Debajyoti Mondal

Debajyoti Mondal

Assistant Professor, University of Saskatchewan, Canada

Biographic Information

Dr. Mondal is an assistant professor in the Department of Computer Science at the University of Saskatchewan.

Previously he was an NSERC Postdoctoral Fellow in the Cheriton School of Computer Science at the University of Waterloo, ON, Canada, and worked as a research intern at Microsoft Research, Redmond, USA. He received his PhD and MSc degree from the Department of Computer Science, University of Manitoba, Winnipeg, MB, Canada. He received his B.Sc. engineering degree from Bangladesh University of Engineering and Technology (BUET).

Research Interest

Information visualization, visual analytics of big data, interactive visualization.
Graph drawing, network analysis and visualization.
Computational geometry, algorithms and complexity.
Interdisciplinary research that integrates visualization into various contexts such as hydrological modelling, social networks, software analysis, bioinformatics, and network routing.


Research Projects

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Graph Drawing and Visualization

Graph drawing focuses on finding geometric representations of graphs. Aside from theoretical interest, graph drawing is used in vast varieties of practical applications such as VLSI circuit layout, social network analysis, software system visualization, geometric routing, and bioinformatics. We examine theoretical bounds on the drawing aesthetics, and develop algorithms to draw graphs satisfying the constraints that arise from practical applications.

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Visual Analytics of Big Data

Our lives today are deeply influenced by information technology which exposes us to a massive volume of data. Visualization is a powerful technique to deal with such large information. A good visualization can reveal the key properties of the data, as well as it helps users to make better decisions. We examine how to develop a visualization summary of large data to reveal interesting structures and features of the underlying information.

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Computational Geometry

Computational geometry is concerned with the design and analysis of algorithms for solving geometric problems. Geometric problems arise from a variety of theoretical and applied fields, e.g., robot motion planning, database search, spatial data handling, computer graphics, etc. We develop efficient algorithms to solve such geometric problems and analyze their efficiency using discrete mathematical methods.

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Graphs and Combinatorics

Graphs are widely used to represent a variety of relational data. Many computational problems are routinely solved using graph models both in theory and practice. We examine graph structures that satisfy a set of given constraints, and combinatorial problems on graphs such as enumeration and coloring.

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Interdisciplinary research

The tools and techniques for solving geometric and graph theoretical problems can be applied effectively in many other research areas. We are particularly interested in applying these concepts, and theories to software testing and computer vision.

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Global Water Future

Visual analytics can reveal important insight into large data. In a project of Global Water future, we are intograting visual analytics to analyze the change in cimate and water quality. Our water is at risk. In Canada and globally, we are facing unprecedented water-related challenges. Canada has some of the world's highest rates of warming, which impacts infrastructure, institutions, ecosystems and human health. Global Water Futures is finding solutions to those water threats in an era of global change.

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