Information for

David R. Cheriton Faculty Fellowships in Computer Science

The David R. Cheriton Faculty Fellowships are a prestigious recognition. The awards support the work of leading faculty in computer science with an emphasis on supporting research that addresses problems associated with designing and implementing efficient and reliable computing systems, along with their effective integration.

These fellowships help the University of Waterloo and the David R. Cheriton School of Computer Science continue their innovations in information technology teaching and research.

Current Cheriton Faculty Fellows


Urs Hengartner

photo of Professoe Urs Hengarter

Urs Hengartner is a member of the Cryptography, Security, and Privacy (CrySP) research group, the Centre for Applied Cryptographic Research and the Systems and Networking Group.

He has a PhD and MS in Computer Science from Carnegie Mellon University and a Dipl. Informatik-Ing. ETH from ETH Zürich.

His research interests are in information privacy and computer and network security with a focus on security and privacy challenges that arise in the context of smartphones and mobile applications. Urs and his students develop privacy-preserving technologies for location-based services and mobile applications to protect users from having to share their personal information with service and application providers.

Urs and his students also study implicit authentication for smartphones, where a smartphone continuously authenticates its owner based on the owner's behaviour without requiring deliberate actions by the owner. He has also worked on privacy-preserving location verification technologies, genomic privacy, and end-to-end voter-verifiable voting systems.

​Bernard Wong

photo of Barnard Wong

Bernard Wong is an Associate Professor and Associate Director of Graduate Studies at the David R. Cheriton School of Computer Science. He is a member of the Systems and Networking research group

He has a Ph.D. (2011) and M.Sc. (2007) in Computer Science from Cornell University, and a B.A.Sc. (2003) in Computer Engineering from the University of Waterloo.

Bernard's research interests span distributed systems and networking, with particular emphasis on problems involving cloud computing, consensus protocols, and distributed storage systems. Recent research projects include building a scalable and massively parallel consensus protocol, improving distributed file system performance through SDN/file system co-design, and designing a completely client-driven key-value store using one-sided RDMA.


Tim Brecht

Tim BrechtTim Brecht received a BSc in Computer Science from the University of Saskatchewan in 1983, an MMath from the University of Waterloo in 1985 and a PhD from the University of Toronto in 1994. Between 1993 and 1998, Tim was an Assistant and Associate Professor at York University in Toronto.

Tim joined the University of Waterloo in 1998, where he is currently an Associate Professor in the David R. Cheriton School of Computer Science.

In 2000 Tim spent a year on sabbatical at Hewlett-Packard Laboratories in Palo Alto, California. He took a leave of absence from Waterloo from 2001 to 2002 to continue his work at Hewlett-Packard as a Research Scientist working on high-performance Internet server design. He later spent one year on sabbatical (2008–2009) as Invited Professor with the LABOS group at École Polytechnique Fédérale de Lausanne (EPLF) in Switzerland. During his most recent sabbatical (2015–2016) he was a Visiting Research Scientist at Netflix, where he worked with the Open Connect Architecture Group to significantly increase the throughput of Netflix streaming servers. Tim has also worked with other companies, including Alias|Wavefront, Huawei, IBM, Intel, Morgan Stanley Dean Witter, Real Networks, Sun Microsystems, and the Toronto Stock Exchange.

Tim’s research focuses mainly on understanding and improving the performance of computer systems and networks. This has led to a research career where he has published papers in a wide range of venues covering a variety of topics, including high-performance Internet systems and services, operating systems, parallel and distributed systems, garbage collection, and networking. Recent research projects include understanding and improving HTTP streaming video services, characterizing and improving 802.11 (Wi-Fi) networks, and developing systems to better support the Internet of Things. Tim was a nominee for the 3M Outstanding Canadian Instructor Award in 1998, was awarded an NSERC Discovery Accelerator Supplement in 2012 and a Cheriton Faculty Fellowship in 2016.

Charles Clarke

Charlie ClarkeCharles (Charlie) Clarke is a Professor in the David R. Cheriton School of Computer Science, where he has been faculty since 1999. Previously, he was an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Toronto.

He has a BSc in Mathematics and Computer Science from Memorial University (1986), and an MMath (1990) and a PhD (1996), both in Computer Science from the University of Waterloo.

Charlie’s research addresses problems across the broad field of information retrieval and search. His work is primarily of an applied nature, with results validated through implementation, experimentation and performance measurement. He has published widely on topics such as document ranking, question answering, text mining, classification, clustering, filtering, summarization, indexing, query processing, efficiency, statistical NLP, user behaviour modelling, document structure and XML. He is a co-author of the graduate textbook Information Retrieval: Implementing and Evaluating Search Engines (MIT Press, 2010). From 2013 to 2016 he served as the Chair of the ACM’s Special Interest Group on Information Retrieval. He is currently Co-Editor-in-Chief of the Information Retrieval Journal.

