Recommended expert
Maryam Aghabozorgi
AI Engineer / Data Scientist
Experience
Sep 2025 - Present
5 monthsAI Engineer / Data Scientist
Space Physics Group, Charles University
- Using generative AI techniques to accelerate and enhance Coronal Mass Ejection (CME) simulations for improved space weather prediction.
- Mentored junior researchers in ML model development, data preprocessing, and model validation.
Jan 2025 - Dec 2025
1 yearDigital Twin Floorplan Generation (Python)
- Processed 3D LIDAR point clouds with RANSAC and DBSCAN to generate accurate 2D floorplans.
Jan 2025 - Dec 2025
1 yearTransformer-Based Semantic Embedding Prototype (Python)
Self-directed
- Prototyped semantic search using Sentence Transformers and FAISS vector similarity to explore domain-specific retrieval.
- Compared cosine similarity and hybrid search strategies for identifying context-relevant plasma events.
- Gained practical understanding of embeddings, vector stores, query expansion, and RAG workflows.
Feb 2024 - May 2024
4 monthsVisiting Researcher (HPC AI Workflows)
National Center for High-Performance Computing (NCHC)
- Automated data ingestion and analysis pipelines in HPC environments using Python and Linux-based scripting.
Jan 2024 - Dec 2025
2 yearsRegion Identification in Spacecraft Data using Machine Learning (Python)
- Processed THEMIS spacecraft time series data, performed feature extraction, and trained supervised ML models.
- Developed Random Forest and Neural Network classifiers using scikit-learn and TensorFlow to automate region identification.
Jan 2022 - Dec 2023
2 yearsMagnetopause Location Modeling with ANN (IDL)
- Trained an ANN to predict boundary locations using solar wind parameters, IMF orientation, and corrected Dst.
Oct 2021 - Sep 2025
4 yearsResearch Assistant
Charles University
- Conducted AI-driven analysis of plasma environments using spacecraft data from THEMIS, Geotail, and Magion 4 missions.
- Built predictive models to estimate magnetopause positions and classify solar wind regions.
- Developed end-to-end data pipelines for feature extraction, normalization, and model training using Python and TensorFlow.
- Applied machine learning models (neural networks, random forests) to classify complex satellite datasets.
Dec 2020 - Aug 2021
9 monthsTelecom Pre-Deployment Engineer
Borje Noor
- Designed FTTx broadband network topologies and optimized component selection using COMSof FTTx.
- Supported planning for 5G infrastructure and coordinated with engineering and procurement teams.
Jul 2020 - Dec 2020
6 monthsRemote
Remote Guest Researcher (Quantum Systems)
QuTech, TU Delft
- Theoretically analyzed two-qubit photonic crystal systems and explored entanglement mechanisms in solid-state photonics.
Oct 2016 - Jun 2020
3 years 9 monthsResearch Assistant, Photonics Group
Shahrekord University
- Simulated electromagnetic and photonic systems using COMSOL and Lumerical for sensing and energy harvesting applications.
- Designed and optimized plasmonic waveguides, resonators, and solar cells.
Summary
AI Engineer with a PhD in space physics and a strong background in applied machine learning, data pipelines, and scientific computing. Experienced in developing classification models using neural networks and decision trees for large-scale, domain-specific datasets.
Knowledgeable in modern NLP techniques including transformer-based models (e.g., BERT, GPT), vector similarity search, and retrieval-augmented generation (RAG). Strong Python programmer with expertise in TensorFlow, scikit-learn, and data visualization. Actively exploring LLM-based architectures and semantic search integration for specialized domains.
Skills
- Python
- Sql
- Matlab
- Idl
- R
- C++
- Tensorflow
- Keras
- Pytorch
- Scikit-learn
- Huggingface Transformers
- Sentence Transformers
- Faiss
- Opensearch
- Pinecone
- Docker
- Azure
- Git
- Linux (Bash)
- Ci/cd
- Matplotlib
- Seaborn
- Spotfire
- Ggplot2
Languages
English
AdvancedCzech
ElementaryEducation
Charles University
PhD · space physics · Prague, Czech Republic
Certifications & licenses
Honored Certificate
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