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Foutse Khomh
Eng., Ph.D (UdeM), Postdoc (Queen's U)
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Full Professor
Department of Computer Engineering and Software Engineering
Phone: (514) 340-4711 Ext. 4233 Fax: (514) 340-5139 Room: M-4123
Areas of expertise
Cybersecurity Artificial intelligence Information technology Software engineering Software and development

Research interests and affiliations

Research interests

Research interests of Professor Foutse Khomh include software maintenance and evolution, cloud engineering, service-centric software engineering, machine learning systems engineering, and dependable and trustworthy artificial intelligence.

Affiliation(s)

Publications

Recent publications
Book chapter
Jamshidi, S., Nikanjam, A., Hamdaqa, M.A. & Khomh, F. (2023). Attack Detection by Using Deep Learning for Cyber-Physical System. In Artificial Intelligence for Cyber-Physical Systems Hardening (Vol. Engineering cyber-physical sytems and critical infrastructures, pp. 155-179). Springer. Retrieved from https://doi.org/10.1007/978-3-031-16237-4_7
Conference paper
Humeniuk, D., Antoniol, G. & Khomh, F. (2022). ***AmbieGen tool at the SBST 2022 Tool Competition. Paper presented at the 15th Search-Based Software Testing Workshop (SBST 2022), En ligne / Online (pp. 43-46). Retrieved from https://doi.org/10.1145/3526072.3527531
Journal article
Verdi, M., Sami, A., Akhondali, J., Khomh, F., Uddin, G. & Motlagh, A.K. (2022). An Empirical Study of C plus plus Vulnerabilities in Crowd-Sourced Code Examples. IEEE Transactions on Software Engineering, 48(5), 1497-1514. Retrieved from https://doi.org/10.1109/tse.2020.3023664
Journal article
Uddin, G., Guéhénuc, Y.-G., Khomh, F. & Roy, C.K. (2022). An Empirical Study of the Effectiveness of an Ensemble of Stand-alone Sentiment Detection Tools for Software Engineering Datasets. ACM Transactions on Software Engineering and Methodology, 31(3), 38 pages. Retrieved from https://doi.org/10.1145/3491211
See all publications (216)

Biography

Foutse Khomh is a Full Professor in the Department of Computer Engineering at École Polytechnique de Montréal, where he leads the SWAT team on software analytics and cloud engineering research. He is a Canada CIFAR AI Chair on Trustworthy Machine Learning Software Systems and FRQ-IVADO Research Chair on Software Quality Assurance for Machine Learning Applications. Prior to these positions, he was a Research Fellow at Queen's University (Canada), working with the Software Reengineering Research Group and the NSERC/RIM Industrial Research Chair in Software Engineering of Ultra Large Scale Systems. He received a  Ph.D.  in Computer Science from the University of Montreal (Dean's Honour List). He also received a Master's degree in Software Engineering from the National Advanced School of Engineering (Cameroon) and a D.E.A (Master's degree) in Mathematics from the University of Yaoundé I (Cameroon). He has experience as a Software Designer at different companies doing research, system design, and project management. 

His research interests include software maintenance and evolution, cloud engineering, service-centric software engineering, empirical software engineering, and software analytics. He received a CS-Can/Info-Can Outstanding Young Computer Science Researcher Prize for 2019 and the ADRIQ-RSRI 2022 Innovation Award. He has published several papers in international conferences and journals, including ICSME, ASE, SANER, ICWS, HPCC, ISSRE, JSS, JSEP, EMSE, and TSE. His work has received four 10-Year Most Influential Paper Awards, six Best/Distinguished Paper Awards, and more than sixteen nominations for Best Paper Awards. He has served on the program committees of several international conferences including ICSME, SANER, MSR, ICPC, SCAM, ESEM and has reviewed for top international journals such as SQJ, EMSE, TSE, and TOSEM. He is on the Review Board of EMSE. He is program chair for Satellite Events at SANER 2015, program co-chair of SCAM 2015, ICSME 2018, PROMISE 2019, and ICPC 2019, general chair of ICPC 2018 and SCAM 2020, and co-general chair of SANER 2020. He is (has been) on the steering committee of PROMISE, SANER (chair), ICPC (chair), MSR, and ICSME (vice-chair). He is one of the organizers of the RELENG workshop series, a co-founder of the NSERC CREATE SE4AI: A Training Program on the Development, Deployment, and Servicing of Artificial Intelligence-based Software Systems, and is an Associate Editor for IEEE Software, EMSE, and JSEP journals. He is a member of ACM, IEEE, and IEEE Computer Society.

