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.Computer vision, image processing
- Object recognition and categorization under unknown lighting and pose
- 3D shape reconstruction
- Perceptual grouping and segmentation
Multi-level computational methods, scientific computation.
Probabilistically Checkable Proofs
Hardness of Approximation
Coping with NP-hard combinatorial optimization problems, algorithms, computational complexity, random walks, algorithmic game theory.
Robotics, motor control and learning, movement disorders, computational neuroscience, virtual reality.
Property Testing; Probabilistic proof systems; Pseudorandomness; Foundations of Cryptography; Complexity theory
Probabilistic proofs, cryptography, computational number theory, complexity theory.
Visual formalisms, software engineering, biological modeling, visualization.
Computer Vision, Video information analysis and applications, Image Processing.
Design and analysis of algorithms, including massive data sets, data analysis, and combinatorial optimization
Embeddings of finite metric spaces, high dimensional geometry
Computer vision, Computer graphics, Image processing
Geometric modeling, geometry processing, shape analysis, computer graphics, Discrete differential geometry
Numerical analysis, differential equations, dynamical systems.
Mathematical Statistics, Statistical Machine Learning, Statistical Signal and Image Processing, Applied Mathematics
Cryptography and Complexity
Distributed Computing
Concrete Complexity
graph algorithms, spanners, approximation algorithms
D. Peleg, Cyril Gavoille, Liam Rodittydistributed computing, fault tolerance, multi-robot systems, multi-agent systems
D. Peleg, Gopal Pandurangan, Pierre Fraigniaud, Andrzej Pelc, Roger Wattenhofercommunication networks, wireless communication
D. Peleg, Zvi Lotker, Chen AvinComplexity Theory: In particular: Boolean circuit complexity, arithmetic circuit complexity, communication complexity, probabilistically checkable proofs, quantum computation and communication, randomness and derandomization.
Foundations of Computer Science
- Computational Complexity
- Foundations of Cryptography
- Randomness, Derandomization and Explicit Combinatorial Constructions
Hamiltonian systems - theory and applications
V. Rom-Kedar, M. Radnovic, A. Rapoport, E. Shlizerman, D. Turaev
- Near-integrable systems
- The Boltzmann ergodic hypothesis and soft billiards.
- Chaotic scattering.
- Resonant surface waves.
- 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. GildorModels 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, big data
Biomolecular computing and its medical applications
High-throughput Computer-Aided Design, Manufacturing and Application
Human and mouse cell lineage trees
E. Shapiro, E. Shapiro, Prof. Nava Dekel, Prof. Karl Skorecki, Dr Liran Shlush
E. Titi
Nonlinear Partial Differential Equations and Dynamical Systems
- Infinite-dimensional dynamical systems , Reduced dynamical systems, Numerical analysis of dissipative PDEs
- Limit behavior of fast and slow dynamics
Fluid Dynamics and geophysical flows
- Navier-Stokes, Euler and related geophysical models
- Turbulence theory
- Polymeric flows and non-Newtonian complex fluid
Vision, image understanding, brain theory, artificial intelligence.