Saif Eddin Jabari
Scholar

Saif Eddin Jabari

Google Scholar ID: S0RhavQAAAAJ
New York University Abu Dhabi
scaling lawstraffic data analysisstochastic traffic flowtraffic operations and control
Citations & Impact
All-time
Citations
1,508
 
H-index
20
 
i10-index
31
 
Publications
20
 
Co-authors
24
list available
Resume
Academic Achievements
  • Published papers include 'Linear representations of neural networks', 'Adversarial training with general p norms', 'Traffic Forecasting As A Matrix Completion Problem', 'Position-Weighted Backpressure Intersection Control', 'Stochastic Lagrangian Traffic Dynamics', 'Sparse Estimation of Travel Times from Streaming Data', 'Node Modeling for Urban Networks', 'Probabilistic Fundamental Relations', 'Incident Localization and Sensor Placement'.
Research Experience
  • Research projects involve examining the vulnerability of deep neural networks (DNNs) used in AV control, developing scaling laws to disentangle transient fluctuations from long-term dynamics in traffic, and creating novel operators to solve forward and backward problems in traffic flow.
Background
  • Research interests include using applied probability, statistical physics, optimization, linear algebra, and dynamical systems theory to address three classes of problems: AI and AV security, the statistical physics of traffic, and neural operators for traffic flow.