Link(s) of interest

Supervision at Polytechnique

COMPLETED

  • Ph.D. Thesis (6)

    • Abidi, M. (2021). Multi-Language Design Smells: Characteristics, Prevalence, and Impact (Ph.D. Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/6304/
    • An, L. (2019). Understanding the Impact of Release Processes and Practices on Software Quality (Ph.D. Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/3857/
    • Kermansaravi, Z. (2019). Linguistic Anti-Patterns: Impact Analysis on Code Quality (Ph.D. Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/3950/
    • Morales Alvarado, R. (2017). Automated improvement of software design by search-based refactoring (Ph.D. Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2878/
    • Saborido Infantes, R. (2017). Assisting developers and users in developing and choosing efficient mobile device apps (Ph.D. Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2846/
    • Soh, Z. (2015). Improving Program Comprehension and Recommendation Systems Using Developers' Context (Ph.D. Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2034/

  • Master's Thesis (18)

    • Yousefifeshki, F. (2022). Studying the Practices and Challenges of Developing Hardware Description Language Programs (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/10340/
    • Hamidi, A. (2021). Machine Learning Engineering: An Exploratory Study of Challenges and Practices (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/6569/
    • Humeniuk, D. (2021). A Search-Based Framework for Automatic Generation of Testing Environments for Cyber-Physical Systems (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/9144/
    • Openja, M. (2021). An Empirical Study of Testing and Release Practices for Machine Learning Software Systems (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/9177/
    • Vahedi, M. (2021). TechTube: Summarizing Relevant Parts from Technical Videos (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/6290/
    • Jebnoun, H. (2020). Understanding the Impact of Poor Coding Practices on the Quality of Deep Learning Systems (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/5542/
    • Msika, S. (2020). Renforcement de systèmes de détection d'intrusions par des attaques GAN et métaheuristiques (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/4192/
    • Rivera-Landos, E. (2020). On the Challenges of Implementing Machine Learning Systems in Industry (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/5538/
    • Ben Braiek, H. (2019). Towards Debugging and Testing Deep Learning Systems (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/3959/
    • Barbez, A. (2018). Deep Learning Structural and Historical Features for Anti-Patterns Detection (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/3724/
    • Barrak, M.A. (2018). Just-in-Time Detection of Protection-Impacting Changes on Wordpress and Mediawiki (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/3684/
    • Foundjem, A.T. (2017). Towards improving the reliability of live migration operations in openstack clouds (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2498/
    • Musavi Mirkalaei, S.P. (2017). API Failures in Openstack Cloud Environments (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2715/
    • Abtahizadeh, S.A. (2016). Understanding the Impact of Cloud Computing Patterns on Performance and Energy Consumption (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2296/
    • Bani, B. (2016). Understanding the Impact of Databases on the Energy Efficiency of Cloud Applications (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2256/
    • Mlouki, O. (2016). On the Detection of Licenses Violations in the Android Ecosystem (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2124/
    • Saboury, A. (2016). On the fault-proneness of Javascript code smells (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2445/
    • An, L. (2015). Improving Bug Triaging Using Software Analytics (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/1908/

