Nadim Saad
Assistant Teaching Professor
Education
- PhD in Computational and Mathematical Engineering, Stanford University
- MSc in Computational and Mathematical Engineering, Stanford University
- BSc in Applied Mathematics, American University of Beirut — Lebanon
Biography
Nadim Saad is an assistant teaching professor in the Khoury College of Computer Sciences at Northeastern University, based in Silicon Valley.
During his doctoral studies at Stanford University, Saad developed traffic flow models based on partial differential equations. He also built physically informed deep learning models to solve PDEs during his time as an applied scientist intern with Amazon Web Services.
Saad joined Khoury College in 2023, where he teaches a variety of foundational computer science and data science courses. Saad enjoys these courses, as he can guide students in subject areas that might be new to them and encourage them to pursue computing careers. He also enjoys teaching more specialized elective courses like “Supervised Machine Learning and Learning Theory” to help students who have already found a passion within computer science to grow their knowledge further.
Recent publications
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Guiding continuous operator learning through Physics-based boundary constraints
Citation: Nadim Saad, Gaurav Gupta, Shima Alizadeh, Danielle C. Maddix. (2022). Guiding continuous operator learning through Physics-based boundary constraints CoRR, abs/2212.07477. https://doi.org/10.48550/arXiv.2212.07477 -
Modeling Advection on Directed Graphs using Matérn Gaussian Processes for Traffic Flow
Citation: Danielle C. Maddix, Nadim Saad, Yuyang Wang . (2022). Modeling Advection on Directed Graphs using Matérn Gaussian Processes for Traffic Flow CoRR, abs/2201.00001. https://arxiv.org/abs/2201.00001