Publications: Co-authored papers applying process mining, machine learning, and deep learning to improve mortality prediction for ICU patients.
Research Experience
Research Projects: Developing advanced AI models to solve real-world problems in healthcare and transportation, including applying process mining, machine learning, and deep learning to improve mortality prediction for ICU patients. Also worked on projects utilizing NLP, generative AI, and optimization techniques in transportation, finance, agriculture, and manufacturing.
Education
Degree: Bachelor's; School: Sharif University of Technology; Time: Not specified; Major: Not specified.
Background
Research Interests: Artificial Intelligence, Data Science, Machine Learning, and Optimization. Background: Graduate student at the University of Southern California, focusing on Analytics, with a background in AI, Data Science, Machine Learning, and Optimization.
Miscellany
Skills: Proficient in tools such as TensorFlow, PyTorch, scikit-learn, R, SQL, and Gurobi, with expertise in deep learning, large language models (LLMs), statistical analysis, data-driven decision-making, and reinforcement learning.