Awards and honors

News about Foutse Khomh

NEWS | December 7, 2021
Artificial Intelligence: a new Canada-CIFAR Chair in AI for Professor Foutse Khomh | Read
NEWS | August 17, 2021
Two Polytechnique professors ranked among the world’s most productive software engineering researchers | Read
NEWS | June 14, 2021
NSERC CREATE program: Polytechnique Montréal involved in two training and mentoring programs | Read
NEWS | February 24, 2021
50 Polytechnique Montréal researchers among the top 2% most cited in their respective fields | Read
NEWS | February 18, 2021
Software Engineering: Professors Antoniol and Khomh Receive Award for Most Influential Article of the Decade | Read
NEWS | September 23, 2020
Polytechnique Montréal’s Professor Foutse Khomh wins research excellence award | Read
NEWS | April 17, 2019
Appointments to three FRQ-IVADO research chairs for diversity and equity in data science | Read
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Press review about Foutse Khomh

February 24, 2023, Québec Science, Comment augmenter la fiabilité de l'intelligence artificielle? À l'occasion de son 150e anniversaire, Polytechnique Montréal vous invite à découvrir ses huit différents pôles de recherche. Rencontre avec Foutse Khohm, professeur au Département de génie informatique et génie logiciel, qui revient sur les recherches menées à Polytechnique pour augmenter la fiabilité de l'intelligence artificielle.
February 16, 2023, ICI Radio-Canada | L'heure du monde, ChatGPT et la chanson québécoise : Reportage de Louis-Philippe Ouimet Foutse Khohm, professeur titulaire au Département de génie informatique et génie logiciel, commente si l'intelligence artificielle serait en mesure de remplacer les artistes (2:02).
February 16, 2023, ICI Radio-Canada Télé | Le Téléjournal avec Céline Galipeau, L'IA devient artiste Foutse Khomh, professeur titulaire au Département de génie informatique et génie logiciel, discute du potentiel des outils d'intelligence artificielle dans le domaine de la musique.
January 29, 2023, La Presse, Les robots sont-ils sur le point de mener le monde ? Est-ce que les robots sont en voie de remplacer les professionnels ? Foutse Khomh, professeur titulaire au département de génie informatique et génie logiciel, répond à cette question. 
November 30, 2020, CScience IA, La recherche aérospatiale fait bien plus de place à l'IA Les explications de Foutse Khomh, professeur titulaire au Département de génie informatique et génie logiciel de Polytechnique Montréal et chercheur du projet DEEL (DEpendable Explainable Learning).
January 27, 2020, Radio-Canada, RDI économie - Cybersécurité : les entreprises ne sont pas prêtes Entrevue de Foutse Khomh, professeur agrégé au Département de génie informatique et génie logiciel de Polytechnique Montréal (1:14).
Other mentions: Cybersécurité : les entreprises canadiennes ne ressentent pas l'urgence d'agir, Cybersécurité : pas une priorité pour les entreprises canadiennes, selon une étude, Pratiques en matière de sécurité: pas encore une priorité pour les entreprises | Grenier aux nouvelles, Pénélope - Bulletin régional - CBF (4:42), Le Téléjournal - Bulletin de nouvelles du mardi 28 janvier 2020 (34:47), Portrait des TI en entreprise au Canada : résultats de l'étude NOVIPRO/Léger
March 20, 2019, Québec Science, Tragédies aériennes: qu'est-ce que le logiciel MCAS? Le professeur Foutse Khomh, du Département de génie informatique et de génie logiciel de Polytechnique Montréal, explique ce qu'est un MCAS (pour Maneuvering Characteristics Augmentation System),  un logiciel anti-décrochage dont il est beaucoup question dans le dossier des récentes tragédies aériennes impliquant des appareils Boeing 737 Max. 
March 16, 2019, Le Devoir, Peut-on avoir confiance en nos avions? Le professeur au Département de génie informatique et de génie logiciel de Polytechnique Montréal, Foutse Khomh, commente le processus de certification dans l'industrie aérospatiale.  
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