Charlie has a longstanding interest in evaluation methodologies for information retrieval systems. His efforts have been directed toward creating evaluation measures and test collections. Through his coordination of evaluation efforts sponsored by the US National Institute for Standards and Technology, he has created and validated test collections to evaluate web search, web spam, retrieval diversity, contextual suggestion, and high-recall retrieval.

Recent research projects have included efforts to improve the performance of multi-stage rankers by learning efficiency/effectiveness trade-offs from static query and collection features. In collaboration with colleagues in Management Science, he has been developing and validating models of searchers interacting with search engines. In other recent work, he has explored the infrastructure needed to support search and other transactional web services for future interplanetary colonists.

Charlie has also been a consultant and software developer. From 1985 to 1998 he worked for an ocean engineering company developing remote-sensing, digital signal processing and image-processing applications. From 1992 to 1993 he worked for a systems integration firm developing point-of-sale systems and network software. In 1998, he co-founded isagn Inc. a privately held company that created and supported digital library systems. During a sabbatical in 2006 he visited Microsoft, where he worked on what became the Bing search engine. During a sabbatical from 2016–2017 he visited Facebook, where he worked on machine learning and data analytics for search.


Dan Brown

photo of Dan BrownDan Brown is an Associate Professor in the David R. Cheriton School of Computer Science at the University of Waterloo, where he has been a faculty member since 2000. Dan earned his bachelor's degree in Math with Computer Science from MIT, and his PhD in Computer Science from Cornell.

Before coming to Waterloo, he spent a year working on the Human and Mouse Genome Projects as a post-doc at the Whitehead Institute / MIT Center for Genome Research (now the Broad Institute).

Dan's primary research interests are designing algorithms for understanding biological evolution, and applying bioinformatics ideas to problems in music information retrieval. For example, a few years ago he did work on identifying rhyming patterns in rap music lyrics, and using those patterns to predict song authorship; more recently, he has studied how cleverness in rhyme and meter in song lyrics predicts the success of a pop song. He also studies problem gambling prevention, making computers write poetry, and a host of other topics.

Pascal Poupart

photo of Pascal PoupartPascal Poupart is an Associate Professor in the David R. Cheriton School of Computer Science at the University of Waterloo, Waterloo (Canada). He received the BSc in Mathematics and Computer Science at McGill University, Montreal (Canada) in 1998, the MSc in Computer Science at the University of British Columbia, Vancouver (Canada) in 2000 and the PhD in Computer Science at the University of Toronto, Toronto (Canada) in 2005.

His research focuses on the development of algorithms for reasoning under uncertainty and machine learning with application to health informatics and natural language processing. He is most well known for his contributions to the development of approximate scalable algorithms for partially observable Markov decision processes (POMDPs) and their applications in real-world problems, including automated prompting for people with dementia for the task of handwashing and spoken dialog management.

Other notable projects that his research team are currently working on include chatbots for automated personalized conversations and wearable analytics to assess modifiable health risk factors. He co-founded Veedata, a startup that provides analytics services to the insurance industry and the researcher market.

Pascal Poupart received a David R. Cheriton Faculty Award in 2015, an Early Researcher Award (a competitive honor for top Ontario researchers) by the Ontario Ministry of Research and Innovation in 2008. He was also a co-recipient of the Best Paper Award Runner Up at the 2008 Conference on Uncertainty in Artificial Intelligence (UAI) and the IAPR Best Paper Award at the 2007 International Conference on Computer Vision Systems (ICVS). He also serves on the editorial boards of the Journal of Machine Learning Research (JMLR) (2009 - present) and the Journal of Artificial Intelligence Research (JAIR) (2008 - 2011). His research collaborators include Huawei, Google, Intel, Kik Interactive, In the Chat, Slyce, HockeyTech, the Alzheimer Association, the UW-Schlegel Research Institute for Aging, Sunnybrook Health Science Centre and the Toronto Rehabilitation Institute.

Previous Cheriton Faculty Fellows

Cheriton Faculty Fellows Year
Michael Godfrey, Jesse Hoey 2014–17
Tamer Oszu, Ihab Ilyas 2013–16 
Raouf Boutaba, Kate Larson 2012–15 
Gladimir Baranoski, Peter Forsyth 2011–14     
Robin Cohen, Alejandro Lopez-Ortiz 2010–13
Ken Salem, John Watrous 2009–12  
Charles Clarke, Yuying Li 2008–11 
 Frank Tompa, Raouf Boutaba 2007–10