Hello! I'm Mohammad Akbari Monfared, a data scientist and software enthusiast based in Köln, Germany. I enjoy turning messy industrial data into actionable insights and building AI-powered solutions that improve processes and decision-making. I'm currently pursuing a Master of Computer Science at the University of Bonn, combining hands-on programming with research in AI, particularly focusing on explainability and collaboration with cross-functional teams. I love communicating complex results to both technical and non-technical stakeholders, and I continuously learn new tools to solve real-world problems.

Mohammad Akbari Monfared

Hello! I'm Mohammad Akbari Monfared, a data scientist and software enthusiast based in Köln, Germany. I enjoy turning messy industrial data into actionable insights and building AI-powered solutions that improve processes and decision-making. I'm currently pursuing a Master of Computer Science at the University of Bonn, combining hands-on programming with research in AI, particularly focusing on explainability and collaboration with cross-functional teams. I love communicating complex results to both technical and non-technical stakeholders, and I continuously learn new tools to solve real-world problems.

Available to hire

Hello! I’m Mohammad Akbari Monfared, a data scientist and software enthusiast based in Köln, Germany. I enjoy turning messy industrial data into actionable insights and building AI-powered solutions that improve processes and decision-making.

I’m currently pursuing a Master of Computer Science at the University of Bonn, combining hands-on programming with research in AI, particularly focusing on explainability and collaboration with cross-functional teams. I love communicating complex results to both technical and non-technical stakeholders, and I continuously learn new tools to solve real-world problems.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
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Language

English
Fluent
German
Beginner
Persian
Fluent

Work Experience

Data Science working student at SMS Group GmbH
August 1, 2025 - September 8, 2025
Prepared raw industrial data through extensive cleaning, merging, and transformation for advanced analytics and forecasting. Designed algorithms to identify key production phases, incorporating explainable AI for transparency and stakeholder alignment. Contributed to architecture design, including batch processing, integration, and dashboards. Developed custom models for process optimisation, outperforming baselines by 30%. Collaborated with technical and management teams over two years, increasing overall productivity by 2%.
Student researcher at CAISA Lab, University of Bonn
August 1, 2025 - September 8, 2025
Developed the first agentic data augmentation framework for ABSA for Masters Thesis combining LLM-based generation and agentic reasoning. Closed the performance gap between lightweight models and state-of-the-art systems through high quality label consistent synthetic data. Designed systematic experimentation framework, to analyse factors such as task complexity, tuning strategies, data ratios. Delivered evidence that agentic system outperforms naive prompting by around 6% F1 and enables competitive results with real benchmark datasets in low resource settings.
Data Science Working Student at SMS Group GmbH
August 1, 2025 - September 8, 2025
Prepared raw industrial data through extensive cleaning, merging, and transformation for advanced analytics and forecasting. Designed algorithms to identify key production phases, incorporating explainable AI for transparency and stakeholder alignment. Contributed to architecture design, including batch processing, integration, and dashboards. Developed custom models for process optimisation, outperforming baselines by 30%. Collaborated with technical and management teams over two years, increasing overall productivity by 2%.
Student Researcher at CAISA Lab, University of Bonn
August 1, 2025 - September 8, 2025
Developed the first agentic data augmentation framework for ABSA for Masters Thesis combining LLM-based generation and agentic reasoning. Closed the performance gap between lightweight models and state-of-the-art systems through high quality label consistent synthetic data. Designed systematic experimentation framework, to analyse factors such as task complexity, tuning strategies, data ratios. Delivered evidence that agentic system outperforms naive prompting by around 6% F1 and enables competitive results with real benchmark datasets in low resource settings.

Education

Master of Computer Science at University of Bonn
January 1, 2021 - January 1, 2025
Bachelor of Computer Science at Sharif University of Technology
January 1, 2013 - January 1, 2019
Master of Computer Science at University of Bonn
January 1, 2021 - January 1, 2025
Bachelor of Computer Science at Sharif University of Technology
January 1, 2013 - January 1, 2019

Qualifications

Add your qualifications or awards here.

Industry Experience

Computers & Electronics, Manufacturing, Education, Professional Services, Software & Internet