Our work involves the improvement of technology surrounding intelligent hardware and software agents and the development of applications employing these technologies. We are especially interested in humanoid and micro-robots, cooperation in multi-agent settings, and the infrastructure necessary to support social interaction in intelligent systems.
The bioinformatics lab develops tools for problems in life sciences. We focus on algorithms for dealing with genomic and proteomic data. Recent collaborative projects in the bioinformatics labs include genome sequencing, EST data analysis, and RNA structure prediction algorithms.
We tackle research problems in combinatorial configurations; i.e., graphs, designs, lottodesigns, hypergraphs, Latin squares, codes and geometries. We ask "For what parameters do these configurations exist/" and "Are there 'nice' ones?". We prove theorems and write programs requiring large resources.
Pricing instruments is a highly challenging area of research in Computational Finance (CF). We (i) design, develop and implement new algorithms on advanced computing systems; (ii) apply our current CF knowledge to Grid/Cloud Computing; and (iii) train and create a new breed of HQP.
The Computational Geometry Laboratory examines research problems in theoretical computer science and, in particular, on algorithmic problems that involve geometry. Current research projects span several areas, including algorithms, data structures, computational complexity, and graph theory.
The website is a classified list of papers and theses by people in the Department of Computer Science at the University of Manitoba. Topics that we have been concentrating on recently include fair curve design, curve design with spirals, and curve design with arc splines.
Research within the laboratory focuses on databases and data mining, which includes efficient and effective management of, knowledge discovery from, as well as analysis of, large amounts of data (such as transactional, uncertain, social media, Web, and/or streams of data).
We explore how to design, implement and evaluate ways for people to interact with emerging computing technologies. Specifically, we investigate Information Visualization, Tabletop and Large Displays, Intelligent Interactive Systems, and Human-Robot Interaction.
At IDEAS laboratory, we evolve ideas from nature to map and design algorithms on futuristic high performance, heterogeneous multicore architectures. We design and analyze performance of parallel/distributed algorithms for compute intensive, large-scale graph problems in a wide range of interdisciplinary applications, including wireless mobile networks.
We work in parallel / distributed systems and certain supporting technologies such as compilers, networks, and operating systems. Our research includes newer topics such as cloud/grid computing, sensor networks, P2P, and pervasive computing. Issues of scale, performance and reliability are a focus. Methodology includes a combination of prototyping and simulation.