Rashin Gholijani Farahani

Hi! I’m Rashin Gholijani Farahani, an MSc student in Artificial Intelligence and an aspiring researcher passionate about building data-efficient, explainable, and trustworthy machine learning systems with real-world impact. I completed my BSc in three years with distinction and currently maintain a top-tier academic standing in my master’s program, alongside teaching programming and AI fundamentals to early-career learners.

My research interests are broad and interdisciplinary, spanning deep learning, reinforcement learning, natural language processing, computer vision, speech and audio processing, and multimodal learning. I am especially drawn to problems where rigorous methodology meets societal value — particularly AI for healthcare and well-being, explainable and trustworthy AI, and the responsible application of large language models and foundation models to complex, data-scarce domains.

Across my projects, I have worked on a range of applied ML problems including audio-based classification, medical diagnosis support, mental-health-related modeling, financial decision systems, and image-based recognition in agricultural settings. I enjoy working at the full stack of an ML project — from signal and feature engineering, through model design and training, to evaluation, interpretability, and clear scientific communication.

I am currently exploring PhD opportunities abroad in machine learning and its applications to health, language, and human-centered AI. I’m always open to research collaborations, discussions, and new ideas — please feel free to reach out!