Department of Computer Science and Applied Mathematics

Vered Rom-Kedar, Head


The principal interests of the department lie in the areas of computer science and applied mathematics. Research areas include (but are not limited to) algorithms, their design and analysis; biological applications, bioinformatics, system biology, biological modeling; computational complexity, probabilistic proof systems, hardness of approximation, circuit complexity, combinatorial games; computer vision, image processing; cryptography; differential equations; distributed and parallel computing; dynamical systems; fluid dynamics; logic of programs, specification methodologies; machine learning and mathematical statistics; numerical analysis; randomness and its relation to computation; robotics and motion control; visual perception and brain modeling.

The departmental computer facilities include multiple PCs, multiple unix servers, two Linux clusters with multiple nodes, and large data storage systems. In addition, the vision laboratories, robotics laboratories and computational biology laboratories have a combination of experimental equipment and large-scale computing clusters.


R. Basri

Computer vision, image processing

  1.  Object recognition and categorization under unknown lighting and pose

  2.  3D shape reconstruction

  3.  Perceptual grouping and segmentation


A. Brandt

Multi-level computational methods, scientific computation.


I. Dinur

Probabilistically Checkable Proofs

Hardness of Approximation


U. Feige

Coping with NP-hard combinatorial optimization problems, algorithms, computational complexity, random walks, algorithmic game theory.


T. Flash

Robotics, motor control and learning, movement disorders, computational neuroscience, virtual reality.


O. Goldreich

Randomness and Computation

  1.  Property Testing

  2.  Probabilistic proof systems

  3.  Pseudorandomness

Foundations of Cryptography

Complexity theory


S. Goldwasser

Probabilistic proofs, cryptography, computational number theory, complexity theory.


D. Harel

Visual formalisms, software engineering, biological modeling, visualization.


M. Irani

Computer Vision, Video information analysis and applications, Image Processing.


R. Krauthgamer

Design and analysis of algorithms, including massive data sets, data analysis, and combinatorial optimization

Embeddings of finite metric spaces, high dimensional geometry


Y. Lipman

Geometric modeling, geometry processing, shape analysis, computer graphics, Discrete differential geometry


B. Nadler

Mathematical Statistics, Statistical Machine Learning, Statistical Signal and Image Processing, Applied Mathematics


M. Naor

Cryptography and Complexity

Distributed Computing

Concrete Complexity


D. Peleg

graph algorithms, spanners, approximation algorithms
D. Peleg, Cyril Gavoille, Liam Roditty

distributed computing, fault tolerance, multi-robot systems, multi-agent systems
D. Peleg, Gopal Pandurangan, Pierre Fraigniaud, Andrzej Pelc, Roger Wattenhofer

communication networks, wireless communication
D. Peleg, Zvi Lotker, Chen Avin


R. Raz

Complexity Theory: In particular: Boolean circuit complexity, arithmetic circuit complexity, communication complexity, probabilistically checkable proofs, quantum computation and communication, randomness and derandomization.


V. Rom-Kedar

Hamiltonian systems - theory and applications
V. Rom-Kedar, M. Radnovic, A. Rapoport, E. Shlizerman, D. Turaev

  1.  Near-integrable systems

  2.  The Boltzmann ergodic hypothesis and soft billiards.

  3.  Chaotic scattering.

  4.  Resonant surface waves.

  5.  Perturbed nonlinear Schrodinger equation.

Mathematical models of the hematopoietic system and their medical implications
V. Rom-Kedar, R. Malka, E. Shochat.

Chaotic mixing of fluid flows
V. Rom-Kedar, R. Aharon, H. Gildor


E. Segal

Models for transcription and chromatin regulation

Modeling the role of microRNAs and non-coding RNAs in gene regulation


A. Shamir

Cryptography, cryptanalysis, electronic money, smartcard security, internet security, complexity theory, the design and analysis of algorithms.


O. Shamir

Machine Learning, statistical learning, online learning, learning theory, optimization


E. Shapiro

Laying the Biological, Computational and Architectural Foundations for Human Cell Lineage Discovery
E. Shapiro, E. Shapiro, V. Adalsteinsson, H. Brodi, M. Minden, R. Halaban, C. Klein, M. Meyerson, C. Wu, T. Zukerman, R. Shalom


E. Titi

Nonlinear Partial Differential Equations and Dynamical Systems

  1.  Infinite-dimensional dynamical systems , Reduced dynamical systems, Numerical analysis of dissipative PDEs

  2.  Limit behavior of fast and slow dynamics

Fluid Dynamics and geophysical flows

  1.  Navier-Stokes, Euler and related geophysical models

  2.  Turbulence theory

  3.  Polymeric flows and non-Newtonian complex fluid


S. Ullman

Vision, image understanding, brain theory, artificial intelligence.