David Gordon, University of Alberta

Research

process modeling machine learning model predictive control energy conversion systems combustion engines realtime control sensors fuel cells

Latest papers

Safe deep reinforcement learning in diesel engine emission control.
Proceedings of the Institution of Mechanical Engineers. Part I, Journal of systems and control engineering · 2023
Support vector machine based emissions modeling using particle swarm optimization for homogeneous charge compression ignition engine.
International journal of engine research · 2023 · first author

All 2 publications

Latest funding

Machine learning based control in transportation and smart agriculture: enhancing performance, efficiency and robustness
NSERC · 2024 · Principal investigator
$35,000
Machine Learning Control for Hydrogen integration in Heavy-duty engines
NSERC · 2024 · Co-investigator
$190,000
Machine learning based control in transportation and smart agriculture: enhancing performance, efficiency and robustness
NSERC · 2024 · Principal investigator
$12,500

All 3 grants and awards

2 publications.

01

Safe deep reinforcement learning in diesel engine emission control.

Norouzi A, Shahpouri S, Gordon D, Shahbakhti M, Koch CR

Proceedings of the Institution of Mechanical Engineers. Part I, Journal of systems and control engineering2023

DOI: 10.1177/09596518231153445 PMID: 37692899

02

Support vector machine based emissions modeling using particle swarm optimization for homogeneous charge compression ignition engine.

Gordon D, Norouzi A, Blomeyer G, Bedei J, Aliramezani M, Andert J, Koch CR

International journal of engine research2023First author

DOI: 10.1177/14680874211055546 PMID: 36776419

Machine learning based control in transportation and smart agriculture: enhancing performance, efficiency and robustness

Principal investigatorNSERC2024Discovery Grants Program - Individual

Principal investigators: Gordon, David

Keywords: machine learning; model predictive control; energy conversion systems; combustion engines; realtime control; process modeling; sensors; process modeling; fuel cells; mechatronics

$35,000

Machine Learning Control for Hydrogen integration in Heavy-duty engines

Co-investigatorNSERC2024Alliance Grants

Principal investigators: Koch, Charles CR

Keywords: air quality; alternative fuels; combustion; controls; emissions; fuel cells; hydrogen; machine learning; transportation

$190,000

Machine learning based control in transportation and smart agriculture: enhancing performance, efficiency and robustness

Principal investigatorNSERC2024Discovery Launch Supplement

Principal investigators: Gordon, David

Keywords: machine learning; model predictive control; energy conversion systems; combustion engines; realtime control; process modeling; sensors; process modeling; fuel cells; mechatronics

$12,500

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

Mahdi Shahbakhti

Mechanical Engineering

1 shared papers, latest 2023

Write to this professor

A short, specific email works best. This draft uses one of their recent papers; replace the parts in brackets with your own details before sending.

Applying for

Paper to mentionMention their NSERC grant from 2024

Subject: Prospective PhD student: process modeling Dear Professor Gordon, My name is [your name], and I am a [your current degree or role] at [your institution]. I am applying for a PhD position starting in [term and year]. I read your paper "Safe deep reinforcement learning in diesel engine emission control." (2023), and it connects closely to my own work on [your research topic]. [One or two sentences on what you did and what you learned.] I also saw your NSERC-funded project "Machine learning based control in transportation and smart agriculture: enhancing performance, efficiency and robustness" (2024), and I would be glad to contribute to work in that direction. Are you accepting new PhD students for [term and year]? I have attached my CV and transcripts, and I would be glad to talk at a time that suits you. Thank you for your time. Kind regards, [your name]