Huda Nassar

I am a fifth year Computer Science PhD student at Purdue University (currently on the job market). My major focus is on graph alignment, where I focus on low rank approaches to solve these computationally hard problems. More broadly, I am interested in network science in general and numerical linear algebra problems. Before joining Purdue, I obtained two Bachelor's degrees in Mathematics and Computer Science, as well as a diploma in Educational Management and Leadership (My secret dream job was to have my own school one day) -- all from the American University of Beirut (AUB).


  • Vikram Ravindra, Huda Nassar, David F. Gleich, Ananth Grama, Structural graph alignment, submitted
  • Huda Nassar, Georgios Kollias, Ananth Grama, David F. Gleich, Low rank methods for multiple network alignment, submitted
  • Chih-Hsu Lin, Daniel Konecki, Meng Liu, Stephen Wilson, Huda Nassar, Angela Wilkins, David Gleich and Olivier Lichtarge, Multimodal Network Diffusion Predicts Future Disease-Gene-Chemical Associations, Bioinformatics 2018.
  • Huda Nassar, Nate Veldt, Shahin Mohammadi, Ananth Grama, David F. Gleich, Low Rank Spectral Network Alignment, The Web Conference 2018.
  • David F. Gleich, Kyle Kloster, Huda Nassar, Localization in Seeded PageRank, Journal of Internet Mathematics 2017.
  • Huda Nassar and David F. Gleich, Multimodal Network Alignment, SIAM International Conference on Data Mining 2017.
  • Huda Nassar, Kyle Kloster, David F. Gleich, Strong Localization in Personalized PageRank Vectors, Workshop on Algorithms and Models for the Web Graph 2015.

    Meetings organized

  • Julia Purdue University Group (JPUG)
  • [Past]: Women in Data Science (WIDS)
  • Software packages and resources

  • Graph Algorithms in Julia MatrixNetworks.jl
  • Network Alignment algorithms in Julia NetworkAlign.jl
  • Julia for data science material from Purdue WIDS 2018.
  • Intro to Julia.
  • A quick short tutorial on matrix factorizations
  • Contact Info

  • Email: hnassar at
  • @nassarhuda on Github and Twitter