2022 PHD Theses

• PHD-2022-01(*) Alon Stern (Tomer Shlomi): Methods for inferring compartmentalized fluxes and concentrations in mammalian cells
• PHD-2022-02 Amit Boyarski (Alex Bronstein): Geometry in Numerical Algorithms
• PHD-2022-03 Yaron Fairstein (Joseph Naor and Danny Raz): Dynamicity and Multi-Commodity in Networks
• PHD-2022-04 Alona Golts (Michael Elad): Deep Energy: Task Driven Training of Deep Neural Networks
• PHD-2022-05 David Dovrat (Alfred M. Bruckstein): An Automata Theory Method for the Analysis of Unicycle Pursuit Problems
• PHD-2022-06 Lev Yohananov (Eitan Yaakobi): Codes over Graphs
• PHD-2022-07 Idan Schwartz (Tamir Hazan, Alexander Schwing): Cognitive Models in Deep Learning
• PHD-2022-08 Guy Rosin (Kira Radinsky, Shaul Markovitch): Incorporating Time into Word Representations
• PHD-2022-09 Dean Leitersdorf (Keren Censor-Hillel): Fast Distributed Algorithms via Sparsity Awareness
• PHD-2022-10 Ohad Eytan (Roy Friedman): Access Patterns and Caching Algorithms
• PHD-2022-11 Ido Hakimi (Assaf Schuster): Distributed Deep Neural Networks