Expertise

Scientific Director

Raymond T Ng

Professor, Computer Science
Canada Research Chair in Data Science and Analytics
Chief Informatics Officer, PROOF (Prevention of Organ Failure) Centre

Raymond’s main research area for the past two decades is on data mining, with a specific focus on health informatics and text mining. He has published over 180 peer-reviewed publications on data clustering, outlier detection, OLAP processing, health informatics and text mining. He is the recipient of two best paper awards – from the 2001 ACM SIGKDD conference, the premier data mining conference in the world, and the 2005 ACM SIGMOD conference, one of the top database conferences worldwide. For the past decade, he has co-led several large-scale genomic projects funded by Genome Canada, Genome BC and industrial collaborators. Since the inception of the PROOF Centre of Excellence, which focuses on biomarker development for end-stage organ failures, he has held the position of the Chief Informatics Officer of the Centre. From 2009 to 2014, Dr. Ng was the associate director of the NSERC-funded strategic network on business intelligence.

More about Raymond Ng

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Affiliated Faculty Members

Alexandre Bouchard-Cote

Associate Professor, Statistics

Alexandre’s main field of research is in statistical machine learning. He is interested in the mathematical side of the subject as well as in applications in linguistics and biology. On the methodology side, he is interested in Monte Carlo methods, graphical models, non-parametric Bayesian statistics, randomized algorithms and variational inference. His favorite applications, both in linguistics and biology, are related to phylogenetics. Some examples of recent studies include: automated reconstruction of proto-languages; cancer phylogenetics; population genetics; and pedigrees, tree and alignment inference.

Departmental Website

Jenny Bryan

Associate Professor, Statistics

Jenny's is an applied statistician who focuses on data analysis and computing, especially in the R programming environment (one of the top programming languages used in data science). Her most recent work, in collaboration with colleagues in the Michael Smith Labs at UBC, produced an assay and analytical method, which allow for the detection of specific mutations in colorectal cancers – a development that will be key in guiding patient treatment (DOI: 10.1016/j.jmoldx.2015.09.003).

Departmental Website

Giuseppe Carenini

Associate Professor, Computer Science

Giuseppe has broad interdisciplinary interests. His research focuses on how natural language processing and information visualization can be effectively combined to support data analysis and decision making. More specifically, he has been working on mining and summarization of conversational data (emails, meetings, blogs); discourse parsing; the generation and summarization of evaluative text; and visual text analytic techniques for opinions and conversations.

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Christopher Carlsten

Associate Professor & Chair in Occupational and Environmental Lung Disease, Department of Medicine

Chris is interested in the effects of occupational and environmental exposure on respiratory diseases such as asthma, chronic obstructive pulmonary disease (COPD), cancer, and pleural disease. His laboratory leverages the power of controlled human exposure methodology and high-dimensional molecular analysis to focus on the respiratory and immunological health effects of inhaled environmental and occupational threats, using diesel exhaust, western red cedar, and phthalates as model inhalants.

Lab Website

Artem Cherkasov

Professor, Urologic Sciences, Vancouver Prostate Centre

Artem is interested in developing new therapies to treat prostate cancer and other diseases. Specifically, his work focuses on computer-aided drug design, employing artificial intelligence in structure-activity modeling, drug reprofiling, and development of novel cheminformatics and bioinformatics tools.

Departmental Website

Gabriela Cohen-Freue

Assistant Professor, Statistics

Gabriela works in statistical problems that usually appear in the analysis of proteomics and genomics data. In these applications, some variables may be measured with error; the number of features is much larger than the number of observations; the observations are not always independent; and outliers are present in the data. Gabriela develops statistical and computational methods to address some of these common issues in statistical genomics. In particular, she is interested in the development of robust estimation methods for sparse linear models.

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Cristina Conati

Professor, Computer Science

Cristina’s research integrates research in Artificial Intelligence (AI), Human Computer Interaction (HCI) and Cognitive Science to create intelligent interactive systems that can learn and adapt to the needs of their individual users, in order to delivery highly personalize interaction experiences. Recent examples of Cristina's research include creating serious e-games that can adapt to both a user's cognitive and affective states, learning effective user's interaction behaviors from data, and leveraging eye-tracking for user modeling

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Michael Friedlander

Professor, Computer Science and Mathematics

Michael’s research focuses on solving large-scale optimization problems, and spans algorithm design, analysis, and software implementation. His work includes applications in signal processing and machine learning.

