Michael Kokkolaras, McGill University

Research

computational engineering design numerical optimization distributed multidisciplinary optimization bayesian optimization derivative-free optimization data-driven modeling scientific and physics-informed machine learning generative design

Latest papers

Weekly Nowcasting of New COVID-19 Cases Using Past Viral Load Measurements.
Viruses · 2022 · senior author
Using Parallel Coordinates in Optimization of Nano-Particle Drug Delivery.
Journal of biomechanical engineering · 2022 · senior author
A Dual Nanoparticle Delivery Strategy for Enhancing Drug Distribution in Cancerous Tissue.
Journal of biomechanical engineering · 2020 · senior author

All 8 publications

Latest funding

Bayesian optimization with automated machine-learned models for computational engineering design
NSERC · 2024 · Principal investigator
$53,000
ACI-OPT: Aircraft Component Installation Optimization
NSERC · 2022 · Co-investigator
$136,500
Data-driven optimization for enhanced computational engineering design
NSERC · 2018 · Principal investigator
$192,000

All 11 grants and awards

8 publications.

01

Weekly Nowcasting of New COVID-19 Cases Using Past Viral Load Measurements.

Khalil A, Al Handawi K, Mohsen Z, Abdel Nour A, Feghali R, Chamseddine I, Kokkolaras M

Viruses2022Senior author

DOI: 10.3390/v14071414 PMID: 35891394

02

Using Parallel Coordinates in Optimization of Nano-Particle Drug Delivery.

Kipouros T, Chamseddine I, Kokkolaras M

Journal of biomechanical engineering2022Senior author

DOI: 10.1115/1.4052578 PMID: 34590693

03

A Dual Nanoparticle Delivery Strategy for Enhancing Drug Distribution in Cancerous Tissue.

Chamseddine IM, Kokkolaras M

Journal of biomechanical engineering2020Senior author

DOI: 10.1115/1.4047657 PMID: 32601692

04

Multi-objective optimization of tumor response to drug release from vasculature-bound nanoparticles.

Chamseddine IM, Frieboes HB, Kokkolaras M

Scientific reports2020Senior author

DOI: 10.1038/s41598-020-65162-2 PMID: 32427977

05

Sound simulation-based design optimization of brass wind instruments.

Tournemenne R, Petiot JF, Talgorn B, Gilbert J, Kokkolaras M

The Journal of the Acoustical Society of America2019Senior author

DOI: 10.1121/1.5111346 PMID: 31255147

06

Design Optimization of Tumor Vasculature-Bound Nanoparticles.

Chamseddine IM, Frieboes HB, Kokkolaras M

Scientific reports2018Senior author

DOI: 10.1038/s41598-018-35675-y PMID: 30538267

07

Assessment of structural and hemodynamic performance of vascular stents modelled as periodic lattices.

Prithipaul PKM, Kokkolaras M, Pasini D

Medical engineering & physics2018

DOI: 10.1016/j.medengphy.2018.04.017 PMID: 29759946

08

Nanoparticle Optimization for Enhanced Targeted Anticancer Drug Delivery.

Chamseddine IM, Kokkolaras M

Journal of biomechanical engineering2018Senior author

DOI: 10.1115/1.4038202 PMID: 29049542

Bayesian optimization with automated machine-learned models for computational engineering design

Principal investigatorNSERC2024Discovery Grants Program - Individual

Principal investigators: Kokkolaras, Michael

Keywords: computational engineering design; numerical optimization; distributed multidisciplinary optimization; bayesian optimization; derivative-free optimization; data-driven modeling; scientific and physics-informed machine learning; generative design; aerospace, energy, and healthcare systems applications; optimization applications of quantum computing

$53,000

ACI-OPT: Aircraft Component Installation Optimization

Co-investigatorNSERC2022Alliance Grants

Principal investigators: Liscouet-Hanke, Susan US

Keywords: aircraft design; component installation; conceptual design; mdo; optimization; system integration

$136,500

Data-driven optimization for enhanced computational engineering design

Principal investigatorNSERC2018Discovery Grants Program - Individual

Principal investigators: Kokkolaras, Michael

$192,000

Development and Analysis of a Novel Lightweight Monocoque Architecture for Electric Delivery Trucks

Principal investigatorNSERC2017Engage Grants Program

Principal investigators: Kokkolaras, Michael

$25,000

Digital multidisciplinary analysis and design optimization platform for aeroderivative gas turbines

Principal investigatorNSERC2017Collaborative Research and Development Grants

Principal investigators: Kokkolaras, Michael

$785,000

Surrogate Models for Maximizing Net Present Value of Renewable Energy Sources

Principal investigatorNSERC2016Engage Plus Grants Program

Principal investigators: Kokkolaras, Michael

$12,500

Surrogate Models for Maximizing Net Present Value of Renewable Energy Sources

Principal investigatorNSERC2015Engage Grants Program

Principal investigators: Kokkolaras, Michael

$25,000

Additive manufacturing optimization and simulation platform for repairing and re-manufacturing of aerospace components

Co-investigatorNSERC2015Collaborative Research and Development Grants

Principal investigators: Zhao, Yaoyao

$320,000

NSERC CREATE in Competitive Manufacturing for the Aerospace Industry: Technology and Design

Co-investigatorNSERC2014Collaborative Research and Training Experience

Principal investigators: Yue, Stephen

$1,257,000

Coordination Methodology for an Industrial Multilevel Multidisciplinary Design Optimization Framework

Principal investigatorNSERC2014Engage Grants Program

Principal investigators: Kokkolaras, Michael

$25,000

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

Damiano Pasini

Mechanical Engineering

1 shared papers, latest 2018

Write to this professor

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Applying for

Paper to mentionMention their NSERC grant from 2024

Subject: Prospective PhD student: computational engineering design Dear Professor Kokkolaras, 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 "Weekly Nowcasting of New COVID-19 Cases Using Past Viral Load Measurements." (2022), 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 "Bayesian optimization with automated machine-learned models for computational engineering design" (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]