I am a graduate research assistant at Isfahan University of Technology (IUT) with extensive experience in designing and developing AI frameworks for healthcare applications. My passion lies in creating advanced AI tools to assist patients and healthcare professionals, ultimately enhancing quality of life. Through my work, I aim to improve clinical outcomes, detect and prevent diseases, and mitigate harmful health habits. I thrive on conducting research and developing innovative solutions by leveraging machine learning, deep learning, and signal and image processing techniques. To stay at the forefront of this rapidly evolving field, I am dedicated to continuously expanding my knowledge and expertise in AI. My ultimate goal is to bridge the gap between cutting-edge technology and practical healthcare solutions, fostering impactful advancements in the medical field.

- My research focuses on leveraging AI and machine learning, particularly deep learning and neural networks, to detect both physical and mental health conditions early. The goal is to prevent diseases before they arise, halt their progression, and reduce complications for patients who are already affected.

- Working with signals (e.g., ECG, EEG) and medical images (e.g., MRI, CT) to extract features and develop ML models for real-time monitoring, diagnosis, and deeper understanding of medical conditions.

- Designing methods that make AI decision-making clear and reliable so that clinicians and patients can use them with confidence.

- Experienced in dataset creation (collection, annotation, and curation) and fine-tuning pretrained LLMs for NLP tasks such as sentiment analysis. Interested in extending this expertise to multi-modal medical applications by integrating text, images, and signals for deeper understanding of complex conditions.