Prof. Pain's research interests lie within high-throughput sequencing and comparative genomics of human and animal pathogens, host-pathogen interactions, non-protein-coding RNAs and regulation of gene expression in apicomplexan parasites, deep sequencing of microbial populations to study natural and experimental genome and phenotypic diversity and translation of the research findings to diagnostics and therapeutics.
Prof. Gehring is interested in discovering how plants perceive and signal environmental stimuli, process this information and mount both short-term and long-term responses at the systems level to ensure optimal growth and development.

Dr. Matthew MacCabe's research is focused on Hydrological cycle, Water resources engineering, Earth system modeling, Evapotranspiration, In-situ measurement, Land-atmosphere interactions and Climate impacts.

Dr. Rachid Ait-Haddou's interests are in Geometric Modeling, Geometric Processing and the Mathematical Modeling of biological systems. His recent work includes the study of Chebyshev blossoms in Muntz spaces, the geometrical and analytical applications of the theory of complex Bezier curves and the investigation of the effect of buffers in intra-cellular calcium signaling.
Prof. Arold’s research interests are focused on integrative structural biology based on hybrid approaches. His work involves inferring structure and function of macromolecular assemblies, to enhance computational methods for functional annotation of genes (system-wide or focused), and to design and engineer molecules with desired properties (switches, genetic/epi-genetic regulators, detectors).
Prof. Vladimir Bajic's primary interest is in the facilitation of biological discoveries through the use of sophisticated bioinformatic systems combined with data modeling methods, with an emphasis on the discovery of bioactive molecules for potential medical applications. To accomplish this, Bajic partly uses technologies he co-developed for identifying co-regulated gene groups implicated in various diseases and cellular responses, along with new modeling technologies for relevant sequence signal recognition.