SEMLA 2024, June 12 – 13, 2024

The Software Engineering for Machine Learning Applications (SEMLA) international symposium aims at bringing together leading researchers and practitioners in software engineering and machine learning to reflect on and discuss the challenges and implications of engineering complex data-intensive software systems.

From the early attempts in the late 80s (such as the MAIA project) to the most recent breakthroughs in applications of deep learning, the human kind dreams of building machines capable of learning new tasks, adapting to the environment, and evolving. Yet this exploration poses important computational, practical and ethical challenges. Failure to properly address these challenges in such software intensive systems can lead to catastrophic consequences. Consider, for example, the recent human toll incidence caused by the $47-million Michigan Integrated Data Automated System (MiDAS) (see Broken: The human toll of Michigan’s unemployment fraud saga), or the recent finding that simple tweaks can fool neural networks in identifying street signs (see Robust Physical-World Attacks on Deep Learning Visual Classification).

The increasing concern of machine learning impacting people’s lives found a strong advocate in Prof. David Parnas, who expressed his concern in an ACM communication article. These challenges are also reflected in new IEEE standardization initiatives. With data science and deep learning becoming increasingly pervasive in the contemporary world, it is now imperative to engage software engineers and machine learning experts in in-depth conversations about the necessary perspectives, approaches, and roadmaps to address these challenges and concerns.

We are interested in (but not limited to) discussing the following topics concerning software-intensive machine learning applications “in the wild”:

  • Architecture and software design
  • Model/data verification and validation
  • Change management
  • User experience evaluation and adjustment
  • Privacy, safety, security issues and ethical concerns

The theme of SEMLA 2024 is “Verification, Validation, and Operations of AI Systems”. This year, we are pleased to have world-renowed speakers from academia and industry, from the software engineering and machine learning communities. Our program includes academic and industry talks, panels on research, practice, and education, as well as two tutorials on AI software testing (from academic and industry). We encourage and welcome experts from all sub-fields of software engineering and machine learning to participate in such a discussion.


Polytechnique Montréal (in person)
Address: 2500 Chem. de Polytechnique, Montréal, QC H3T 1J4
Presentation sessions: Building: Pavillon Principal — Room: Amphithéâtre Bernard‑Lamarre
Poster session and reception: Building: Pavillon Lassonde — Roon=m: Atrium Lassonde (M-3500)

Streaming channels

Youtube Streaming
Zoom Meeting


Online registration is available here.

General (Entire event):  $250 (plus taxes)
General (1st day – Industry Track): $150 (plus taxes)
General (2nd day – Research Track): $150 (plus taxes)
General Student Admission: $75 (plus taxes)
Polytechnique Students and Faculty: $5.75

These low fees are possible thanks to the contributions of the Département de génie informatique et génie logiciel of Polytechnique Montreal and the Institute for Data Valorization (IVADO).