Faculty profile
Paulo Alencar
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Latest papers
Assessing ML classification algorithms and NLP techniques for depression detection: An experimental case study.
PloS one · 2025
A framework for spatial-temporal cluster evolution representation and analysis based on graphs.
Scientific reports · 2024
Leveraging mHealth Technologies for Public Health.
JMIR public health and surveillance · 2024
Latest funding
- $108,000
Static and Dynamic High-Integrity Architectural Application Frameworks
NSERC · 2015 · Principal investigator
- $150,000
Recombinant and evolutionary high-level software architectures: Design, integration, evolution and analysis
NSERC · 2009 · Principal investigator
- $448,500
An architecture, meta-model and easy-to-use toolkit for the creation of web-based geomatics information
NSERC · 2009 · Co-investigator
11 publications.
Assessing ML classification algorithms and NLP techniques for depression detection: An experimental case study.
Lorenzoni G, Tavares C, Nascimento N, Alencar P, Cowan D
A framework for spatial-temporal cluster evolution representation and analysis based on graphs.
Portugal I, Alencar P, Cowan D
Leveraging mHealth Technologies for Public Health.
Velmovitsky PE, Kirolos M, Alencar P, Leatherdale S, Cowan D, Morita PP
Application of a mobile health data platform for public health surveillance: A case study in stress monitoring and prediction.
Velmovitsky PE, Alencar P, Leatherdale ST, Cowan D, Morita PP
Can heart rate variability data from the Apple Watch electrocardiogram quantify stress?
Velmovitsky PE, Lotto M, Alencar P, Leatherdale ST, Cowan D, Morita PP
Using apple watch ECG data for heart rate variability monitoring and stress prediction: A pilot study.
Velmovitsky PE, Alencar P, Leatherdale ST, Cowan D, Morita PP
A conceptual IoT-based early-warning architecture for remote monitoring of COVID-19 patients in wards and at home.
Paganelli AI, Velmovitsky PE, Miranda P, Branco A, Alencar P, Cowan D, Endler M, Morita PP
A face recognition software framework based on principal component analysis.
Peng P, Portugal I, Alencar P, Cowan D
Convergence of Precision Medicine and Public Health Into Precision Public Health: Toward a Big Data Perspective.
Velmovitsky PE, Bevilacqua T, Alencar P, Cowan D, Morita PP
Knowledge reuse in software projects: Retrieving software development Q&A posts based on project task similarity.
Melo G, Oliveira T, Alencar P, Cowan D
Static and Dynamic High-Integrity Architectural Application Frameworks
Principal investigators: Alencar, Paulo
Recombinant and evolutionary high-level software architectures: Design, integration, evolution and analysis
Principal investigators: Alencar, Paulo
An architecture, meta-model and easy-to-use toolkit for the creation of web-based geomatics information
Principal investigators: Cowan, Donald
Evolutionary concern-based extensions: A flexible and modular approach for the design, composition and customization of high-integrity architectural application frameworks
Principal investigators: Alencar, Paulo
Next-generation declarative enterprise frameworks based on advanced separation of concerns
Principal investigators: Cowan, Donald
Integration and analysis of high-level software architecture components: interfaces, views, wrappers and contracts
Principal investigators: Alencar, Paulo
Prophylactic program design: an approach to next generation legacy web-based software applications
Principal investigators: Cowan, Donald
The validation of high-level software descriptions
Principal investigators: Alencar, Paulo
Component-based software systems- a development approach using viewpoints
Principal investigators: Cowan, Donald
From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.
Frequent collaborators
- Scott Leatherdale and Paulo Alencar: 1 shared paper
- Peng Peng and Paulo Alencar: 1 shared paper
- Computer Science, David R. Cheriton School of
- Mechanical and Mechatronics Engineering
- School of Public Health and Health Systems
Co-authors at University of Waterloo, colored by department. Thicker lines mean more shared papers; select anyone to open their profile and their own map.
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