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

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.
	Vision-Based Deep-Learning System For The Automated Inspection Of Packaging And Labeling Quality On High-Speed Food Production Lines Kiarash Soleimanzadeh 2026 A vision-based image analysis system for automated inspection of food packaging in high-speed pro-duction lines by combining image processing and deep learning methods, including CNN-based defect detection, OCR for product and expiration verification, and barcode quality assessment.
	IntelliBib: A Context-Aware Citation Recommendation System For LaTeX Academic Writing On Overleaf Kiarash Soleimanzadeh 2024 An innovative NLP-powered tool designed to enhance academic writing on the popular Overleaf plat-form. It analyzes the user’s current writing context to recommend the most relevant references to cite. The system features an intelligent citation recommendation engine that learns from both past and ongoing LaTeX projects, adapting to the user’s domain expertise and citation style over time.
	Linear Albegra for AI Kiarash Soleimanzadeh 2024 An ultimate guide to linear algebra for AI.

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