I am a PhD physicist and AI researcher with 4+ years of R&D experience applying deep learning and scientific data analysis to imaging and sensor data. I enjoy building transformer-based models (Qwen, CLIP, ViT), multimodal retrieval systems, and image segmentation pipelines, using Python as my primary toolkit. I thrive in cross-disciplinary teams and have mentored juniors and colleagues across international collaborations. My work spans academia and industry, bridging experiments with computation. I have led projects in Portugal, Switzerland, Germany, and the Netherlands, developed reproducible pipelines for materials computation and imaging validation, and designed physics-informed generative models to synthesize data and address class imbalance. I am passionate about turning complex data into actionable insights and scalable workflows.

Ali Baghi Zadeh

I am a PhD physicist and AI researcher with 4+ years of R&D experience applying deep learning and scientific data analysis to imaging and sensor data. I enjoy building transformer-based models (Qwen, CLIP, ViT), multimodal retrieval systems, and image segmentation pipelines, using Python as my primary toolkit. I thrive in cross-disciplinary teams and have mentored juniors and colleagues across international collaborations. My work spans academia and industry, bridging experiments with computation. I have led projects in Portugal, Switzerland, Germany, and the Netherlands, developed reproducible pipelines for materials computation and imaging validation, and designed physics-informed generative models to synthesize data and address class imbalance. I am passionate about turning complex data into actionable insights and scalable workflows.

Available to hire

I am a PhD physicist and AI researcher with 4+ years of R&D experience applying deep learning and scientific data analysis to imaging and sensor data. I enjoy building transformer-based models (Qwen, CLIP, ViT), multimodal retrieval systems, and image segmentation pipelines, using Python as my primary toolkit. I thrive in cross-disciplinary teams and have mentored juniors and colleagues across international collaborations.

My work spans academia and industry, bridging experiments with computation. I have led projects in Portugal, Switzerland, Germany, and the Netherlands, developed reproducible pipelines for materials computation and imaging validation, and designed physics-informed generative models to synthesize data and address class imbalance. I am passionate about turning complex data into actionable insights and scalable workflows.

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Experience Level

Expert
Expert
Expert
Expert
Intermediate

Language

English
Fluent
German
Advanced
Portuguese
Beginner

Work Experience

Self-Employed / Independent Researcher at Self-Employed
July 1, 2023 - November 12, 2025
Developed pipelines for pattern recognition and peak fitting of time-series mass spectrometry data, increasing the speed of data analysis. Designed reproducible Python workflows for defect detection in materials, enabling batch creation of models using materials computation and image simulation for microscopy validation. Built physics-informed generative models to create synthetic microscopy datasets and classify real data, addressing class imbalance and different ferroelastic domain types.
Technology Consultant at ScopeM Service Centre, ETH Zurich
July 1, 2023 - July 1, 2023
Implemented experimental microscopy/spectroscopy workflows with temperature, gas, and electrical measurements for in-situ studies. Delivered signal processing workflows (FFT, PCA denoising, clustering) to extract clean features from spectroscopy and microscopy signals for two clients. Built GPU-accelerated CNN pipelines and deployed cloud-based spectroscopy/microscopy Python pipelines to unify analysis across instruments/workstations. Integrated materials computation (DFT) with image simulation, linking ground truth to experimental data analysis. Led cross-team projects connecting physical experiments with modeling (10+ projects).
Postdoctoral Research Scientist at CICECO Institute of Materials, University of Aveiro
December 1, 2019 - December 1, 2019
Developed regression models on literature and experimental datasets to forecast material properties. Introduced hybrid computation–regression workflows, improving experimental design. Coordinated research collaborations across 3 countries and led nanoanalysis in an EU-funded project.
Technical Staff at University of Aveiro (Portugal) + Ministry of Science (Iran)
February 1, 2017 - February 1, 2017
Conducted laboratory analysis of magnetic nanoparticles and dielectric ceramics using in-situ XRD/TEM/AFM. Built process models (Monte Carlo, symmetry analysis) to predict materials behaviour and explain experimental data across 3 industry projects.

Education

PhD in Material Science at University of Aveiro
January 11, 2030 - January 1, 2015
MSc in Physics (First-Class Honour) at K. N. Toosi University of Technology
January 11, 2030 - January 1, 2002
BSc in Physics (First-Class Honour) at Bu-Ali Sina University
January 11, 2030 - January 1, 2000

Qualifications

FCT Postdoc grant
January 1, 2017 - December 31, 2017
FCT-Sesame PhD fellowship
January 1, 2011 - December 31, 2011

Industry Experience

Education, Life Sciences, Manufacturing, Professional Services, Software & Internet