I'm Sepehr Rezaee, a Bachelor's student in Computer Science at the National University of Iran, Tehran. My research interests include:
- Modeling disease progression using differential equations and employing Physics-Informed Neural Networks (PINN).
- Developing robust and interpretable machine learning models.
- Analyzing M/EEG data using advanced deep learning techniques.
I have submited papers in prestigious conferences like NeurIPS, focusing on topics such as backdooring out-of-distribution detection methods, scanning trojaned models, and robust novelty detection under style shifts.
My professional experience includes:
- Research Assistant at the Artificial Intelligence and Scientific Computing Lab, Tehran.
- Research Assistant at the Robust and Interpretable Machine Learning Lab, Sharif University of Technology, Tehran.
- Deep Learning and Neuroscience Intern Researcher at the Institute for Research in Fundamental Sciences (IPM), Tehran.
I have received awards and honors, including the Best Ideator Award at the 7th National Young Scientists Festival and ranking among the top 0.5% in the entrance exam.
Additionally, I have served as a Teaching Assistant for Advanced Programming, Data Mining and Analysis, and Basic Programming courses at the National University of Iran. I have also been actively involved in extracurricular activities, acting as an assistant teacher and mentor for the application of Data Science and Artificial Intelligence in various industries.