Kiarash Soleimanzadeh

(pronounced 'kee-aw-rahsh solei-man-za-deh')

I am incredibly interested in machine/deep learning, computer vision, AI for medicine/healthcare, medical image/signal analysis, explainable (XAI), large language models, multimodal learning, natural language processing, and data analytics to improve quality of life.

I have several years of professional working experience specializing in the software industry at leading companies as a team leader, senior software engineer, and software architect, which gives me a strong engineering foundation for turning research ideas into working systems.

If I am not developing code, I am somewhere else, thinking about novel research ideas. Also, my free time is dedicated to playing tennis, hiking, camping, cooking, cycling, reading, swimming, and listening to music. These works are my daily schedules, so feel free to ask for anything related.

Please check out my blog, it is my pleasure.

Email  /  Bio  /  Google Scholar  /  Twitter  /  Github  /  Skype

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Education

Master's Degree
Information Technology Engineering (Ranked the first student based on GPA)

Bachelor's Degree
Software Engineering

Research

Representative sections/papers are highlighted.

Sub-Class-Aware and Prompt-Driven Weak Supervision for Medical Image Segmentation with Seg-menting Anything Model (SAM)
Kiarash Soleimanzadeh, Muharram Mansoorizadeh
In Progess, 2025

A novel weakly supervised medical image segmentation approach built on SAM to reduce labeling costs.

SD-WLB: An SDN-aided mechanism for web load balancing based on server statistics
Kiarash Soleimanzadeh, Mahmood Ahmadi, Mohammad Nassiri
ETRI Journal, 2019
bibtex  /  PDF

A smart method to balance requests/loads among servers in data centers.

This paper has been recognized as a top downloaded paper by Wiley.

Linear Albegra for AI
Kiarash Soleimanzadeh
2024

An ultimate guide to linear algebra for AI.


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