Research Units

The Algorithms for Ecological and Evolutionary Genomics Unit develops computer algorithms for core problems in genomics to study the genomes of every extant species on our planet.

The Applied Cryptography Unit investigates the design and analysis of modern cryptographic primitives and schemes used to protect the confidentiality and integrity of data – at rest, being communicated or computed upon – both in the classical and the quantum settings. Particular areas of interest include the design and analysis of quantum / post-quantum cryptography schemes, the algebraic cryptanalysis of symmetric and asymmetric key algorithms, as well as the design and analysis of primitives for privacy-preserving cryptographic mechanisms.

The biological nonlinear dynamics data science unit investigates complex systems explicitly taking into account the role of time. We do this by instead of averaging occurrences using their statistics, we treat observations as frames of a movie and if patterns reoccur then we can use their behaviors in the past to predict their future. In most cases the systems that we study are part of complex networks of interactions and cover multiple scales. These include but are not limited to systems neuroscience, gene expression, posttranscriptional regulatory processes, to ecology, but also include societal and economic systems that have complex interdependencies. The processes that we are most interested in are those where the data has a particular geometry known as low dimensional manifolds. These are geometrical objects generated from embeddings of data that allows us to predict their future behaviors, investigate causal relationships, find if a system is becoming unstable, find early warning signs of critical transitions or catastrophes and more. Our computational approaches are based on tools that have their origin in the generalized Takens theorem, and are collectively known as empirical dynamic modeling (EDM). As a lab we are both a wet and dry lab where we design wet lab experiments that maximize the capabilities of our mathematical methods. The results from this data driven science approach then allows us to generate mechanistic hypotheses that can be again tested experimentally for empirical confirmation. This approach merges traditional hypothesis driven science and the more modern Data driven science approaches into a single virtuous cycle of discovery.

We seek the principles governing the behavior of whole organisms, integrating physics, biology and computational approaches to understand life's most complex and fascinating phenomena.

Chiral representation theory unit investigates the symmetries arising in quantum field theories. More specifically, it focuses on the representation theory of infinite-dimensional Lie algebras such as Kac–Moody algebras, and more generally, on vertex algebras.

Collective Dynamics and Quantum Transport Unit explores dynamical and transport phenomena in various quantum matters and their spintronic, electronic, and quantum-information applications.

We study multiscale and multiphysics problems related to fluid dynamics by numerical simulations. Our research is focused on turbulence, non-Newtonian fluids and multiphase flows.

We study how neurons and microcircuits in the brain operate and explore the influences of neuronal morphology and excitability on common neural functions such as synaptic plasticity and learning, and determine how molecular mechanisms enable these functions.

We are developing theoretical and experimental projects in cognitive science, guided by the hypothesis that agent-environment interaction is an essential part of mental activity.

The ECBS unit studies the effects of symbiotic interactions on the origin and evolution of cellular life.

Research projects of the Evolutionary Neurobiology Unit include (1) anatomical and physiological dissections of the nervous systems of basal metazoans, mainly on diffused and regionally cond...

The Future-Proof Cryptography Unit studies Multi-Party Computation, Fully Homomorphic Encryption, Verifiable Computation and Cryptanalysis and how these are affected by quantum computers.

The Genomics and Regulatory Systems Unit combines computational and experimental methods to study principles of gene regulation during early organismal development, using Oikopleura dioica as a model organism.

We use the genomes of Neandertals and Denisovans, the closest evolutionary relatives of present-day humans, to identify genomic variants that are unique to modern humans.

The Information Theory, Probability and Statistics Unit performs theoretical research at the intersection of the fields described in the name with applications to various areas that include Estimation Theory, Computational Biology, Hypothesis Testing, etc.

In the machine learning and data science (MLDS) unit, we focus on developing fundamental machine learning algorithms and solving important scientific problems using machine learning. We are currently interested in statistical modeling for high-dimensional data including kernel and deep learning models and geometric machine learning algorithms, including graph neural networks (GNN) and optimal transport problems. In addition to developing ML models, we focus on developing new machine learning methods to automatically find a new scientific discoveries from data.

The Marine Physics and Engineering Unit advances the forecast of ocean dynamics and the development of hydrodynamic disaster mitigation alternatives, paving the way for novel ocean technologies.

Our unit focuses on understanding how environmental changes impact soil microbes, particularly those that are symbiotic with or pathogenic to plants, and drive biogeochemical cycling.