People

PDELab brings together researchers across numerical methods, scientific machine learning, quantum computing, and high-performance computing, all working towards developing simulation tools applicable to real-world problems.

Principal Investigator

Prof. David Del Rey Fernández

Associate Professor, Department of Applied Mathematics, University of Waterloo

Pratt & Whitney Canada Chair in Industrial Artificial Intelligence

DegreePhD, University of Toronto
OfficeMC 6318

David C. Del Rey Fernández is an Associate Professor in the Department of Applied Mathematics at the University of Waterloo, the Pratt & Whitney Canada Research Chair in Industrial Artificial Intelligence, an Associate Director of the Waterloo Institute for Sustainable Aeronautics, and a Research Cluster Lead (Modelling) for the Future Cities Institute. He is also the Graduate Officer of the Computational Mathematics Program and serves on the Advisory Committee for Women in Mathematics at the University of Waterloo and the Canvassing Committee for the Association for Women in Mathematics.

He obtained his PhD from the University of Toronto Institute for Aerospace Studies in 2015 and was a postdoctoral fellow and then research scientist at NASA Langley Research Center through the National Institute of Aerospace from 2016 to 2021. He is a recipient of the CAIMS/PIMS Early Career Award in Applied Mathematics (2024), the Faculty of Mathematics Golden Jubilee Research Excellence Award (2025), and the Ontario Early Researcher Award (2026).

Prof. Del Rey Fernández develops efficient and robust numerical methods and algorithms for a broad class of time-dependent partial differential equations (PDEs), with mathematical guarantees and applicability to high-performance computing systems. His research focuses on mathematically rigorous numerical frameworks, with an emphasis on numerical methods with mathematical guarantees; mesh adaptation; geometric complexity and moving meshes; machine-learning-accelerated numerical methods; machine learning for automation and increased efficiency; and quantum computing algorithms.

His projects involve industry partners such as Pratt & Whitney Canada, Bombardier, NVIDIA and Ansys as well as partnerships with various Canadian municipalities; collaborators in government labs, including NRC, NASA, INRIA, Sandia National Laboratories, and Argonne National Laboratory; and various academic partners.

Prof. David Del Rey Fernández

Postdoctoral Researchers

2
Sacha Cardonna

Sacha Cardonna

He/him

Applied Mathematics

Modeling, numerical analysis and scientific computing for nonlinear PDEs and multiphysics problems

MC 6434
Zelalem Arega Worku

Zelalem Arega Worku

He/him

Applied Mathematics

Development and implementation of robust and efficient numerical methods for discretization of partial differential equations

MC 6101

PhD Students

6
Dongze Li

Dongze Li

He/him

Applied Mathematics

Entropy-Stable Space-Time Discretizations

MC 6408
Jiajun Fang

Jiajun Fang

He/him

Applied Mathematics

Quantum Algorithms

MC 6331
Kunal Ghosh

Kunal Ghosh

He/him

Applied Mathematics

Adaptive Mesh Refinement

MC 6471
Lucas Bennett

Lucas Bennett

He/him

Applied Mathematics

Efficient time-stepping algorithms

MC 6428
Scott Holtshousen

Scott Holtshousen

He/him

Applied Mathematics

Reinforcement learning and artificial intelligence for multidisciplinary design analysis and optimization

MC 6471
Xinze Ren

Xinze Ren

She/her

Applied Mathematics

Numerical Methods and Scientific Computing

MC 6331

Master's Students

11
Adam Wieler

Adam Wieler

He/him

Computational Mathematics

Machine learning to accelerate numerical methods

MC 6478
Alaa Elsayed

Alaa Elsayed

He/him

Applied Mathematics

Graph-based surrogate models for PDEs

MC 6471
Alireza Laalmanesh

Alireza Laalmanesh

He/him

Computational Mathematics

Operations Research & Optimization

MC 6478
Andrew Gray

Andrew Gray

He/him

Applied Mathematics

Machine learning enhanced numerical methods

NA
Ayda Moraveji

Ayda Moraveji

She/her

Computational Mathematics

Decision-Focused Learning and Mathematical Optimization

MC 6478
Devin Blankespoor

Devin Blankespoor

He/him

Applied Mathematics

Quantum Algorithms for Nonlinear PDEs

Gaia Noseworthy

Gaia Noseworthy

They/them

Applied Mathematics

Quantum Stochastic Collocation

MC 6432
Levi Prost

Levi Prost

He/him

Computational Mathematics

Surrogate PDE Solvers

MC 6478
Parth

Parth

He/him

Applied Mathematics

Scientific Machine Learning and Agentic Operations

MC 6471
Rupam Ghosh

Rupam Ghosh

He/him

Applied Mathematics

Port Hamiltonian modelling and control of pipe network systems

MC6501
Venkatesh Sangiah Karuppiah

Venkatesh Sangiah Karuppiah

He/him

Applied Mathematics

Higher order methods for Fluid Structure Interaction and High-Performance Computing

MC 6471

Undergraduate Student

2
Daniel Kohn

Daniel Kohn

He/Him

Mathematics

Quantum State Preparation and Algorithms for PDEs

NA
Len Dizard

Len Dizard

He/Him

Mathematics

Growth Management Platform

NA

Alumni

Former members of PDELab and where they are now. Select a year to view its graduates.

20262 graduates
Joshua Joseph George
DegreeMMath in Applied Mathematics
First DestinationPhD @ University of Michigan
20251 graduate
NameDegreeThesisFirst Destination
Vyom PatelMMath in Applied Mathematics (Quantum Information)Quantum Algorithms for PDEs via Summation-by-Parts Discretisations Research Scientist @ BEIT
Vyom Patel
DegreeMMath in Applied Mathematics (Quantum Information)
First DestinationResearch Scientist @ BEIT

One lab, many origins

Gathering talent from around the world.

We bring together talented researchers from cities around the world, all connected to our home base in Waterloo, Ontario.

PDELab
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