Detection Domain Adaptation Image Processing Deep Learning Machine Learning Computer Vision

Experience

PhD Researcher | Machine Learning Engineer
University of Copenhagen, Department of Computer Science May 2023 – August 2026
Built imaging and clinical data pipelines for pancreatic cancer survival prediction (1,531 patients). Developed self-supervised learning methods for 3D medical image segmentation. Designed explainable AI methods for visual attribution and missing clinical feature reconstruction. Led university–hospital collaborations on survival estimation and treatment response modeling.
Machine Learning Intern | Research Intern
Amsterdam UMC | VU Amsterdam January 2026 – April 2026
Developed and validated a Siamese deep learning model to predict cancer treatment response from pre- and post-treatment CT scans (n=502). Built an end-to-end training and cross-validation pipeline using PyTorch and MONAI, collaborating closely with oncologists and radiologists to ensure clinical relevance and interpretability. Led a cross-institutional university–hospital project.
Machine Learning Intern | Research Intern
Geneva University Hospital September 2025 – January 2026
Built a multi-center deep learning system to predict cancer subtype from PET scans using set-based modeling (Transformers, Deep Sets, MIL, GNN). Achieved ROC-AUC up to 0.91 in cross-validation and improved external performance from 0.81 to 0.87 via test-time adaptation (entropy minimization). Led a fully remote university–hospital collaboration.
Deep Learning Engineer
PART Artificial Intelligence Startup October 2022 – January 2023
Developed and deployed YOLO-based object detection models for license plate detection and signature localization, achieving mAP0.5 of 0.97 and 0.94 respectively. Optimized robustness under varying lighting and quality conditions. Containerized and deployed models using Docker with real-time inference APIs in production.
Technical Lead | Computer Vision & Signal Processing Engineer
Iran’s National Elites Foundation September 2020 – September 2021
Led the computer vision group in developing a non-contact heart rate estimation system from RGB video (3.02 MAE). Designed signal processing pipelines including ROI tracking, temporal filtering, and amplitude normalization. Coordinated deployment on mobile and embedded platforms for real-time inference.
Engineering Intern
Electro-Xray Company July 2017 – September 2017
Performed repair and maintenance of medical imaging systems including CT scanners, portable radiology devices, C-Arm systems, mammography units, and OPG systems.
Teaching Assistant
Copenhagen University | Sharif University of Technology | Amirkabir University of Technology Present
Teaching assistant for courses in Deep Learning, Numerical Methods, Medical Image Analysis and Processing, Image Processing, and Medical Imaging Systems.

Education

PhD Computer Science
Copenhagen University May 2023 – August 2026
Transforming Pancreatic Cancer Data into Clinically Useful AI Representations
MS in Biomedical Engineering
Sharif University of Technology September 2019 – May 2022
Worked on Medical Image Segmentation Using Deep Learning Methods
Read Thesis (Persian)
BS in Biomedical Engineering
Amirkabir University of Technology September 2014 – September 2019
Design and implementation of brain surgery bipolar electrocoagulation simulator using haptic technology.
Read Thesis (Persian)

Featured Publications

Machine Learning

Explanation-Guided Reconstruction of Missing Clinical Features for Survival Prediction in Pancreatic Cancer

Explanation-guided framework for reconstructing missing multimodal clinical features while preserving information relevant to pancreatic cancer survival prediction.

Reza Karimzadeh

• Jul 1, 2026 • 1 min read

Medical Imaging

Revisiting Multi-Nodal Radiomics with Advanced Feature Learning for Lymphoma Classification: A Multi-Center Study

Multi-center PET radiomics framework using set-based feature learning and test-time adaptation for patient-level Hodgkin versus non-Hodgkin lymphoma classification.

Reza Karimzadeh

• Jun 23, 2026 • 1 min read

Computer Vision

Extremal Contours: Gradient-driven contours for compact visual attribution

Training-free method that uses gradient-driven smooth contours for compact visual attribution.

Reza Karimzadeh

• Nov 3, 2025 • 1 min read

Medical Image Segmentation

PiMPiC: An Overlap-Aware Contrastive Learning Framework for 3D Patch-Based Medical Image Segmentation

Contrastive learning framework with overlap-aware modules for improved 3D medical image segmentation.

Reza Karimzadeh

• Oct 12, 2025 • 1 min read

Recent Publications

Reza Karimzadeh, Sophie Kollbeck, Erik Gudmann Steuble Brandt, Michael Brun Andersen, Christoph Felix Muller, Anders Bertil Rodell, Martin Sillesen, Bulat Ibragimov (2026). Explanation-Guided Reconstruction of Missing Clinical Features for Survival Prediction in Pancreatic Cancer. IEEE JBHI.

DOI Source Document

Reza Karimzadeh, Setareh Hasanabadi, Maryam Cheraghi, Mehrdad Bakhshayesh Karam, Hossein Arabi, Bulat Ibragimov (2026). Revisiting Multi-Nodal Radiomics with Advanced Feature Learning for Lymphoma Classification: A Multi-Center Study. Physics in Medicine & Biology.

DOI Source Document Code

Reza Karimzadeh, Albert Alonso, Frans Zdyb, Julius B. Kirkegaard, Bulat Ibragimov (2025). Extremal Contours: Gradient-driven contours for compact visual attribution. NLDL 2026.

Preprint DOI Source Document

Reza Karimzadeh, Ehsan Yousefzadeh-Asl-Miandoab, Hossein Arabi, Pinar Tözün, Bulat Ibragimov (2025). PiMPiC: An Overlap-Aware Contrastive Learning Framework for 3D Patch-Based Medical Image Segmentation. DEMI 2025.

DOI Source Document Code

Ehsan Yousefzadeh-Asl-Miandoab, Reza Karimzadeh, Bulat Ibragimov, Florina M. Ciorba, Pinar Tözün (2025). CARMA: Collocation-Aware Resource Manager with GPU Memory Estimator. arXiv:2508.19073.

Preprint DOI Source Document

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