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Kendall Ho

Professor, Department of Emergency Medicine, Faculty of Medicine

Kendall is a practicing emergency medicine specialist and lead Digital Emergency Medicine. His academic and research interests focuses on using digital technologies to improve healthcare delivery and raising digital health literacy. Examples of his research include using home sensors and wearables for remote patient monitoring, virtual health, social media for interprofessional communication and multicultural public engagement, and evidence informed policy translation in digital health.

Digital Emergency Medicine website

Laks Lakshmanan

Professor, Computer Science

Laks' research interests span a wide spectrum of topics in Database Systems and related areas, including: relational and object-oriented databases, advanced data models for novel applications, OLAP and data warehousing, database mining, data integration, semi-structured data and XML, directory-enabled networks, querying the WWW, information and social networks and social media, recommender systems, and personalization. A common theme underlying his research is to model problems not traditionally viewed as standard data management problems and bring the technology of efficient data management and mining to bear on them, thus pushing the frontiers of technology.

Departmental Website

Sara Mostafavi

Assistant Professor, Statistics

Sara develops and applies machine learning and statistical methods to study the genomics of complex diseases. In particular, she develops computational methods for combining multiple types of genomic data, such as gene expression and genotype data, and modeling prior biological pathways and networks for disentangling spurious from meaningful correlations.

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Tamara Munzner

Professor, Computer Science

Tamara's research interests include the development, evaluation, and characterization of information visualization systems and techniques. She has worked in a broad range of application domains, including genomics, evolutionary biology, geometric topology, computational linguistics, large-scale system administration, web log analysis, and journalism.

Departmental Website

Sarah Otto

Professor, Zoology, Biodiversity Research Centre

Understanding how evolution has led to the remarkable diversity of life is the key motivating force behind Sarah’s research. She combines mathematical models, experimental data analysis, and comparative phylogenetic studies to determine which evolutionary transitions are plausible, which are probable, and which are inaccessible.

Departmental Website

Yaniv Plan

Assistant Professor, Mathematics

Yaniv studies the mathematics of information, with a focus on compressed sensing and low-rank matrix recovery. He has a recent interest in deep learning. Much of his work studies the role of randomness in the analysis of high-dimensional data.

Website

Loren Rieseberg

Professor, Botany

Loren’s lab employs a combination of ecological, genomic, and bioinformatics approaches to study the origin and evolution of new species, exploits the genetic diversity of wild extremophile species for crop improvement, and combats invasive weeds, focusing on members of the sunflower family.

Departmental Website

Mark Schmidt

Assistant Professor, Computer Science

Mark works in the area of machine learning, which focuses on automatic discovery of patterns in large datasets. His theoretical focus is on the algorithms underlying these methods. He tries to make them scale up to huge datasets and work on developing generalizations that can model very complicated patterns. He has also worked on various practical applications, including several works on medical imaging.

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Andy Warfield

Associate Professor, Computer Science

Andy is broadly interested in the design and implementation of computer systems that support challenging data analysis tasks. In the past, his work has explored many aspects of enterprise and cloud-based infrastructure, including virtualization, storage, networking, security, and development frameworks. He is currently interested in building systems that better support audit and repeatability in order to provide "responsible" big data environments. He is also exploring the construction of large-scale datastores to support interactive analysis of genomic data.

Departmental Website

Will Welch

Professor, Statistics

Welch’s research spans computer-aided design of experiments, quality improvement, the design and analysis of computer experiments, statistical methods for drug discovery, and algorithms for statistical/machine learning. For a list of publications please see http://scholar.google.com/citations?user=Bus4Xi8AAAAJ&hl=en

Departmental Website

Ozgur Yilmaz

Professor, Mathematics

Ozgur’s work is on the theory of compressed sensing and related fields studying mathematics of information as well as the application of theory and computation in practical problems. The areas of applications he focuses on include seismic data analysis, audio signal processing, and analog-to-information conversion.

Departmental Website

Ruben Zamar

Professor, Statistics

Ruben's research interest lies in the areas of data mining and statistical computing, with specific focus on data and text mining, modeling data quality of high dimensional data, development of new robust procedures, and bioinformatics.

Departmental Website