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I'm Fatemeh Saedi Fard, a Machine Learning Engineer focused on deep learning, multimodal data processing, and human-computer interaction. I design and evaluate AI-powered decision support and interactive systems, with hands-on experience building real-time prediction and explainability into driver-assistance prototypes at Fiat Research Center (CRF) in Italy. My work blends technical rigor with a user-centered approach to improve safety and usability in complex environments. I hold a Master of Science in Technology Engineering from the University of Genova and a Bachelor of Science in Electronics Engineering from Azad University. My research spans real-time prediction of human driving intentions validated in CARLA, with ongoing manuscript preparation for IEEE/ ACM venues. I am passionate about multimodal large language models and computational interaction research, and I welcome collaboration and opportunities to apply AI to real-world human-computer interaction challenges.…I'm Fatemeh Saedi Fard, a Machine Learning Engineer focused on deep learning, multimodal data processing, and human-computer interaction. I design and evaluate AI-powered decision support and interactive systems, with hands-on experience building real-time prediction and explainability into driver-assistance prototypes at Fiat Research Center (CRF) in Italy. My work blends technical rigor with a user-centered approach to improve safety and usability in complex environments. I hold a Master of Science in Technology Engineering from the University of Genova and a Bachelor of Science in Electronics Engineering from Azad University. My research spans real-time prediction of human driving intentions validated in CARLA, with ongoing manuscript preparation for IEEE/ ACM venues. I am passionate about multimodal large language models and computational interaction research, and I welcome collaboration and opportunities to apply AI to real-world human-computer interaction challenges.

Fatemeh Saedi Fard

Data Scientist, AI Engineer, AI Developer, +2

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I'm Fatemeh Saedi Fard, a Machine Learning Engineer focused on deep learning, multimodal data processing, and human-computer interaction. I design and evaluate AI-powered decision support and interactive systems, with hands-on experience building real-time prediction and explainability into driver-assistance prototypes at Fiat Research Center (CRF) in Italy. My work blends technical rigor with a user-centered approach to improve safety and usability in complex environments. I hold a Master of Science in Technology Engineering from the University of Genova and a Bachelor of Science in Electronics Engineering from Azad University. My research spans real-time prediction of human driving intentions validated in CARLA, with ongoing manuscript preparation for IEEE/ ACM venues. I am passionate about multimodal large language models and computational interaction research, and I welcome collaboration and opportunities to apply AI to real-world human-computer interaction challenges.…I'm Fatemeh Saedi Fard, a Machine Learning Engineer focused on deep learning, multimodal data processing, and human-computer interaction. I design and evaluate AI-powered decision support and interactive systems, with hands-on experience building real-time prediction and explainability into driver-assistance prototypes at Fiat Research Center (CRF) in Italy. My work blends technical rigor with a user-centered approach to improve safety and usability in complex environments. I hold a Master of Science in Technology Engineering from the University of Genova and a Bachelor of Science in Electronics Engineering from Azad University. My research spans real-time prediction of human driving intentions validated in CARLA, with ongoing manuscript preparation for IEEE/ ACM venues. I am passionate about multimodal large language models and computational interaction research, and I welcome collaboration and opportunities to apply AI to real-world human-computer interaction challenges.

Available to hire

I’m Fatemeh Saedi Fard, a Machine Learning Engineer focused on deep learning, multimodal data processing, and human-computer interaction. I design and evaluate AI-powered decision support and interactive systems, with hands-on experience building real-time prediction and explainability into driver-assistance prototypes at Fiat Research Center (CRF) in Italy. My work blends technical rigor with a user-centered approach to improve safety and usability in complex environments.

I hold a Master of Science in Technology Engineering from the University of Genova and a Bachelor of Science in Electronics Engineering from Azad University. My research spans real-time prediction of human driving intentions validated in CARLA, with ongoing manuscript preparation for IEEE/ ACM venues. I am passionate about multimodal large language models and computational interaction research, and I welcome collaboration and opportunities to apply AI to real-world human-computer interaction challenges.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Work Experience

Machine Learning Engineer at Fiat Research Center (CRF), Italy

June 1, 2024 - February 1, 2025

Designed and implemented an AI-driven interactive driver assistance prototype for real-time human-machine interaction in simulated environments. Developed deep learning models for human behavior prediction and lane-change timing up to 4 seconds in advance. Built multimodal decision pipelines using vehicle dynamics, contextual data, and surrounding agent behavior. Created proactive alert systems based on predicted user intent and environmental risk factors. Implemented real-time validation pipelines in the CARLA simulator using Python. Applied explainable AI techniques (SHAP) for model interpretation and transparency.

Data Analyst at Khuzestan Steel Co

November 1, 2015 - March 1, 2019

Analyzed operational and financial data to support internal reporting and process improvement. Built data-driven reports and performance tracking workflows to improve decision-making. Supported productivity improvement initiatives through structured data analysis.