Curriculum Vitae
Dr. Seyedsaman Emami
Assistant Professor, machine learning researcher, and founder working across gradient boosting, deep neural networks, multi-task learning, and research software.
Appointments
Current positions
2025 — Present
Assistant Professor
Universidad Autónoma de Madrid · UAM
Teaching
- Design and Analysis of Software
- Programming Languages
- Communication Networks
- Biomedical Engineering
Research
- Advanced machine learning models, including gradient boosting and deep neural networks.
- Learning theory, algorithmic efficiency, and research software.
- Collaboration with the GAA research group on AI initiatives.
2026 — Present
Founder
CVorah · AI-powered CV analysis and optimization platform
- Founded an AI-powered web and mobile platform for CV analysis and optimization.
Experience
Previous positions
2020 — 2025
Researcher and University Teaching Assistant
Universidad Autónoma de Madrid · UAM
- Created and formulated machine learning models in the Gradient Boosting Machine area.
- Designed novel deep neural network approaches for image processing and neural network training.
- Ran developed models on cluster servers with specific datasets and experimental settings.
- Taught Java and Computer Networks laboratory courses.
2025
Visiting Professor
Universitat de les Illes Balears · UIB
- Taught an undergraduate programming languages course.
2023 — 2024
Co-founder and CTO
NapCat Ventures
- Developed machine learning models using NLP, LLMs, CNNs, and GANs.
- Worked on industry research, innovation, and collaboration with external partners.
Education
Academic background
Ph.D. in Computer and Telecommunications Engineering
Universidad Autónoma de Madrid · Cum laude
Visiting Ph.D. Student
Telecommunications Engineering · University of Padua
MSc in Financial Engineering
IAU University
BSc in Industrial Engineering
IAU University
Technical profile
Skills and tools
Programming
PythonJavaCythonSQLHTML/CSSBashLaTeXMarkdown
Machine learning
NumPyPandasSciPyScikit-learnXGBoostKerasPyTorchTensorFlowGradioHuggingFace
Cloud platforms
AWSAzureGoogle CloudHuggingFace