Milad Nasiri
Summary
A Junior Computer Vision Machine Learning Engineer with a profound interest in machine learning and two years of experience in international team collaborations. Possesses a strong foundation in developing algorithms and models for computer vision applications, coupled with a relentless dedication to advancing skills in this field. Exceptional teamwork and communication abilities, with a background in Bioelectronics, facilitating the application of technological solutions in the healthcare sector. Committed to making meaningful contributions to the domains of computer vision and machine learning through unwavering curiosity and a drive for continuous learning.
Overview
3
3
years of professional experience
1
1
Certification
Work History
Machine Learning and Data Science Specialist
TopNetwork SpA
10.2022 - Current
- Responsibilities : Specialized in computer vision, concentrating on enhancing object detection accuracy in cutting-edge, confidential European initiatives and collaborative interdisciplinary projects. Utilized advanced transfer learning techniques to elevate object detection accuracy, making substantial contributions to project success and field advancement.
- Main Approach : Focused on computer vision, leveraging a diverse range of transfer learning methods and research papers to optimize object detection accuracy and advance the field.
- Achievements : Significantly improved object detection accuracy in computer vision applications, playing a pivotal role in the success of critical projects.
Data Science and Machine Learning Specialist
AiGoT SRL
03.2022 - 09.2022
- Responsibilities : Played a pivotal role in the "MaindCare" project, focusing on stress level detection from wearable devices like Smart watches . Conducted an extensive literature review, data synthesis, and developed a robust machine learning pipeline. Managed interdisciplinary collaboration and successfully delivered a stress detection solution.
- Main Approach : Utilized machine learning techniques, including Generative Adversarial Networks (GANs), for data generation and TensorFlow for pipeline development. Additionally, analyzed the impact of data from smartwatches and phones on human resource performance.
- Achievements : Achieved the successful implementation of a stress detection pipeline, showcasing adaptability and dedication to real-world problem-solving.
Internship and Master Thesis(Data Science and Mac)
Sapienza University Of Rome/Fondazione Santa Lucia Hospital
03.2021 - 03.2022
- Responsibilities : Significantly improved EEG signal analysis within the ERC (European Research Council) project. Enhanced the "semi-automatic ICs selection pipeline" by integrating the Independent Component Analysis (ICA) algorithm. Developed a versatile "IC selection" application using Python, MATLAB, and machine learning techniques for advanced EEG signal analysis.
- Main Approach : Integrated the Independent Component Analysis (ICA) algorithm into EEG signal processing, transcending conventional localization constraints. Developed a versatile "IC selection" application using Python and MATLAB for comprehensive visualization and analysis of pipeline outputs.
- Achievements : Advanced EEG signal analysis, contributing to the field's knowledge and expanding the capabilities of EEG data processing.
Education
Master of Science - Telecommunications Engineering
University of Padua
Padova,Italy04.2022
Bachelor of Science - Biomedical Engineering (Bioelectric)
University of Qazvin
Iran07.2016
Skills
- Expert in deep learning and machine learning methodologies
- Skilled in Generative AI techniques, contributing to innovative solutions
- Proficient in Python for data analysis and machine learning
- Experienced in MATLAB and R for advanced data processing
- Competent in Code Vision CI/CD for seamless development processes
- Proficient with Git and Github for version control and collaboration
- Experienced in SQL and Tableau for efficient data analysis and visualization
- Specialized in computer vision for advanced visual data analysis
- Knowledgeable in Bioelectric Engineering for specialized applications
- Proficient in PyTorch, NumPy, pandas, TensorFlow, and scikit-learn for machine learning and data analysis
- Familiar in Java and JavaScript for software development
- Familiar with LabVIEW and Proteus for electronics and embedded systems
- Familiar with Docker for containerization of applications
- Familiar in Natural Language Processing (NLP) for text analysis
Certification
AI and Machine Learning:
- Generative AI by Google
- Machine Learning and Data Science with PyTorch
- GE-healthcare - Artificial Intelligence
Computer Vision and Image Processing:
- Computer Vision Master Class
Tools and Frameworks:
- Git & Github
- EEG Signal Processing
- Natural Language Processing
- SQL - Business Intelligence Analysis
Languages
Persian
Bilingual or Proficient (C2)
English
Advanced (C1)
Italian
Elementary (A2)
Timeline
Machine Learning and Data Science Specialist
TopNetwork SpA
10.2022 - Current
Data Science and Machine Learning Specialist
AiGoT SRL
03.2022 - 09.2022
Internship and Master Thesis(Data Science and Mac)
Sapienza University Of Rome/Fondazione Santa Lucia Hospital
03.2021 - 03.2022
Master of Science - Telecommunications Engineering
University of Padua
Bachelor of Science - Biomedical Engineering (Bioelectric)
University of Qazvin
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